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40 Commits

Author SHA1 Message Date
Guido Cossu 2223cf0f4b Layout changes and typo fixes 2018-03-23 10:32:57 +00:00
Guido Cossu 56d1308477 Updated the list of configuration flags 2018-03-21 10:42:35 +00:00
Guido Cossu a88ce1a573 More changes to the comm flags docs 2018-03-21 10:32:04 +00:00
Guido Cossu 6c9b8e2850 Small fix 2018-03-21 10:28:39 +00:00
Guido Cossu 90b8e57765 Shared mem support flags 2018-03-21 10:25:04 +00:00
Guido Cossu ae6dcd057d Fixing typo 2018-03-19 15:37:06 +00:00
Guido Cossu f8721a4388 Font size on the web 2018-03-15 17:48:45 +00:00
Guido Cossu 38f93f7e12 Adding pdf generation capabilities 2018-03-15 17:01:59 +00:00
Guido Cossu 7c51dc07f1 Adding support for Skylake AVX512 for GCC 2018-01-28 17:01:33 +01:00
Guido Cossu 4931505e5a Small correction in the HMC 2017-05-12 11:17:16 +01:00
Guido Cossu 2099047b06 Updating for version 0.7.0. Adding HMC docs 2017-05-12 11:10:36 +01:00
Guido Cossu 0fb307ae17 Adding SITMO reference 2017-02-02 10:14:54 +00:00
Guido Cossu 2b100d76f2 Adding one flag in comms 2016-11-08 13:59:22 +00:00
Guido Cossu 04160eaa30 Adding more details on the travis tests 2016-11-08 10:11:18 +00:00
Guido Cossu 6cb9d2935f Adding images and more comment on Travis 2016-11-07 11:36:47 +00:00
Guido Cossu ac7f845583 Small change in naming of the pages 2016-11-04 19:26:48 +00:00
Guido Cossu ff057145b4 Adding Dslash flags explanation 2016-11-04 19:20:14 +00:00
Guido Cossu 9fdb209b7e Dropping the logo 2 2016-11-04 16:46:00 +00:00
Guido Cossu 2d324f53cc Dropping the logo 2016-11-04 16:44:34 +00:00
Guido Cossu f250133dc5 Debugging octicon 2016-11-04 16:31:34 +00:00
Guido Cossu 8d61a552e4 Debug again 2016-11-04 16:30:27 +00:00
Guido Cossu 84cac60ca9 Other debug 2016-11-04 16:27:26 +00:00
Guido Cossu dfd7a2e86e Debugging bug_Report file 2016-11-04 16:16:38 +00:00
Guido Cossu 23666f20c1 Update of Gemfile 2016-11-04 16:14:11 +00:00
Guido Cossu 44f33e47d7 Cleaning the readme file 2016-11-04 16:10:40 +00:00
Guido Cossu b1bd88cfba Adding the initial documentation 2016-11-04 16:07:25 +00:00
Guido Cossu d63110d26f Revert pygments to rouge 2016-10-31 10:03:53 +00:00
Guido Cossu a170855d84 Adding local config file for testing purposes 2016-10-31 10:01:30 +00:00
Guido Cossu 416bd9a874 Correcting the quick start 2016-10-30 16:56:30 +00:00
Guido Cossu bc9427c38c Quick-start guide 2016-10-30 16:53:01 +00:00
Guido Cossu 188d9472da Base url 2016-10-26 17:03:32 +01:00
Guido Cossu dc6951f43e Other commit 2016-10-26 17:01:58 +01:00
Guido Cossu 2deeef622b Change in the config.yml 2016-10-26 16:45:33 +01:00
Guido Cossu 8ec1950718 Refactoring of the gh pages 2016-10-26 16:35:05 +01:00
Guido Cossu dc942d5d56 Added github pages support to Jekyll 2016-10-12 16:07:58 +01:00
Guido Cossu b3de0f922a More tests on jekyll 2016-10-12 12:21:42 +01:00
Guido Cossu 3c0931cca9 Adding full Jekyll site 2016-10-12 12:10:54 +01:00
Guido Cossu d75906f517 Adding Jekyll support 2016-10-11 17:12:54 +01:00
Guido Cossu c354838200 Deleting travis CI by now 2016-10-11 17:02:26 +01:00
Guido Cossu 3292924e6e First commit on gh-pages 2016-10-11 17:02:01 +01:00
1548 changed files with 24879 additions and 259674 deletions
-54
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name: Bug report
description: Report a bug.
title: "<insert title>"
labels: [bug]
body:
- type: markdown
attributes:
value: >
Thank you for taking the time to file a bug report.
Please check that the code is pointing to the HEAD of develop
or any commit in master which is tagged with a version number.
- type: textarea
attributes:
label: "Describe the issue:"
description: >
Describe the issue and any previous attempt to solve it.
validations:
required: true
- type: textarea
attributes:
label: "Code example:"
description: >
If relevant, show how to reproduce the issue using a minimal working
example.
placeholder: |
<< your code here >>
render: shell
validations:
required: false
- type: textarea
attributes:
label: "Target platform:"
description: >
Give a description of the target platform (CPU, network, compiler).
Please give the full CPU part description, using for example
`cat /proc/cpuinfo | grep 'model name' | uniq` (Linux)
or `sysctl machdep.cpu.brand_string` (macOS) and the full output
the `--version` option of your compiler.
validations:
required: true
- type: textarea
attributes:
label: "Configure options:"
description: >
Please give the exact configure command used and attach
`config.log`, `grid.config.summary` and the output of `make V=1`.
render: shell
validations:
required: true
+6 -120
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# Doxygen stuff
html/*
latex/*
# Exclude directories
_site
.sass-cache
.jekyll-metadata
pdf
# Compiled Object files #
#########################
*.slo
*.lo
*.o
*.obj
# Editor files #
################
# Exclude backup files
*~
*#
*.sublime-*
# Precompiled Headers #
#######################
*.gch
*.pch
# Compiled Dynamic libraries #
##############################
*.so
*.dylib
*.dll
# Fortran module files #
########################
*.mod
# Compiled Static libraries #
#############################
*.lai
*.la
*.a
*.lib
# Executables #
###############
*.exe
*.out
*.app
# http://www.gnu.org/software/automake #
########################################
Makefile.in
Makefile
Config.h
Config.h.in
config.log
config.status
.deps
Make.inc
eigen.inc
Eigen.inc
# http://www.gnu.org/software/autoconf #
########################################
autom4te.cache
aclocal.m4
compile
configure
depcomp
install-sh
missing
stamp-h1
config.sub
config.guess
INSTALL
.dirstamp
ltmain.sh
# Logs and databases #
######################
*.log
*.sql
*.sqlite
# OS generated files #
######################
.DS_Store
.DS_Store?
._*
.Spotlight-V100
.Trashes
ehthumbs.db
Thumbs.db
.dirstamp
# build directory #
###################
build*/*
Documentation/_build
# IDE related files #
#####################
*.xcodeproj/*
build.sh
.vscode
*.code-workspace
# Eigen source #
################
Grid/Eigen
Eigen/*
# libtool macros #
##################
m4/lt*
m4/libtool.m4
# github pages #
################
gh-pages/
# generated sources #
#####################
Grid/qcd/spin/gamma-gen/*.h
Grid/qcd/spin/gamma-gen/*.cc
Grid/util/Version.h
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Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: Peter Boyle <peterboyle@MacBook-Pro.local>
Author: paboyle <paboyle@ph.ed.ac.uk>
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mpicxx -qmkl=parallel -fsycl BatchBlasBench.cc -o BatchBlasBench -DGRID_SYCL
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CXX=hipcc
MPICXX=mpicxx
CXXFLAGS="-fPIC -I{$ROCM_PATH}/include/ -I${MPICH_DIR}/include -L/lib64 -I/opt/cray/pe/mpich/8.1.28/ofi/gnu/12.3/include -DGRID_HIP"
LDFLAGS="-L/lib64 -L${MPICH_DIR}/lib -lmpi -L${CRAY_MPICH_ROOTDIR}/gtl/lib -lmpi_gtl_hsa -lamdhip64 -lhipblas -lrocblas -lmpi_gnu_123"
hipcc $CXXFLAGS $LDFLAGS BatchBlasBench.cc -o BatchBlasBench
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mpicxx -qmkl=parallel -fsycl BatchBlasBench.cc -o BatchBlasBench -DGRID_SYCL
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## [3.4.8](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.4.8)
### Enhancements
- Improve type readability for larger viewports by bumping up base `font-size`. [#533](https://github.com/mmistakes/minimal-mistakes/issues/533)
- Update Portuguese localized UI text. [#541](https://github.com/mmistakes/minimal-mistakes/pull/541)
- Add `page.title` and via parameter to Twitter share link. [#538](https://github.com/mmistakes/minimal-mistakes/pull/538)
### Bug Fixes
- Fix Last.fm author profile URL. [#540](https://github.com/mmistakes/minimal-mistakes/pull/540)
### Maintenance
- Move Brazilian Portuguese localized text under `pt-BR` key.
## [3.4.7](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.4.7)
### Enhancements
- Add `layout` based and user-defined class names to `<body>` element for added CSS hooks. [#526](https://github.com/mmistakes/minimal-mistakes/pull/526)
- Add simplified Chinese localized UI text. [#532](https://github.com/mmistakes/minimal-mistakes/pull/532)
### Bug Fixes
- Remove duplicate include of `base_path` in category-list.html [#522](https://github.com/mmistakes/minimal-mistakes/pull/522)
## [3.4.6](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.4.6)
### Enhancements
- Add Italian "comments" related localized UI text. [#514](https://github.com/mmistakes/minimal-mistakes/pull/514)
### Bug Fixes
- Disable `compress` HTML layout by default. To enable add `layout: compress` to `_layouts/default.html`.
## [3.4.5](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.4.5)
### Enhancements
- Improve line numbered code block styling when using `{% highlight linenos %}` tag. [#513](https://github.com/mmistakes/minimal-mistakes/issues/513)
- Add English fallback to "Follow" button label. [#496](https://github.com/mmistakes/minimal-mistakes/pull/496)
### Bug Fixes
- Fix Firefox alignment issues with code blocks generated with the `{% highlight %}` tag. [#512](https://github.com/mmistakes/minimal-mistakes/issues/512)
### Maintenance
- Clarified comment for `author.stackoverflow` value used in author sidebar links. [#487](https://github.com/mmistakes/minimal-mistakes/pull/487)
- Add list of localized text strings. [#488](https://github.com/mmistakes/minimal-mistakes/pull/488)
- Add `{% highlight %}` code block examples to demo site.
- Add documentation for using custom sidebar navigation menus. [#476](https://github.com/mmistakes/minimal-mistakes/issues/476)
## [3.4.4](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.4.4)
### Enhancements
- Add French "comments" related localized UI text. [#472](https://github.com/mmistakes/minimal-mistakes/pull/472)
### Bug Fixes
- Exclude `vendor` in Jekyll config file.
- Fix Liquid syntax error for offending parenthesis. [#479](https://github.com/mmistakes/minimal-mistakes/issues/479)
### Maintenance
- Update gems: `colorator` (1.1.0), `forwardable-extended` (2.6.0), `github-pages` (93), `jekyll` (= 3.2.1), `minima` (= 1.0.1).
## [3.4.3](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.4.3)
### Enhancements
- Make ["honeypot" `input`](https://github.com/mmistakes/minimal-mistakes/commit/06a8249a69a37dddda7e2a5bfbe32056c1a9a607) in Staticman comment form less obvious to spam bots
- Add padding to `.highlight` code blocks to better [align `overflow` scrollbar](https://github.com/mmistakes/minimal-mistakes/commit/e4abec0a6f7f8cff72505ca0754615df294fd5b3) to the bottom.
- Add additional image options for Twitter card social sharing meta tags. [#466](https://github.com/mmistakes/minimal-mistakes/pull/466)
- Add structured data markup for Staticman comments. [#458](https://github.com/mmistakes/minimal-mistakes/issues/458)
### Bug Fixes
- Format `og:locale` tag with `_` instead of `-`. [#462](https://github.com/mmistakes/minimal-mistakes/issues/462)
### Maintenance
- Add note to docs about using `url: http://localhost:4000` when working locally.
## [3.4.2](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.4.2)
### Enhancements
- Improve UX of static comment forms. [#448](https://github.com/mmistakes/minimal-mistakes/issues/448)
## [3.4.1](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.4.1)
### Enhancements
- Add `staticman.filename` configuration with UNIX timestamp for sorting data files. example ~> `comment-1470943149`.
### Bug Fixes
- Don't add `<a>` to author name if URL is blank.
## [3.4.0](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.4.0)
### Enhancements
- Support static-based commenting via [Staticman](https://staticman.net/) for sites hosted with GitHub Pages. [#424](https://github.com/mmistakes/minimal-mistakes/issues/424)
## [3.3.7](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.3.7)
### Bug Fixes
- Re-enabled Jekyll plugins in `_config.yml` in case they aren't autoloaded in `Gemfile`. [#417](https://github.com/mmistakes/minimal-mistakes/issues/417)
### Enhancements
- Fallback to `site.github.url` for use in `{{ base_path }}` when `site.url` is `nil`.
- Replace Sass and Autoprefixer `npm` build scripts with [Jekyll's built-in asset support](https://jekyllrb.com/docs/assets/). [#333](https://github.com/mmistakes/minimal-mistakes/issues/333)
### Maintenance
- Document `site.repository` and its role with [`github-metadata`](https://github.com/jekyll/github-metadata) gem.
- Add sample [archive page with content](https://mmistakes.github.io/minimal-mistakes/archive-layout-with-content/) for testing styles on demo site.
## [3.3.6](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.3.6)
### Bug Fixes
- Fix blank `site.teaser` bug. [#412](https://github.com/mmistakes/minimal-mistakes/issues/412)
## [3.3.5](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.3.5)
### Enhancements
- Add English default text `site.locale` strings. [#407](https://github.com/mmistakes/minimal-mistakes/issues/407)
- Add Portuguese localized UI text. [#411](https://github.com/mmistakes/minimal-mistakes/pull/411)
- Add Italian localized UI text. [#409](https://github.com/mmistakes/minimal-mistakes/pull/409)
### Maintenance
- Remove unused Google AdSense variables in `_config.yml`. [#404](https://github.com/mmistakes/minimal-mistakes/issues/404)
- Update `Gemfile` instructions for using `github-pages` vs. native `jekyll` gems.
- Disable `gems:` in `_config.yml` and enable plugins with Bundler instead.
- Add `repository` to `_config.yml` to suppress GitHub Pages error `Liquid Exception: No repo name found.`
## [3.3.4](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.3.4)
### Enhancements
- Add support for configurable feed URL to use a service like FeedBurner instead of linking directly to `feed.xml` in `<head>` and the site footer. [#378](https://github.com/mmistakes/minimal-mistakes/issues/378), [#379](https://github.com/mmistakes/minimal-mistakes/pull/379), [#406](https://github.com/mmistakes/minimal-mistakes/pull/406)
- Add Turkish localized UI text. [#403](https://github.com/mmistakes/minimal-mistakes/pull/403)
### Maintenance
- Update gems: `activesupport` (4.2.7), `ffi` (1.9.14), `github-pages` (88), `jekyll-redirect-from` (0.11.0), `jekyll-watch` (1.5.0).
## [3.3.3](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.3.3)
### Enhancements
- Make footer stick to the bottom of the page.
### Bug Fixes
- Fix `gallery` size bug [#402](https://github.com/mmistakes/minimal-mistakes/issues/402)
### Maintenance
- Set default `lang` to `en`.
## [3.3.2](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.3.2)
### Bug Fixes
- Fix JavaScript that triggers "sticky" sidebar to avoid layout issues on screen sizes < `1024px`. [#396](https://github.com/mmistakes/minimal-mistakes/issues/396)
## [3.3.1](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.3.1)
### Enhancements
- Enable image popup on < 500px wide screens. [#385](https://github.com/mmistakes/minimal-mistakes/issues/385)
- Indicate the relationship between component URLs in a paginated series by applying `rel="prev"` and `rel="next"` to pages that use `site.paginator`. [#253](https://github.com/mmistakes/minimal-mistakes/issues/253)
- Improve link posts in archive listings. [#276](https://github.com/mmistakes/minimal-mistakes/issues/276)
### Maintenance
- Update gems: `github-pages` (86), `ffi` 1.9.13, `jekyll-mentions` 1.1.3, and `rouge` 1.11.1
- Fix note about custom sidebar content appearing below author profile. [#388](https://github.com/mmistakes/minimal-mistakes/issues/388)
## [3.2.13](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.13)
### Enhancements
- Add English default UI text for Canada, Great Britain, and Australia. [#377](https://github.com/mmistakes/minimal-mistakes/issues/377)
- Switch default locale from `en-US` to `en`.
## [3.2.12](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.12)
### Enhancements
- Remove window width "magic number" from sticky sidebar check in `main.js` for improved flexibility. [#375](https://github.com/mmistakes/minimal-mistakes/pull/375)
### Bug Fixes
- Fix author override conditional where a missing `authors.yml` would show broken sidebar content. Defaults to `site.author`. [#376](https://github.com/mmistakes/minimal-mistakes/pull/376)
## [3.2.11](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.11)
### Bug Fixes
- Fix disappearing author sidebar links [#372](https://github.com/mmistakes/minimal-mistakes/issues/372)
### Maintenance
- Update gems: `github-pages` (84), `jekyll-github-metadata` 2.0.2, and `kramdown` 1.11.1
- Update vendor JavaScript: jQuery 1.12.4, Stickyfill.js 1.1.4
- Update Font Awesome 4.6.3
## [3.2.10](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.10)
### Maintenance
- Add `CONTRIBUTING.md`
## [3.2.9](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.9)
### Enhancements
- Add support for [header overlay images](https://mmistakes.github.io/minimal-mistakes/docs/layouts/#header-overlay) for Open Graph images. [#358](https://github.com/mmistakes/minimal-mistakes/pull/358)
### Bug Fixes
- Fix `Person` typo Schema.org type [#358](https://github.com/mmistakes/minimal-mistakes/pull/358)
### Maintenance
- Update `github-pages` gem and dependencies.
- Remove `minutes_read` to avoid awkward reading time wording [#356](https://github.com/mmistakes/minimal-mistakes/issues/356)
## [3.2.8](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.8)
### Bug Fixes
- Remove `cursor: pointer` that appears on white-space surrounding author side list items and links. [#354](https://github.com/mmistakes/minimal-mistakes/pull/354)
### Maintenance
- Add contributing information to `README.md`. [#357](https://github.com/mmistakes/minimal-mistakes/issues/357)
## [3.2.7](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.7)
### Enhancements
- Add French localized UI text. [#346](https://github.com/mmistakes/minimal-mistakes/pull/346)
### Bug Fixes
- Fix branch logic for Yandex and Alexa in `seo.html`. [#348](https://github.com/mmistakes/minimal-mistakes/pull/348)
## [3.2.6](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.6)
### Bug Fixes
- Fix error `Liquid Exception: divided by 0 in _includes/archive-single.html, included in _layouts/single.html` caused by null `words_per_minute` in `_config.yml`. [#345](https://github.com/mmistakes/minimal-mistakes/pull/345)
## [3.2.5](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.5)
### Bug Fixes
- Fix link color in hero overlay to be white.
- Remove underlines from archive item titles.
## [3.2.4](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.4)
### Enhancements
- Improve text alignment of masthead, hero overlay, page footer to be flush left and remove awkward white-space gaps. [#342](https://github.com/mmistakes/minimal-mistakes/issues/342)
- Add Spanish localized UI text. [#338](https://github.com/mmistakes/minimal-mistakes/pull/338)
### Bug Fixes
- Fix alignment of icons in author sidebar [#341](https://github.com/mmistakes/minimal-mistakes/issues/341)
### Maintenance
- Add background color to page footer to set it apart from main content. [#342](https://github.com/mmistakes/minimal-mistakes/issues/342)
- Add terms and privacy policy to theme's demo site. [#343](https://github.com/mmistakes/minimal-mistakes/issues/343)
- Update screenshots found in theme documentation.
## [3.2.3](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.3)
### Enhancements
- Add [Discourse](https://www.discourse.org/) as a commenting provider. [#335](https://github.com/mmistakes/minimal-mistakes/pull/335)
## [3.2.2](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.2)
### Enhancements
- Add support for image captions in Magnific Popup overlays via the [`gallery`](https://mmistakes.github.io/minimal-mistakes/docs/helpers/#gallery) helper. [#334](https://github.com/mmistakes/minimal-mistakes/issues/334)
## [3.2.1](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.1)
### Bug Fixes
- Remove need for "double tapping" masthead menu links on iOS devices. [#315](https://github.com/mmistakes/minimal-mistakes/issues/315)
### Maintenance
- Add `ISSUE_TEMPLATE.md` for improve issue submission process.
## [3.2.0](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.2.0)
### Bug Fixes
- Fix missing category/tag links in post footer due to possible conflict with `site.tags` and `site.categories`. [#329](https://github.com/mmistakes/minimal-mistakes/issues/329#issuecomment-222375568)
## [3.1.8](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.1.8)
### Bug Fixes
- Fix `Liquid Exception: undefined method 'gsub' for nil:NilClass in _layouts/single.html` error when `page.title` is null. `<h1>` element is now conditional if `title: ` is not set for a `page` or collection item. [#312](https://github.com/mmistakes/minimal-mistakes/issues/312)
### Maintenance
- Remove duplicate `fa-twitter` and `fa-twitter-square` classes from `_utilities.scss`. [#302](https://github.com/mmistakes/minimal-mistakes/issues/302)
- Document installing additional Jekyll gem dependencies when using `gem "jekyll"` instead of `gem "github-pages"` to avoid any errors on run. [#305](https://github.com/mmistakes/minimal-mistakes/issues/305)
## [3.1.7](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.1.7)
### Enhancements
- Add translation key for "Recent Posts" used in home page `index.html`. [#316](https://github.com/mmistakes/minimal-mistakes/pull/316)
### Maintenance
- Small fix to avoid underlying the whitespace between icons and related text when hovering. [#303](https://github.com/mmistakes/minimal-mistakes/pull/303)
## [3.1.6](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.1.6)
### Maintenance
- Update gem dependencies. Run `bundle` to update `Gemfile.lock`.
## [3.1.5](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.1.5)
### Maintenance
- Fix `www` and `https` links in author profile include [#293](https://github.com/mmistakes/minimal-mistakes/pull/293)
## [3.1.4](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.1.4)
### Enhancements
- Add overlay_filter param to hero headers [#298](https://github.com/mmistakes/minimal-mistakes/pull/298)
## [3.1.3](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.1.3)
### Enhancements
- Improve `site.locale` documentation [#284](https://github.com/mmistakes/minimal-mistakes/issues/284)
- Remove ProTip note about protocol-less `site.url` as it is an anti-pattern [#288](https://github.com/mmistakes/minimal-mistakes/issues/288)
### Bug Fixes
- Fix `og_image` URL in seo.html [#277](https://github.com/mmistakes/minimal-mistakes/issues/277)
- Fix `author_profile` toggle when assigned in a `_layout` [#285](https://github.com/mmistakes/minimal-mistakes/issues/285)
- Fix typo in `build:all` npm script [#283](https://github.com/mmistakes/minimal-mistakes/pull/283)
- Fix URL typo documentation [#287](https://github.com/mmistakes/minimal-mistakes/issues/287)
- SEO author bug. If `twitter.username` is set and `author.twitter` is `nil` bad things happen. [#289](https://github.com/mmistakes/minimal-mistakes/issues/289)
## [3.1.2](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.1.2)
### Enhancements
- Explain how to use `nav_list` helper in [documentation](https://mmistakes.github.io/minimal-mistakes/docs/helpers/#navigation-list).
- Reduce left/right padding on smaller screens to increase width of main content column.
### Bug Fixes
- Fix alignment issues with related posts [#273](https://github.com/mmistakes/minimal-mistakes/issues/273) and "Follow" button in author profile [#274](https://github.com/mmistakes/minimal-mistakes/issues/274).
## [3.1.1](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.1.1)
### Bug Fix
- Fixed reading time bug when `words_per_minute` wasn't set in `_config.yml` [#271](https://github.com/mmistakes/minimal-mistakes/issues/271)
## [3.1.0](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.1.0)
### Enhancements
- Updated [Font Awesome](https://fortawesome.github.io/Font-Awesome/whats-new/) to version 4.6.1
- Added optional GitHub and Bitbucket links to footer if set on `site.author` in `_config.yml`.
### Bug Fixes
- Fixed Bitbucket URL typo in author sidebar.
## [3.0.3](https://github.com/mmistakes/minimal-mistakes/releases/tag/3.0.3)
### Enhancements
- Rebuilt the entire theme: layouts, includes, stylesheets, scripts, you name it.
- Refreshed the look and feel while staying true to the original design of the theme (author sidebar/main content).
- Replaced grid system with [Susy](http://susy.oddbird.net/).
- Replaced Grunt tasks with `npm` scripts.
- Removed Google Fonts and replaced with system fonts to improve performance (they can be [added back](https://mmistakes.github.io/minimal-mistakes/docs/stylesheets/) if desired)
- Greatly improved [theme documentation](https://mmistakes.github.io/minimal-mistakes/docs/quick-start-guide/).
- Increased the amount of sample posts, sample pages, and sample collections to throughly test the theme and edge-cases.
- Moved all sample content and assets out of `master` to keep it as clean as possible for forking.
- Added new layouts for `splash` pages, archives for [`jekyll-archives`](https://github.com/jekyll/jekyll-archives) if enabled, and [`compress.html`](https://github.com/penibelst/jekyll-compress-html) to improve performance.
- Added taxonomy links to posts (tags and categories).
- Added optional "reading time" meta data.
- Improved Liquid used for Twitter Cards and Open Graph data in `<head>`.
- Improved `gallery` include helper and added `feature_row` for use with splash page layout.
- Added Keybase.io, author web URI, and Bitbucket optional links to sidebar.
- Add `feed.xml` link to footer.
- Added a [UI text data file](https://mmistakes.github.io/minimal-mistakes/docs/ui-text/) to easily change all text found in the theme.
- Added LinkedIn to optional social share buttons.
- Added Facebook, Google+, and custom commenting options in addition to Disqus.
- Added optional breadcrumb links.
## [2.2.1](https://github.com/mmistakes/minimal-mistakes/releases/tag/2.2.1)
## [2.2.0](https://github.com/mmistakes/minimal-mistakes/releases/tag/2.2.0)
### Enhancements
- Add support for Jekyll 3.0
- Minor updates to syntax highlighting CSS and theme documentation
## [2.1.3](https://github.com/mmistakes/minimal-mistakes/releases/tag/2.1.3)
### Enhancements
- Cleaner print styles that remove the top navigation, social sharing buttons, and other elements not needed when printed.
## [2.1.2](https://github.com/mmistakes/minimal-mistakes/releases/tag/2.1.2)
### Enhancements
- Add optional CodePen icon/url to author side bar [#156](https://github.com/mmistakes/minimal-mistakes/pull/156)
- Documented Stackoverflow username explanation in `_config.yml` [#157](https://github.com/mmistakes/minimal-mistakes/pull/157)
- Simplified Liquid in `post-index.html` to better handle year listings [#166](https://github.com/mmistakes/minimal-mistakes/pull/166)
### Bug Fixes
- Cleanup Facebook related Open Graph meta tags [#149](https://github.com/mmistakes/minimal-mistakes/issues/149)
- Corrected minor typos [#158](https://github.com/mmistakes/minimal-mistakes/pull/158) [#175](https://github.com/mmistakes/minimal-mistakes/issues/175)
## [2.1.1](https://github.com/mmistakes/minimal-mistakes/releases/tag/2.1.1)
### Enhancements
- Add optional XING profile link to author sidebar
- Include open graph meta tags for feature image (if assigned) [#149](https://github.com/mmistakes/minimal-mistakes/issues/149)
- Create an include for feed footer
### Bug Fixes
- Remove http protocol from Google search form on sample 404 page
- Only show related posts if there are one or more available
- Fix alignment of email address link in author sidebar
## [2.1.0](https://github.com/mmistakes/minimal-mistakes/releases/tag/2.1.0)
### Enhancements
- Add optional social sharing buttons ([#42](https://github.com/mmistakes/minimal-mistakes/issues/42))
![social sharing buttons](https://cloud.githubusercontent.com/assets/1376749/5860522/d9f28a96-a22f-11e4-9b83-940a3a9a766a.png)
- Add Soundcloud, YouTube ([#95](https://github.com/mmistakes/minimal-mistakes/pull/95)), Flickr ([#119](https://github.com/mmistakes/minimal-mistakes/pull/119)), and Weibo ([#116](https://github.com/mmistakes/minimal-mistakes/pull/116)) icons for use in author sidebar.
- Fix typos in posts and documentation and remove references to Less
- Include note about Octopress gem being optional
- Post author override support extended to the Atom feed ([#71](https://github.com/mmistakes/minimal-mistakes/pull/71))
- Only include email address in feed if specified in `_config.yml` or author `_data`
- Wrap all page content in `#main` to harmonize article and post index styles ([#86](https://github.com/mmistakes/minimal-mistakes/issues/86))
- Include new sample feature images for posts and pages
- Table of contents improvements: fix collapse toggle, indent nested elements, show on small screens, and create an `_include` for reusing in posts and pages.
- Include note about running Jekyll with `bundle exec` when using Bundler
- Fix home page path in top navigation
- Remove Google Authorship ([#120](https://github.com/mmistakes/minimal-mistakes/issues/120))
- Remove duplicate author content that displayed in `div.article-author-bottom`
- Removed unused `_sass/print.scss` styles
- Improve comments in `.scss` files
## [2.0.0](https://github.com/mmistakes/minimal-mistakes/releases/tag/v2.0)
## [1.3.3](https://github.com/mmistakes/minimal-mistakes/releases/tag/1.3.3)
### Enhancements
- Added new icons and profile links for Stackoverflow, Dribbble, Pinterest, Foursquare, and Steam to the author bio sidebar.
- Cleaned up the Kramdown auto table of contents styling to be more readable
- Removed page width specific .less stylesheets and created mixins for easier updating
- Removed Modernizr since it wasn't being used
- Added pages to sitemap.xml
- Added category: to rake new_post task
- Minor typographic changes
### Bug Fixes
- Corrected various broken links in README and Theme Setup.
## [1.3.1](https://github.com/mmistakes/minimal-mistakes/releases/tag/1.3.1)
### Enhancements
- Cleaned up table of contents styling
- Reworked top navigation to be a better experience on small screens. Nav items now display vertically when the menu button is tapped, revealing links with larger touch targets.
![menu animation](https://camo.githubusercontent.com/3fbd8c1326485f4b1ab32c0005c0fca7660b5d31/68747470733a2f2f662e636c6f75642e6769746875622e636f6d2f6173736574732f313337363734392f323136343037352f31653366303663322d393465372d313165332d383961612d6436623636376562306564662e676966)
## [1.2.0](https://github.com/mmistakes/minimal-mistakes/releases/tag/1.2.0)
### Bug Fixes
- Table weren't filling the entire width of the content container. They now scale at 100%. Thanks [@dhruvbhatia](https://github.com/dhruvbhatia)
### Enhancements
- Decreased spacing between Markdown footnotes
- Removed dark background on footer
- Removed UPPERCASE styling on post titles in the index listing
## [1.1.4](https://github.com/mmistakes/minimal-mistakes/releases/tag/1.1.4)
### Bug Fixes
- Fix top navigation bug issue ([#10](https://github.com/mmistakes/minimal-mistakes/issues/10)) for real this time. Remember to clear your floats kids.
## [1.1.3](https://github.com/mmistakes/minimal-mistakes/releases/tag/1.1.3)
### Bug Fixes
- Fix top navigation links that weren't click able on small viewports (Issue [#10](https://github.com/mmistakes/minimal-mistakes/issues/10)).
- Remove line wrap from top navigation links that may span multiple lines.
## [1.1.2](https://github.com/mmistakes/minimal-mistakes/releases/tag/1.1.2)
### Enhancements
- Added Grunt build script for compiling Less/JavaScript and optimizing image assets.
- Added support for large image summary Twitter card.
- Stylesheet adjustments
## [1.1.1](https://github.com/mmistakes/minimal-mistakes/releases/tag/1.1.1)
### Bug Fixes
- Removed [Typeplate](http://typeplate.com/) styles. Was [causing issues with newer versions of Less](https://github.com/typeplate/typeplate.github.io/issues/108) and is no longer maintained.
### Enhancements
- Added [image attribution](http://mmistakes.github.io/minimal-mistakes/theme-setup/#feature-images) for post and page feature images.
- Added [404 page](http://mmistakes.github.io/minimal-mistakes/404.html).
- Cleaned up various Less variables to better align with naming conventions used in other MM Jekyll themes.
- Removed Chrome Frame references.
- Added global CSS3 transitions to text and block elements.
- Improved typography in a few places.
## [1.0.2](https://github.com/mmistakes/minimal-mistakes/releases/tag/v1.0.2)
### Enhancements
- Google Analytics, Google Authorship, webmaster verifies, and Twitter card meta are now optional.
## [1.0.1](https://github.com/mmistakes/minimal-mistakes/releases/tag/v1.0.1)
-5
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@@ -1,5 +0,0 @@
Version : 0.8.0
- Clang 3.5 and above, ICPC v16 and above, GCC 6.3 and above recommended
- MPI and MPI3 comms optimisations for KNL and OPA finished
- Half precision comms
+27
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@@ -0,0 +1,27 @@
source "https://rubygems.org"
# Hello! This is where you manage which Jekyll version is used to run.
# When you want to use a different version, change it below, save the
# file and run `bundle install`. Run Jekyll with `bundle exec`, like so:
#
# bundle exec jekyll serve
#
# This will help ensure the proper Jekyll version is running.
# Happy Jekylling!
gem "github-pages", group: :jekyll_plugins
# If you want to use Jekyll native, uncomment the line below.
# To upgrade, run `bundle update`.
# gem "jekyll"
gem "wdm", "~> 0.1.0" if Gem.win_platform?
# If you have any plugins, put them here!
group :jekyll_plugins do
# gem "jekyll-archives"
gem 'jekyll-octicons'
end
+155
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@@ -0,0 +1,155 @@
GEM
remote: https://rubygems.org/
specs:
activesupport (4.2.7)
i18n (~> 0.7)
json (~> 1.7, >= 1.7.7)
minitest (~> 5.1)
thread_safe (~> 0.3, >= 0.3.4)
tzinfo (~> 1.1)
addressable (2.4.0)
coffee-script (2.4.1)
coffee-script-source
execjs
coffee-script-source (1.10.0)
colorator (1.1.0)
ethon (0.9.1)
ffi (>= 1.3.0)
execjs (2.7.0)
faraday (0.9.2)
multipart-post (>= 1.2, < 3)
ffi (1.9.14)
ffi (1.9.14-x64-mingw32)
forwardable-extended (2.6.0)
gemoji (2.1.0)
github-pages (104)
activesupport (= 4.2.7)
github-pages-health-check (= 1.2.0)
jekyll (= 3.3.0)
jekyll-avatar (= 0.4.2)
jekyll-coffeescript (= 1.0.1)
jekyll-feed (= 0.8.0)
jekyll-gist (= 1.4.0)
jekyll-github-metadata (= 2.2.0)
jekyll-mentions (= 1.2.0)
jekyll-paginate (= 1.1.0)
jekyll-redirect-from (= 0.11.0)
jekyll-sass-converter (= 1.3.0)
jekyll-seo-tag (= 2.1.0)
jekyll-sitemap (= 0.12.0)
jekyll-swiss (= 0.4.0)
jemoji (= 0.7.0)
kramdown (= 1.11.1)
liquid (= 3.0.6)
listen (= 3.0.6)
mercenary (~> 0.3)
minima (= 2.0.0)
rouge (= 1.11.1)
terminal-table (~> 1.4)
github-pages-health-check (1.2.0)
addressable (~> 2.3)
net-dns (~> 0.8)
octokit (~> 4.0)
public_suffix (~> 1.4)
typhoeus (~> 0.7)
html-pipeline (2.4.2)
activesupport (>= 2)
nokogiri (>= 1.4)
i18n (0.7.0)
jekyll (3.3.0)
addressable (~> 2.4)
colorator (~> 1.0)
jekyll-sass-converter (~> 1.0)
jekyll-watch (~> 1.1)
kramdown (~> 1.3)
liquid (~> 3.0)
mercenary (~> 0.3.3)
pathutil (~> 0.9)
rouge (~> 1.7)
safe_yaml (~> 1.0)
jekyll-avatar (0.4.2)
jekyll (~> 3.0)
jekyll-coffeescript (1.0.1)
coffee-script (~> 2.2)
jekyll-feed (0.8.0)
jekyll (~> 3.3)
jekyll-gist (1.4.0)
octokit (~> 4.2)
jekyll-github-metadata (2.2.0)
jekyll (~> 3.1)
octokit (~> 4.0, != 4.4.0)
jekyll-mentions (1.2.0)
activesupport (~> 4.0)
html-pipeline (~> 2.3)
jekyll (~> 3.0)
jekyll-octicons (3.0.1)
jekyll (~> 3.1)
octicons (~> 3.0)
jekyll-paginate (1.1.0)
jekyll-redirect-from (0.11.0)
jekyll (>= 2.0)
jekyll-sass-converter (1.3.0)
sass (~> 3.2)
jekyll-seo-tag (2.1.0)
jekyll (~> 3.3)
jekyll-sitemap (0.12.0)
jekyll (~> 3.3)
jekyll-swiss (0.4.0)
jekyll-watch (1.5.0)
listen (~> 3.0, < 3.1)
jemoji (0.7.0)
activesupport (~> 4.0)
gemoji (~> 2.0)
html-pipeline (~> 2.2)
jekyll (>= 3.0)
json (1.8.3)
kramdown (1.11.1)
liquid (3.0.6)
listen (3.0.6)
rb-fsevent (>= 0.9.3)
rb-inotify (>= 0.9.7)
mercenary (0.3.6)
mini_portile2 (2.1.0)
minima (2.0.0)
minitest (5.9.1)
multipart-post (2.0.0)
net-dns (0.8.0)
nokogiri (1.6.8.1)
mini_portile2 (~> 2.1.0)
nokogiri (1.6.8.1-x64-mingw32)
mini_portile2 (~> 2.1.0)
octicons (3.0.1)
nokogiri (>= 1.6.3.1)
octokit (4.4.1)
sawyer (~> 0.7.0, >= 0.5.3)
pathutil (0.14.0)
forwardable-extended (~> 2.6)
public_suffix (1.5.3)
rb-fsevent (0.9.8)
rb-inotify (0.9.7)
ffi (>= 0.5.0)
rouge (1.11.1)
safe_yaml (1.0.4)
sass (3.4.22)
sawyer (0.7.0)
addressable (>= 2.3.5, < 2.5)
faraday (~> 0.8, < 0.10)
terminal-table (1.7.3)
unicode-display_width (~> 1.1.1)
thread_safe (0.3.5)
typhoeus (0.8.0)
ethon (>= 0.8.0)
tzinfo (1.2.2)
thread_safe (~> 0.1)
unicode-display_width (1.1.1)
PLATFORMS
ruby
x64-mingw32
DEPENDENCIES
github-pages
jekyll-octicons
BUNDLED WITH
1.13.3
-73
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@@ -1,73 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/DisableWarnings.h
Copyright (C) 2016
Author: Guido Cossu <guido.cossu@ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#ifndef DISABLE_WARNINGS_H
#define DISABLE_WARNINGS_H
#if defined __GNUC__ && __GNUC__>=6
#pragma GCC diagnostic ignored "-Wignored-attributes"
#endif
//disables and intel compiler specific warning (in json.hpp)
#ifdef __ICC
#pragma warning disable 488
#endif
#ifdef __NVCC__
//disables nvcc specific warning in json.hpp
#pragma clang diagnostic ignored "-Wdeprecated-register"
#ifdef __NVCC_DIAG_PRAGMA_SUPPORT__
//disables nvcc specific warning in json.hpp
#pragma nv_diag_suppress unsigned_compare_with_zero
#pragma nv_diag_suppress cast_to_qualified_type
//disables nvcc specific warning in many files
#pragma nv_diag_suppress esa_on_defaulted_function_ignored
#pragma nv_diag_suppress extra_semicolon
#else
//disables nvcc specific warning in json.hpp
#pragma diag_suppress unsigned_compare_with_zero
#pragma diag_suppress cast_to_qualified_type
//disables nvcc specific warning in many files
#pragma diag_suppress esa_on_defaulted_function_ignored
#pragma diag_suppress extra_semicolon
#endif
#endif
// Disable vectorisation in Eigen on the Power8/9 and PowerPC
#ifdef __ALTIVEC__
#define EIGEN_DONT_VECTORIZE
#endif
#ifdef __VSX__
#define EIGEN_DONT_VECTORIZE
#endif
#endif
-50
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@@ -1,50 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/Grid.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: azusayamaguchi <ayamaguc@YAMAKAZE.local>
Author: paboyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
//
// Grid.h
// simd
//
// Created by Peter Boyle on 09/05/2014.
// Copyright (c) 2014 University of Edinburgh. All rights reserved.
//
#ifndef GRID_H
#define GRID_H
#include <Grid/GridCore.h>
#include <Grid/GridQCDcore.h>
#include <Grid/qcd/action/Action.h>
#include <Grid/qcd/utils/GaugeFix.h>
#include <Grid/qcd/utils/CovariantSmearing.h>
#include <Grid/qcd/smearing/Smearing.h>
#include <Grid/parallelIO/MetaData.h>
#include <Grid/qcd/hmc/HMC_aggregate.h>
#endif
-67
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@@ -1,67 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/Grid.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: azusayamaguchi <ayamaguc@YAMAKAZE.local>
Author: paboyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
//
// Grid.h
// simd
//
// Created by Peter Boyle on 09/05/2014.
// Copyright (c) 2014 University of Edinburgh. All rights reserved.
//
#ifndef GRID_BASE_H
#define GRID_BASE_H
#include <Grid/DisableWarnings.h>
#include <Grid/Namespace.h>
#include <Grid/GridStd.h>
#include <Grid/threads/Pragmas.h>
#include <Grid/perfmon/Timer.h>
//#include <Grid/perfmon/PerfCount.h>
#include <Grid/util/Util.h>
#include <Grid/log/Log.h>
#include <Grid/perfmon/Tracing.h>
#include <Grid/allocator/Allocator.h>
#include <Grid/simd/Simd.h>
#include <Grid/threads/ThreadReduction.h>
#include <Grid/serialisation/Serialisation.h>
#include <Grid/util/Sha.h>
#include <Grid/communicator/Communicator.h>
#include <Grid/cartesian/Cartesian.h>
#include <Grid/tensors/Tensors.h>
#include <Grid/lattice/Lattice.h>
#include <Grid/cshift/Cshift.h>
#include <Grid/stencil/Stencil.h>
#include <Grid/stencil/GeneralLocalStencil.h>
#include <Grid/parallelIO/BinaryIO.h>
#include <Grid/algorithms/Algorithms.h>
NAMESPACE_CHECK(GridCore)
#endif
-44
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@@ -1,44 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/Grid.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: azusayamaguchi <ayamaguc@YAMAKAZE.local>
Author: paboyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_QCD_CORE_H
#define GRID_QCD_CORE_H
/////////////////////////
// Core Grid QCD headers
/////////////////////////
#include <Grid/GridCore.h>
#include <Grid/qcd/QCD.h>
#include <Grid/qcd/spin/Spin.h>
#include <Grid/qcd/gparity/Gparity.h>
#include <Grid/qcd/utils/Utils.h>
#include <Grid/qcd/representations/Representations.h>
NAMESPACE_CHECK(GridQCDCore);
#endif
-35
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@@ -1,35 +0,0 @@
#ifndef GRID_STD_H
#define GRID_STD_H
///////////////////
// Std C++ dependencies
///////////////////
#include <cassert>
#include <complex>
#include <memory>
#include <vector>
#include <array>
#include <string>
#include <iostream>
#include <iomanip>
#include <random>
#include <functional>
#include <stdio.h>
#include <stdlib.h>
#include <strings.h>
#include <stdio.h>
#include <signal.h>
#include <ctime>
#include <sys/time.h>
#include <chrono>
#include <zlib.h>
///////////////////
// Grid config
///////////////////
#include "Config.h"
#ifdef TOFU
#undef GRID_COMMS_THREADS
#endif
#endif /* GRID_STD_H */
-75
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@@ -1,75 +0,0 @@
#include <Grid/GridCore.h>
#pragma once
// Force Eigen to use MKL if Grid has been configured with --enable-mkl
#ifdef USE_MKL
#define EIGEN_USE_MKL_ALL
#endif
#if defined __GNUC__
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wdeprecated-declarations"
#endif
/* NVCC save and restore compile environment*/
#ifdef __NVCC__
#pragma push
#ifdef __NVCC_DIAG_PRAGMA_SUPPORT__
#pragma nv_diag_suppress code_is_unreachable
#else
#pragma diag_suppress code_is_unreachable
#endif
#pragma push_macro("__CUDA_ARCH__")
#pragma push_macro("__NVCC__")
#pragma push_macro("__CUDACC__")
#undef __CUDA_ARCH__
#undef __NVCC__
#undef __CUDACC__
#define __NVCC__REDEFINE__
#endif
/* SYCL save and restore compile environment*/
#ifdef GRID_SYCL
#pragma push
#pragma push_macro("__SYCL_DEVICE_ONLY__")
#undef __SYCL_DEVICE_ONLY__
#define EIGEN_DONT_VECTORIZE
#undef EIGEN_USE_SYCL
#define __SYCL__REDEFINE__
#endif
/* HIP save and restore compile environment*/
#ifdef GRID_HIP
#pragma push
#pragma push_macro("__HIP_DEVICE_COMPILE__")
#endif
#define EIGEN_NO_HIP
#include <Grid/Eigen/Dense>
#include <Grid/Eigen/unsupported/CXX11/Tensor>
/* NVCC restore */
#ifdef __NVCC__REDEFINE__
#pragma pop_macro("__CUDACC__")
#pragma pop_macro("__NVCC__")
#pragma pop_macro("__CUDA_ARCH__")
#pragma pop
#endif
/*SYCL restore*/
#ifdef __SYCL__REDEFINE__
#pragma pop_macro("__SYCL_DEVICE_ONLY__")
#pragma pop
#endif
/*HIP restore*/
#ifdef __HIP__REDEFINE__
#pragma pop_macro("__HIP_DEVICE_COMPILE__")
#pragma pop
#endif
#if defined __GNUC__
#pragma GCC diagnostic pop
#endif
-1
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@@ -1 +0,0 @@
#include <Grid/Grid_Eigen_Dense.h>
-81
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@@ -1,81 +0,0 @@
extra_sources=
extra_headers=
if BUILD_COMMS_MPI3
extra_sources+=communicator/Communicator_mpi3.cc
extra_sources+=communicator/Communicator_base.cc
extra_sources+=communicator/SharedMemoryMPI.cc
extra_sources+=communicator/SharedMemory.cc
endif
if BUILD_COMMS_NONE
extra_sources+=communicator/Communicator_none.cc
extra_sources+=communicator/Communicator_base.cc
extra_sources+=communicator/SharedMemoryNone.cc
extra_sources+=communicator/SharedMemory.cc
endif
if BUILD_HDF5
extra_sources+=serialisation/Hdf5IO.cc
extra_headers+=serialisation/Hdf5IO.h
extra_headers+=serialisation/Hdf5Type.h
endif
all: version-cache Version.h
version-cache:
@if [ `git status --porcelain | grep -v '??' | wc -l` -gt 0 ]; then\
a="uncommited changes";\
else\
a="clean";\
fi;\
echo "`git log -n 1 --format=format:"#define GITHASH \\"%H:%d $$a\\"%n" HEAD`" > vertmp;\
if [ -e version-cache ]; then\
d=`diff vertmp version-cache`;\
if [ "$${d}" != "" ]; then\
mv vertmp version-cache;\
rm -f Version.h;\
fi;\
else\
mv vertmp version-cache;\
rm -f Version.h;\
fi;\
rm -f vertmp
Version.h: version-cache
cp version-cache Version.h
.PHONY: version-cache
#
# Libraries
#
include Make.inc
include Eigen.inc
extra_sources+=$(WILS_FERMION_FILES)
extra_sources+=$(STAG_FERMION_FILES)
if BUILD_ZMOBIUS
extra_sources+=$(ZWILS_FERMION_FILES)
endif
if BUILD_GPARITY
extra_sources+=$(GP_FERMION_FILES)
endif
if BUILD_FERMION_REPS
extra_sources+=$(ADJ_FERMION_FILES)
extra_sources+=$(TWOIND_FERMION_FILES)
endif
if BUILD_SP
extra_sources+=$(SP_FERMION_FILES)
extra_sources+=$(SP_TWOIND_FERMION_FILES)
endif
lib_LIBRARIES = libGrid.a
CCFILES += $(extra_sources)
HFILES += $(extra_headers) Config.h Version.h
libGrid_a_SOURCES = $(CCFILES)
libGrid_adir = $(includedir)/Grid
nobase_dist_pkginclude_HEADERS = $(HFILES) $(eigen_files) $(eigen_unsupp_files)
-43
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@@ -1,43 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/Namespace.h
Copyright (C) 2016
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#pragma once
#include <type_traits>
#include <cassert>
#include <exception>
#define NAMESPACE_BEGIN(A) namespace A {
#define NAMESPACE_END(A) }
#define GRID_NAMESPACE_BEGIN NAMESPACE_BEGIN(Grid)
#define GRID_NAMESPACE_END NAMESPACE_END(Grid)
#define NAMESPACE_CHECK(x) struct namespaceTEST##x {}; static_assert(std::is_same<namespaceTEST##x, ::namespaceTEST##x>::value,"Not in :: at" );
#define EXCEPTION_CHECK_BEGIN(A) try {
#define EXCEPTION_CHECK_END(A) } catch ( std::exception e ) { BACKTRACEFP(stderr); std::cerr << __PRETTY_FUNCTION__ << " : " <<__LINE__<< " Caught exception "<<e.what()<<std::endl; throw; }
-84
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@@ -1,84 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/Algorithms.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_ALGORITHMS_H
#define GRID_ALGORITHMS_H
NAMESPACE_CHECK(blas);
#include <Grid/algorithms/blas/BatchedBlas.h>
NAMESPACE_CHECK(algorithms);
#include <Grid/algorithms/SparseMatrix.h>
#include <Grid/algorithms/LinearOperator.h>
#include <Grid/algorithms/Preconditioner.h>
NAMESPACE_CHECK(SparseMatrix);
#include <Grid/algorithms/approx/Zolotarev.h>
#include <Grid/algorithms/approx/Chebyshev.h>
#include <Grid/algorithms/approx/JacobiPolynomial.h>
#include <Grid/algorithms/approx/Remez.h>
#include <Grid/algorithms/approx/MultiShiftFunction.h>
#include <Grid/algorithms/approx/Forecast.h>
#include <Grid/algorithms/approx/RemezGeneral.h>
#include <Grid/algorithms/approx/ZMobius.h>
NAMESPACE_CHECK(approx);
#include <Grid/algorithms/deflation/Deflation.h>
#include <Grid/algorithms/deflation/MultiRHSBlockProject.h>
#include <Grid/algorithms/deflation/MultiRHSDeflation.h>
#include <Grid/algorithms/deflation/MultiRHSBlockCGLinalg.h>
NAMESPACE_CHECK(deflation);
#include <Grid/algorithms/iterative/ConjugateGradient.h>
NAMESPACE_CHECK(ConjGrad);
#include <Grid/algorithms/iterative/BiCGSTAB.h>
NAMESPACE_CHECK(BiCGSTAB);
#include <Grid/algorithms/iterative/ConjugateResidual.h>
#include <Grid/algorithms/iterative/NormalEquations.h>
#include <Grid/algorithms/iterative/SchurRedBlack.h>
#include <Grid/algorithms/iterative/ConjugateGradientMultiShift.h>
#include <Grid/algorithms/iterative/ConjugateGradientMixedPrec.h>
#include <Grid/algorithms/iterative/ConjugateGradientMultiShiftMixedPrec.h>
#include <Grid/algorithms/iterative/ConjugateGradientMixedPrecBatched.h>
#include <Grid/algorithms/iterative/BiCGSTABMixedPrec.h>
#include <Grid/algorithms/iterative/BlockConjugateGradient.h>
#include <Grid/algorithms/iterative/ConjugateGradientReliableUpdate.h>
#include <Grid/algorithms/iterative/MinimalResidual.h>
#include <Grid/algorithms/iterative/GeneralisedMinimalResidual.h>
#include <Grid/algorithms/iterative/CommunicationAvoidingGeneralisedMinimalResidual.h>
#include <Grid/algorithms/iterative/FlexibleGeneralisedMinimalResidual.h>
#include <Grid/algorithms/iterative/FlexibleCommunicationAvoidingGeneralisedMinimalResidual.h>
#include <Grid/algorithms/iterative/MixedPrecisionFlexibleGeneralisedMinimalResidual.h>
#include <Grid/algorithms/iterative/ImplicitlyRestartedLanczos.h>
#include <Grid/algorithms/iterative/PowerMethod.h>
#include <Grid/algorithms/iterative/AdefGeneric.h>
#include <Grid/algorithms/iterative/AdefMrhs.h>
NAMESPACE_CHECK(PowerMethod);
#include <Grid/algorithms/multigrid/MultiGrid.h>
NAMESPACE_CHECK(multigrid);
#include <Grid/algorithms/FFT.h>
#endif
-296
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@@ -1,296 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/Cshift.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef _GRID_FFT_H_
#define _GRID_FFT_H_
#ifdef HAVE_FFTW
#if defined(USE_MKL) || defined(GRID_SYCL)
#include <fftw/fftw3.h>
#else
#include <fftw3.h>
#endif
#endif
NAMESPACE_BEGIN(Grid);
template<class scalar> struct FFTW { };
#ifdef HAVE_FFTW
template<> struct FFTW<ComplexD> {
public:
typedef fftw_complex FFTW_scalar;
typedef fftw_plan FFTW_plan;
static FFTW_plan fftw_plan_many_dft(int rank, const int *n,int howmany,
FFTW_scalar *in, const int *inembed,
int istride, int idist,
FFTW_scalar *out, const int *onembed,
int ostride, int odist,
int sign, unsigned flags) {
return ::fftw_plan_many_dft(rank,n,howmany,in,inembed,istride,idist,out,onembed,ostride,odist,sign,flags);
}
static void fftw_flops(const FFTW_plan p,double *add, double *mul, double *fmas){
::fftw_flops(p,add,mul,fmas);
}
inline static void fftw_execute_dft(const FFTW_plan p,FFTW_scalar *in,FFTW_scalar *out) {
::fftw_execute_dft(p,in,out);
}
inline static void fftw_destroy_plan(const FFTW_plan p) {
::fftw_destroy_plan(p);
}
};
template<> struct FFTW<ComplexF> {
public:
typedef fftwf_complex FFTW_scalar;
typedef fftwf_plan FFTW_plan;
static FFTW_plan fftw_plan_many_dft(int rank, const int *n,int howmany,
FFTW_scalar *in, const int *inembed,
int istride, int idist,
FFTW_scalar *out, const int *onembed,
int ostride, int odist,
int sign, unsigned flags) {
return ::fftwf_plan_many_dft(rank,n,howmany,in,inembed,istride,idist,out,onembed,ostride,odist,sign,flags);
}
static void fftw_flops(const FFTW_plan p,double *add, double *mul, double *fmas){
::fftwf_flops(p,add,mul,fmas);
}
inline static void fftw_execute_dft(const FFTW_plan p,FFTW_scalar *in,FFTW_scalar *out) {
::fftwf_execute_dft(p,in,out);
}
inline static void fftw_destroy_plan(const FFTW_plan p) {
::fftwf_destroy_plan(p);
}
};
#endif
#ifndef FFTW_FORWARD
#define FFTW_FORWARD (-1)
#define FFTW_BACKWARD (+1)
#endif
class FFT {
private:
GridCartesian *vgrid;
GridCartesian *sgrid;
int Nd;
double flops;
double flops_call;
uint64_t usec;
Coordinate dimensions;
Coordinate processors;
Coordinate processor_coor;
public:
static const int forward=FFTW_FORWARD;
static const int backward=FFTW_BACKWARD;
double Flops(void) {return flops;}
double MFlops(void) {return flops/usec;}
double USec(void) {return (double)usec;}
FFT ( GridCartesian * grid ) :
vgrid(grid),
Nd(grid->_ndimension),
dimensions(grid->_fdimensions),
processors(grid->_processors),
processor_coor(grid->_processor_coor)
{
flops=0;
usec =0;
Coordinate layout(Nd,1);
sgrid = new GridCartesian(dimensions,layout,processors,*grid);
};
~FFT ( void) {
delete sgrid;
}
template<class vobj>
void FFT_dim_mask(Lattice<vobj> &result,const Lattice<vobj> &source,Coordinate mask,int sign){
conformable(result.Grid(),vgrid);
conformable(source.Grid(),vgrid);
Lattice<vobj> tmp(vgrid);
tmp = source;
for(int d=0;d<Nd;d++){
if( mask[d] ) {
FFT_dim(result,tmp,d,sign);
tmp=result;
}
}
}
template<class vobj>
void FFT_all_dim(Lattice<vobj> &result,const Lattice<vobj> &source,int sign){
Coordinate mask(Nd,1);
FFT_dim_mask(result,source,mask,sign);
}
template<class vobj>
void FFT_dim(Lattice<vobj> &result,const Lattice<vobj> &source,int dim, int sign){
#ifndef HAVE_FFTW
assert(0);
#else
conformable(result.Grid(),vgrid);
conformable(source.Grid(),vgrid);
int L = vgrid->_ldimensions[dim];
int G = vgrid->_fdimensions[dim];
Coordinate layout(Nd,1);
Coordinate pencil_gd(vgrid->_fdimensions);
pencil_gd[dim] = G*processors[dim];
// Pencil global vol LxLxGxLxL per node
GridCartesian pencil_g(pencil_gd,layout,processors,*vgrid);
// Construct pencils
typedef typename vobj::scalar_object sobj;
typedef typename sobj::scalar_type scalar;
Lattice<sobj> pgbuf(&pencil_g);
autoView(pgbuf_v , pgbuf, CpuWrite);
typedef typename FFTW<scalar>::FFTW_scalar FFTW_scalar;
typedef typename FFTW<scalar>::FFTW_plan FFTW_plan;
int Ncomp = sizeof(sobj)/sizeof(scalar);
int Nlow = 1;
for(int d=0;d<dim;d++){
Nlow*=vgrid->_ldimensions[d];
}
int rank = 1; /* 1d transforms */
int n[] = {G}; /* 1d transforms of length G */
int howmany = Ncomp;
int odist,idist,istride,ostride;
idist = odist = 1; /* Distance between consecutive FT's */
istride = ostride = Ncomp*Nlow; /* distance between two elements in the same FT */
int *inembed = n, *onembed = n;
scalar div;
if ( sign == backward ) div = 1.0/G;
else if ( sign == forward ) div = 1.0;
else assert(0);
FFTW_plan p;
{
FFTW_scalar *in = (FFTW_scalar *)&pgbuf_v[0];
FFTW_scalar *out= (FFTW_scalar *)&pgbuf_v[0];
p = FFTW<scalar>::fftw_plan_many_dft(rank,n,howmany,
in,inembed,
istride,idist,
out,onembed,
ostride, odist,
sign,FFTW_ESTIMATE);
}
// Barrel shift and collect global pencil
Coordinate lcoor(Nd), gcoor(Nd);
result = source;
int pc = processor_coor[dim];
for(int p=0;p<processors[dim];p++) {
{
autoView(r_v,result,CpuRead);
autoView(p_v,pgbuf,CpuWrite);
thread_for(idx, sgrid->lSites(),{
Coordinate cbuf(Nd);
sobj s;
sgrid->LocalIndexToLocalCoor(idx,cbuf);
peekLocalSite(s,r_v,cbuf);
cbuf[dim]+=((pc+p) % processors[dim])*L;
pokeLocalSite(s,p_v,cbuf);
});
}
if (p != processors[dim] - 1) {
result = Cshift(result,dim,L);
}
}
// Loop over orthog coords
int NN=pencil_g.lSites();
GridStopWatch timer;
timer.Start();
thread_for( idx,NN,{
Coordinate cbuf(Nd);
pencil_g.LocalIndexToLocalCoor(idx, cbuf);
if ( cbuf[dim] == 0 ) { // restricts loop to plane at lcoor[dim]==0
FFTW_scalar *in = (FFTW_scalar *)&pgbuf_v[idx];
FFTW_scalar *out= (FFTW_scalar *)&pgbuf_v[idx];
FFTW<scalar>::fftw_execute_dft(p,in,out);
}
});
timer.Stop();
// performance counting
double add,mul,fma;
FFTW<scalar>::fftw_flops(p,&add,&mul,&fma);
flops_call = add+mul+2.0*fma;
usec += timer.useconds();
flops+= flops_call*NN;
// writing out result
{
autoView(pgbuf_v,pgbuf,CpuRead);
autoView(result_v,result,CpuWrite);
thread_for(idx,sgrid->lSites(),{
Coordinate clbuf(Nd), cgbuf(Nd);
sobj s;
sgrid->LocalIndexToLocalCoor(idx,clbuf);
cgbuf = clbuf;
cgbuf[dim] = clbuf[dim]+L*pc;
peekLocalSite(s,pgbuf_v,cgbuf);
pokeLocalSite(s,result_v,clbuf);
});
}
result = result*div;
// destroying plan
FFTW<scalar>::fftw_destroy_plan(p);
#endif
}
};
NAMESPACE_END(Grid);
#endif
-711
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@@ -1,711 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/LinearOperator.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
/////////////////////////////////////////////////////////////////////////////////////////////
// LinearOperators Take a something and return a something.
/////////////////////////////////////////////////////////////////////////////////////////////
//
// Hopefully linearity is satisfied and the AdjOp is indeed the Hermitian Conjugateugate (transpose if real):
//SBase
// i) F(a x + b y) = aF(x) + b F(y).
// ii) <x|Op|y> = <y|AdjOp|x>^\ast
//
// Would be fun to have a test linearity & Herm Conj function!
/////////////////////////////////////////////////////////////////////////////////////////////
template<class Field> class LinearOperatorBase {
public:
// Support for coarsening to a multigrid
virtual void OpDiag (const Field &in, Field &out) = 0; // Abstract base
virtual void OpDir (const Field &in, Field &out,int dir,int disp) = 0; // Abstract base
virtual void OpDirAll (const Field &in, std::vector<Field> &out) = 0; // Abstract base
virtual void Op (const Field &in, Field &out) = 0; // Abstract base
virtual void AdjOp (const Field &in, Field &out) = 0; // Abstract base
virtual void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2)=0;
virtual void HermOp(const Field &in, Field &out)=0;
virtual ~LinearOperatorBase(){};
};
/////////////////////////////////////////////////////////////////////////////////////////////
// By sharing the class for Sparse Matrix across multiple operator wrappers, we can share code
// between RB and non-RB variants. Sparse matrix is like the fermion action def, and then
// the wrappers implement the specialisation of "Op" and "AdjOp" to the cases minimising
// replication of code.
//
// I'm not entirely happy with implementation; to share the Schur code between herm and non-herm
// while still having a "OpAndNorm" in the abstract base I had to implement it in both cases
// with an assert trap in the non-herm. This isn't right; there must be a better C++ way to
// do it, but I fear it required multiple inheritance and mixed in abstract base classes
/////////////////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////
// Construct herm op from non-herm matrix
////////////////////////////////////////////////////////////////////
template<class Matrix,class Field>
class MdagMLinearOperator : public LinearOperatorBase<Field> {
Matrix &_Mat;
public:
MdagMLinearOperator(Matrix &Mat): _Mat(Mat){};
// Support for coarsening to a multigrid
void OpDiag (const Field &in, Field &out) {
_Mat.Mdiag(in,out);
}
void OpDir (const Field &in, Field &out,int dir,int disp) {
_Mat.Mdir(in,out,dir,disp);
}
void OpDirAll (const Field &in, std::vector<Field> &out){
_Mat.MdirAll(in,out);
};
void Op (const Field &in, Field &out){
_Mat.M(in,out);
}
void AdjOp (const Field &in, Field &out){
_Mat.Mdag(in,out);
}
void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
_Mat.MdagM(in,out);
ComplexD dot = innerProduct(in,out);
n1=real(dot);
n2=norm2(out);
}
void HermOp(const Field &in, Field &out){
_Mat.MdagM(in,out);
}
};
template<class Matrix,class Field>
class MMdagLinearOperator : public LinearOperatorBase<Field> {
Matrix &_Mat;
public:
MMdagLinearOperator(Matrix &Mat): _Mat(Mat){};
// Support for coarsening to a multigrid
void OpDiag (const Field &in, Field &out) {
_Mat.Mdiag(in,out);
}
void OpDir (const Field &in, Field &out,int dir,int disp) {
_Mat.Mdir(in,out,dir,disp);
}
void OpDirAll (const Field &in, std::vector<Field> &out){
_Mat.MdirAll(in,out);
};
void Op (const Field &in, Field &out){
_Mat.M(in,out);
}
void AdjOp (const Field &in, Field &out){
_Mat.Mdag(in,out);
}
void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
_Mat.MMdag(in,out);
ComplexD dot = innerProduct(in,out);
n1=real(dot);
n2=norm2(out);
}
void HermOp(const Field &in, Field &out){
_Mat.MMdag(in,out);
}
};
////////////////////////////////////////////////////////////////////
// Construct herm op and shift it for mgrid smoother
////////////////////////////////////////////////////////////////////
template<class Matrix,class Field>
class ShiftedMdagMLinearOperator : public LinearOperatorBase<Field> {
Matrix &_Mat;
RealD _shift;
public:
ShiftedMdagMLinearOperator(Matrix &Mat,RealD shift): _Mat(Mat), _shift(shift){};
// Support for coarsening to a multigrid
void OpDiag (const Field &in, Field &out) {
_Mat.Mdiag(in,out);
assert(0);
}
void OpDir (const Field &in, Field &out,int dir,int disp) {
_Mat.Mdir(in,out,dir,disp);
assert(0);
}
void OpDirAll (const Field &in, std::vector<Field> &out){
assert(0);
};
void Op (const Field &in, Field &out){
_Mat.M(in,out);
assert(0);
}
void AdjOp (const Field &in, Field &out){
_Mat.Mdag(in,out);
assert(0);
}
void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
HermOp(in,out);
ComplexD dot = innerProduct(in,out);
n1=real(dot);
n2=norm2(out);
}
void HermOp(const Field &in, Field &out){
_Mat.MdagM(in,out);
out = out + _shift*in;
}
};
////////////////////////////////////////////////////////////////////
// Create a shifted HermOp
////////////////////////////////////////////////////////////////////
template<class Field>
class ShiftedHermOpLinearOperator : public LinearOperatorBase<Field> {
LinearOperatorBase<Field> &_Mat;
RealD _shift;
public:
ShiftedHermOpLinearOperator(LinearOperatorBase<Field> &Mat,RealD shift): _Mat(Mat), _shift(shift){};
// Support for coarsening to a multigrid
void OpDiag (const Field &in, Field &out) {
assert(0);
}
void OpDir (const Field &in, Field &out,int dir,int disp) {
assert(0);
}
void OpDirAll (const Field &in, std::vector<Field> &out){
assert(0);
};
void Op (const Field &in, Field &out){
HermOp(in,out);
}
void AdjOp (const Field &in, Field &out){
HermOp(in,out);
}
void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
HermOp(in,out);
ComplexD dot = innerProduct(in,out);
n1=real(dot);
n2=norm2(out);
}
void HermOp(const Field &in, Field &out){
_Mat.HermOp(in,out);
out = out + _shift*in;
}
};
////////////////////////////////////////////////////////////////////
// Wrap an already herm matrix
////////////////////////////////////////////////////////////////////
template<class Matrix,class Field>
class HermitianLinearOperator : public LinearOperatorBase<Field> {
Matrix &_Mat;
public:
HermitianLinearOperator(Matrix &Mat): _Mat(Mat){};
// Support for coarsening to a multigrid
void OpDiag (const Field &in, Field &out) {
_Mat.Mdiag(in,out);
}
void OpDir (const Field &in, Field &out,int dir,int disp) {
_Mat.Mdir(in,out,dir,disp);
}
void OpDirAll (const Field &in, std::vector<Field> &out){
_Mat.MdirAll(in,out);
};
void Op (const Field &in, Field &out){
_Mat.M(in,out);
}
void AdjOp (const Field &in, Field &out){
_Mat.M(in,out);
}
void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
HermOp(in,out);
ComplexD dot= innerProduct(in,out); n1=real(dot);
n2=norm2(out);
}
void HermOp(const Field &in, Field &out){
_Mat.M(in,out);
}
};
template<class Matrix,class Field>
class NonHermitianLinearOperator : public LinearOperatorBase<Field> {
Matrix &_Mat;
public:
NonHermitianLinearOperator(Matrix &Mat): _Mat(Mat){};
// Support for coarsening to a multigrid
void OpDiag (const Field &in, Field &out) {
_Mat.Mdiag(in,out);
}
void OpDir (const Field &in, Field &out,int dir,int disp) {
_Mat.Mdir(in,out,dir,disp);
}
void OpDirAll (const Field &in, std::vector<Field> &out){
_Mat.MdirAll(in,out);
};
void Op (const Field &in, Field &out){
_Mat.M(in,out);
}
void AdjOp (const Field &in, Field &out){
_Mat.Mdag(in,out);
}
void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
assert(0);
}
void HermOp(const Field &in, Field &out){
assert(0);
}
};
//////////////////////////////////////////////////////////
// Even Odd Schur decomp operators; there are several
// ways to introduce the even odd checkerboarding
//////////////////////////////////////////////////////////
template<class Field>
class SchurOperatorBase : public LinearOperatorBase<Field> {
public:
virtual void Mpc (const Field &in, Field &out) =0;
virtual void MpcDag (const Field &in, Field &out) =0;
virtual void MpcDagMpc(const Field &in, Field &out) {
Field tmp(in.Grid());
tmp.Checkerboard() = in.Checkerboard();
Mpc(in,tmp);
MpcDag(tmp,out);
}
virtual void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
out.Checkerboard() = in.Checkerboard();
MpcDagMpc(in,out);
ComplexD dot= innerProduct(in,out);
n1=real(dot);
n2=norm2(out);
}
virtual void HermOp(const Field &in, Field &out){
out.Checkerboard() = in.Checkerboard();
MpcDagMpc(in,out);
}
void Op (const Field &in, Field &out){
Mpc(in,out);
}
void AdjOp (const Field &in, Field &out){
MpcDag(in,out);
}
// Support for coarsening to a multigrid
void OpDiag (const Field &in, Field &out) {
assert(0); // must coarsen the unpreconditioned system
}
void OpDir (const Field &in, Field &out,int dir,int disp) {
assert(0);
}
void OpDirAll (const Field &in, std::vector<Field> &out){
assert(0);
};
};
template<class Matrix,class Field>
class SchurDiagMooeeOperator : public SchurOperatorBase<Field> {
public:
Matrix &_Mat;
SchurDiagMooeeOperator (Matrix &Mat): _Mat(Mat){};
virtual void Mpc (const Field &in, Field &out) {
Field tmp(in.Grid());
tmp.Checkerboard() = !in.Checkerboard();
_Mat.Meooe(in,tmp);
_Mat.MooeeInv(tmp,out);
_Mat.Meooe(out,tmp);
_Mat.Mooee(in,out);
axpy(out,-1.0,tmp,out);
}
virtual void MpcDag (const Field &in, Field &out){
Field tmp(in.Grid());
_Mat.MeooeDag(in,tmp);
_Mat.MooeeInvDag(tmp,out);
_Mat.MeooeDag(out,tmp);
_Mat.MooeeDag(in,out);
axpy(out,-1.0,tmp,out);
}
};
template<class Matrix,class Field>
class SchurDiagOneOperator : public SchurOperatorBase<Field> {
protected:
Matrix &_Mat;
public:
SchurDiagOneOperator (Matrix &Mat): _Mat(Mat){};
virtual void Mpc (const Field &in, Field &out) {
Field tmp(in.Grid());
_Mat.Meooe(in,out);
_Mat.MooeeInv(out,tmp);
_Mat.Meooe(tmp,out);
_Mat.MooeeInv(out,tmp);
axpy(out,-1.0,tmp,in);
}
virtual void MpcDag (const Field &in, Field &out){
Field tmp(in.Grid());
_Mat.MooeeInvDag(in,out);
_Mat.MeooeDag(out,tmp);
_Mat.MooeeInvDag(tmp,out);
_Mat.MeooeDag(out,tmp);
axpy(out,-1.0,tmp,in);
}
};
template<class Matrix,class Field>
class SchurDiagTwoOperator : public SchurOperatorBase<Field> {
protected:
Matrix &_Mat;
public:
SchurDiagTwoOperator (Matrix &Mat): _Mat(Mat){};
virtual void Mpc (const Field &in, Field &out) {
Field tmp(in.Grid());
_Mat.MooeeInv(in,out);
_Mat.Meooe(out,tmp);
_Mat.MooeeInv(tmp,out);
_Mat.Meooe(out,tmp);
axpy(out,-1.0,tmp,in);
}
virtual void MpcDag (const Field &in, Field &out){
Field tmp(in.Grid());
_Mat.MeooeDag(in,out);
_Mat.MooeeInvDag(out,tmp);
_Mat.MeooeDag(tmp,out);
_Mat.MooeeInvDag(out,tmp);
axpy(out,-1.0,tmp,in);
}
};
template<class Field>
class NonHermitianSchurOperatorBase : public LinearOperatorBase<Field>
{
public:
virtual void Mpc (const Field& in, Field& out) = 0;
virtual void MpcDag (const Field& in, Field& out) = 0;
virtual void MpcDagMpc(const Field& in, Field& out) {
Field tmp(in.Grid());
tmp.Checkerboard() = in.Checkerboard();
Mpc(in,tmp);
MpcDag(tmp,out);
}
virtual void HermOpAndNorm(const Field& in, Field& out, RealD& n1, RealD& n2) {
assert(0);
}
virtual void HermOp(const Field& in, Field& out) {
assert(0);
}
void Op(const Field& in, Field& out) {
Mpc(in, out);
}
void AdjOp(const Field& in, Field& out) {
MpcDag(in, out);
}
// Support for coarsening to a multigrid
void OpDiag(const Field& in, Field& out) {
assert(0); // must coarsen the unpreconditioned system
}
void OpDir(const Field& in, Field& out, int dir, int disp) {
assert(0);
}
void OpDirAll(const Field& in, std::vector<Field>& out){
assert(0);
};
};
template<class Matrix, class Field>
class NonHermitianSchurDiagMooeeOperator : public NonHermitianSchurOperatorBase<Field>
{
public:
Matrix& _Mat;
NonHermitianSchurDiagMooeeOperator(Matrix& Mat): _Mat(Mat){};
virtual void Mpc(const Field& in, Field& out) {
Field tmp(in.Grid());
tmp.Checkerboard() = !in.Checkerboard();
_Mat.Meooe(in, tmp);
_Mat.MooeeInv(tmp, out);
_Mat.Meooe(out, tmp);
_Mat.Mooee(in, out);
axpy(out, -1.0, tmp, out);
}
virtual void MpcDag(const Field& in, Field& out) {
Field tmp(in.Grid());
_Mat.MeooeDag(in, tmp);
_Mat.MooeeInvDag(tmp, out);
_Mat.MeooeDag(out, tmp);
_Mat.MooeeDag(in, out);
axpy(out, -1.0, tmp, out);
}
};
template<class Matrix,class Field>
class NonHermitianSchurDiagOneOperator : public NonHermitianSchurOperatorBase<Field>
{
protected:
Matrix &_Mat;
public:
NonHermitianSchurDiagOneOperator (Matrix& Mat): _Mat(Mat){};
virtual void Mpc(const Field& in, Field& out) {
Field tmp(in.Grid());
_Mat.Meooe(in, out);
_Mat.MooeeInv(out, tmp);
_Mat.Meooe(tmp, out);
_Mat.MooeeInv(out, tmp);
axpy(out, -1.0, tmp, in);
}
virtual void MpcDag(const Field& in, Field& out) {
Field tmp(in.Grid());
_Mat.MooeeInvDag(in, out);
_Mat.MeooeDag(out, tmp);
_Mat.MooeeInvDag(tmp, out);
_Mat.MeooeDag(out, tmp);
axpy(out, -1.0, tmp, in);
}
};
template<class Matrix, class Field>
class NonHermitianSchurDiagTwoOperator : public NonHermitianSchurOperatorBase<Field>
{
protected:
Matrix& _Mat;
public:
NonHermitianSchurDiagTwoOperator(Matrix& Mat): _Mat(Mat){};
virtual void Mpc(const Field& in, Field& out) {
Field tmp(in.Grid());
_Mat.MooeeInv(in, out);
_Mat.Meooe(out, tmp);
_Mat.MooeeInv(tmp, out);
_Mat.Meooe(out, tmp);
axpy(out, -1.0, tmp, in);
}
virtual void MpcDag(const Field& in, Field& out) {
Field tmp(in.Grid());
_Mat.MeooeDag(in, out);
_Mat.MooeeInvDag(out, tmp);
_Mat.MeooeDag(tmp, out);
_Mat.MooeeInvDag(out, tmp);
axpy(out, -1.0, tmp, in);
}
};
///////////////////////////////////////////////////////////////////////////////////////////////////
// Left handed Moo^-1 ; (Moo - Moe Mee^-1 Meo) psi = eta --> ( 1 - Moo^-1 Moe Mee^-1 Meo ) psi = Moo^-1 eta
// Right handed Moo^-1 ; (Moo - Moe Mee^-1 Meo) Moo^-1 Moo psi = eta --> ( 1 - Moe Mee^-1 Meo Moo^-1) phi=eta ; psi = Moo^-1 phi
///////////////////////////////////////////////////////////////////////////////////////////////////
template<class Matrix,class Field> using SchurDiagOneRH = SchurDiagTwoOperator<Matrix,Field> ;
template<class Matrix,class Field> using SchurDiagOneLH = SchurDiagOneOperator<Matrix,Field> ;
///////////////////////////////////////////////////////////////////////////////////////////////////
// Staggered use
///////////////////////////////////////////////////////////////////////////////////////////////////
template<class Matrix,class Field>
class SchurStaggeredOperator : public SchurOperatorBase<Field> {
protected:
Matrix &_Mat;
Field tmp;
RealD mass;
public:
SchurStaggeredOperator (Matrix &Mat): _Mat(Mat), tmp(_Mat.RedBlackGrid())
{
assert( _Mat.isTrivialEE() );
mass = _Mat.Mass();
}
virtual void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
Mpc(in,out);
ComplexD dot= innerProduct(in,out);
n1 = real(dot);
n2 =0.0;
}
virtual void HermOp(const Field &in, Field &out){
Mpc(in,out);
// _Mat.Meooe(in,out);
// _Mat.Meooe(out,tmp);
// axpby(out,-1.0,mass*mass,tmp,in);
}
virtual void Mpc (const Field &in, Field &out)
{
Field tmp(in.Grid());
Field tmp2(in.Grid());
// _Mat.Mooee(in,out);
// _Mat.Mooee(out,tmp);
_Mat.Meooe(in,out);
_Mat.Meooe(out,tmp);
axpby(out,-1.0,mass*mass,tmp,in);
}
virtual void MpcDag (const Field &in, Field &out){
Mpc(in,out);
}
virtual void MpcDagMpc(const Field &in, Field &out) {
assert(0);// Never need with staggered
}
};
template<class Matrix,class Field> using SchurStagOperator = SchurStaggeredOperator<Matrix,Field>;
/////////////////////////////////////////////////////////////
// Base classes for functions of operators
/////////////////////////////////////////////////////////////
template<class Field> class OperatorFunction {
public:
virtual void operator() (LinearOperatorBase<Field> &Linop, const Field &in, Field &out) = 0;
virtual void operator() (LinearOperatorBase<Field> &Linop, const std::vector<Field> &in,std::vector<Field> &out) {
assert(in.size()==out.size());
for(int k=0;k<in.size();k++){
(*this)(Linop,in[k],out[k]);
}
};
virtual ~OperatorFunction(){};
};
template<class Field> class LinearFunction {
public:
virtual void operator() (const Field &in, Field &out) = 0;
virtual void operator() (const std::vector<Field> &in, std::vector<Field> &out)
{
assert(in.size() == out.size());
for (unsigned int i = 0; i < in.size(); ++i)
{
(*this)(in[i], out[i]);
}
}
virtual ~LinearFunction(){};
};
template<class Field> class IdentityLinearFunction : public LinearFunction<Field> {
public:
void operator() (const Field &in, Field &out){
out = in;
};
};
/////////////////////////////////////////////////////////////
// Base classes for Multishift solvers for operators
/////////////////////////////////////////////////////////////
template<class Field> class OperatorMultiFunction {
public:
virtual void operator() (LinearOperatorBase<Field> &Linop, const Field &in, std::vector<Field> &out) = 0;
};
// FIXME : To think about
// Chroma functionality list defining LinearOperator
/*
virtual void operator() (T& chi, const T& psi, enum PlusMinus isign) const = 0;
virtual void operator() (T& chi, const T& psi, enum PlusMinus isign, Real epsilon) const
virtual const Subset& subset() const = 0;
virtual unsigned long nFlops() const { return 0; }
virtual void deriv(P& ds_u, const T& chi, const T& psi, enum PlusMinus isign) const
class UnprecLinearOperator : public DiffLinearOperator<T,P,Q>
const Subset& subset() const {return all;}
};
*/
////////////////////////////////////////////////////////////////////////////////////////////
// Hermitian operator Linear function and operator function
////////////////////////////////////////////////////////////////////////////////////////////
template<class Field>
class HermOpOperatorFunction : public OperatorFunction<Field> {
void operator() (LinearOperatorBase<Field> &Linop, const Field &in, Field &out) {
Linop.HermOp(in,out);
};
};
template<typename Field>
class PlainHermOp : public LinearFunction<Field> {
public:
using LinearFunction<Field>::operator();
LinearOperatorBase<Field> &_Linop;
PlainHermOp(LinearOperatorBase<Field>& linop) : _Linop(linop)
{}
void operator()(const Field& in, Field& out) {
_Linop.HermOp(in,out);
}
};
template<typename Field>
class FunctionHermOp : public LinearFunction<Field> {
public:
using LinearFunction<Field>::operator();
OperatorFunction<Field> & _poly;
LinearOperatorBase<Field> &_Linop;
FunctionHermOp(OperatorFunction<Field> & poly,LinearOperatorBase<Field>& linop)
: _poly(poly), _Linop(linop) {};
void operator()(const Field& in, Field& out) {
_poly(_Linop,in,out);
}
};
template<class Field>
class Polynomial : public OperatorFunction<Field> {
private:
std::vector<RealD> Coeffs;
public:
using OperatorFunction<Field>::operator();
Polynomial(std::vector<RealD> &_Coeffs) : Coeffs(_Coeffs) { };
// Implement the required interface
void operator() (LinearOperatorBase<Field> &Linop, const Field &in, Field &out) {
Field AtoN(in.Grid());
Field Mtmp(in.Grid());
AtoN = in;
out = AtoN*Coeffs[0];
for(int n=1;n<Coeffs.size();n++){
Mtmp = AtoN;
Linop.HermOp(Mtmp,AtoN);
out=out+AtoN*Coeffs[n];
}
};
};
NAMESPACE_END(Grid);
-52
View File
@@ -1,52 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/Preconditioner.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_PRECONDITIONER_H
#define GRID_PRECONDITIONER_H
NAMESPACE_BEGIN(Grid);
template<class Field> using Preconditioner = LinearFunction<Field> ;
/*
template<class Field> class Preconditioner : public LinearFunction<Field> {
using LinearFunction<Field>::operator();
virtual void operator()(const Field &src, Field & psi)=0;
};
*/
template<class Field> class TrivialPrecon : public Preconditioner<Field> {
public:
using Preconditioner<Field>::operator();
virtual void operator()(const Field &src, Field & psi){
psi = src;
}
TrivialPrecon(void){};
};
NAMESPACE_END(Grid);
#endif
-86
View File
@@ -1,86 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/SparseMatrix.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_ALGORITHM_SPARSE_MATRIX_H
#define GRID_ALGORITHM_SPARSE_MATRIX_H
NAMESPACE_BEGIN(Grid);
/////////////////////////////////////////////////////////////////////////////////////////////
// Interface defining what I expect of a general sparse matrix, such as a Fermion action
/////////////////////////////////////////////////////////////////////////////////////////////
template<class Field> class SparseMatrixBase {
public:
virtual GridBase *Grid(void) =0;
// Full checkerboar operations
virtual void M (const Field &in, Field &out)=0;
virtual void Mdag (const Field &in, Field &out)=0;
virtual void MdagM(const Field &in, Field &out) {
Field tmp (in.Grid());
M(in,tmp);
Mdag(tmp,out);
}
virtual void MMdag(const Field &in, Field &out) {
Field tmp (in.Grid());
Mdag(in,tmp);
M(tmp,out);
}
virtual void Mdiag (const Field &in, Field &out)=0;
virtual void Mdir (const Field &in, Field &out,int dir, int disp)=0;
virtual void MdirAll (const Field &in, std::vector<Field> &out)=0;
virtual ~SparseMatrixBase() {};
};
/////////////////////////////////////////////////////////////////////////////////////////////
// Interface augmented by a red black sparse matrix, such as a Fermion action
/////////////////////////////////////////////////////////////////////////////////////////////
template<class Field> class CheckerBoardedSparseMatrixBase : public SparseMatrixBase<Field> {
public:
virtual GridBase *RedBlackGrid(void)=0;
//////////////////////////////////////////////////////////////////////
// Query the even even properties to make algorithmic decisions
//////////////////////////////////////////////////////////////////////
virtual RealD Mass(void) { return 0.0; };
virtual int ConstEE(void) { return 1; }; // Disable assumptions unless overridden
virtual int isTrivialEE(void) { return 0; }; // by a derived class that knows better
// half checkerboard operaions
virtual void Meooe (const Field &in, Field &out)=0;
virtual void Mooee (const Field &in, Field &out)=0;
virtual void MooeeInv (const Field &in, Field &out)=0;
virtual void MeooeDag (const Field &in, Field &out)=0;
virtual void MooeeDag (const Field &in, Field &out)=0;
virtual void MooeeInvDag (const Field &in, Field &out)=0;
virtual ~CheckerBoardedSparseMatrixBase() {};
};
NAMESPACE_END(Grid);
#endif
-414
View File
@@ -1,414 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/approx/Chebyshev.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: paboyle <paboyle@ph.ed.ac.uk>
Author: Christoph Lehner <clehner@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CHEBYSHEV_H
#define GRID_CHEBYSHEV_H
#include <Grid/algorithms/LinearOperator.h>
NAMESPACE_BEGIN(Grid);
struct ChebyParams : Serializable {
GRID_SERIALIZABLE_CLASS_MEMBERS(ChebyParams,
RealD, alpha,
RealD, beta,
int, Npoly);
};
////////////////////////////////////////////////////////////////////////////////////////////
// Generic Chebyshev approximations
////////////////////////////////////////////////////////////////////////////////////////////
template<class Field>
class Chebyshev : public OperatorFunction<Field> {
private:
using OperatorFunction<Field>::operator();
std::vector<RealD> Coeffs;
int order;
RealD hi;
RealD lo;
public:
void csv(std::ostream &out){
RealD diff = hi-lo;
RealD delta = diff*1.0e-9;
for (RealD x=lo; x<hi; x+=delta) {
delta*=1.02;
RealD f = approx(x);
out<< x<<" "<<f<<std::endl;
}
return;
}
// Convenience for plotting the approximation
void PlotApprox(std::ostream &out) {
out<<"Polynomial approx ["<<lo<<","<<hi<<"]"<<std::endl;
for(RealD x=lo;x<hi;x+=(hi-lo)/50.0){
out <<x<<"\t"<<approx(x)<<std::endl;
}
};
Chebyshev(){};
Chebyshev(ChebyParams p){ Init(p.alpha,p.beta,p.Npoly);};
Chebyshev(RealD _lo,RealD _hi,int _order, RealD (* func)(RealD) ) {Init(_lo,_hi,_order,func);};
Chebyshev(RealD _lo,RealD _hi,int _order) {Init(_lo,_hi,_order);};
////////////////////////////////////////////////////////////////////////////////////////////////////
// c.f. numerical recipes "chebft"/"chebev". This is sec 5.8 "Chebyshev approximation".
////////////////////////////////////////////////////////////////////////////////////////////////////
// CJ: the one we need for Lanczos
void Init(RealD _lo,RealD _hi,int _order)
{
lo=_lo;
hi=_hi;
order=_order;
if(order < 2) exit(-1);
Coeffs.resize(order,0.0);
Coeffs[order-1] = 1.0;
};
// PB - more efficient low pass drops high modes above the low as 1/x uses all Chebyshev's.
// Similar kick effect below the threshold as Lanczos filter approach
void InitLowPass(RealD _lo,RealD _hi,int _order)
{
lo=_lo;
hi=_hi;
order=_order;
if(order < 2) exit(-1);
Coeffs.resize(order);
for(int j=0;j<order;j++){
RealD k=(order-1.0);
RealD s=std::cos( j*M_PI*(k+0.5)/order );
Coeffs[j] = s * 2.0/order;
}
};
void Init(RealD _lo,RealD _hi,int _order, RealD (* func)(RealD))
{
lo=_lo;
hi=_hi;
order=_order;
if(order < 2) exit(-1);
Coeffs.resize(order);
for(int j=0;j<order;j++){
RealD s=0;
for(int k=0;k<order;k++){
RealD y=std::cos(M_PI*(k+0.5)/order);
RealD x=0.5*(y*(hi-lo)+(hi+lo));
RealD f=func(x);
s=s+f*std::cos( j*M_PI*(k+0.5)/order );
}
Coeffs[j] = s * 2.0/order;
}
};
template<class functor>
void Init(RealD _lo,RealD _hi,int _order, functor & func)
{
lo=_lo;
hi=_hi;
order=_order;
if(order < 2) exit(-1);
Coeffs.resize(order);
for(int j=0;j<order;j++){
RealD s=0;
for(int k=0;k<order;k++){
RealD y=std::cos(M_PI*(k+0.5)/order);
RealD x=0.5*(y*(hi-lo)+(hi+lo));
RealD f=func(x);
s=s+f*std::cos( j*M_PI*(k+0.5)/order );
}
Coeffs[j] = s * 2.0/order;
}
};
void JacksonSmooth(void){
RealD M=order;
RealD alpha = M_PI/(M+2);
RealD lmax = std::cos(alpha);
RealD sumUsq =0;
std::vector<RealD> U(M);
std::vector<RealD> a(M);
std::vector<RealD> g(M);
for(int n=0;n<=M;n++){
U[n] = std::sin((n+1)*std::acos(lmax))/std::sin(std::acos(lmax));
sumUsq += U[n]*U[n];
}
sumUsq = std::sqrt(sumUsq);
for(int i=1;i<=M;i++){
a[i] = U[i]/sumUsq;
}
g[0] = 1.0;
for(int m=1;m<=M;m++){
g[m] = 0;
for(int i=0;i<=M-m;i++){
g[m]+= a[i]*a[m+i];
}
}
for(int m=1;m<=M;m++){
Coeffs[m]*=g[m];
}
}
RealD approx(RealD x) // Convenience for plotting the approximation
{
RealD Tn;
RealD Tnm;
RealD Tnp;
RealD y=( x-0.5*(hi+lo))/(0.5*(hi-lo));
RealD T0=1;
RealD T1=y;
RealD sum;
sum = 0.5*Coeffs[0]*T0;
sum+= Coeffs[1]*T1;
Tn =T1;
Tnm=T0;
for(int i=2;i<order;i++){
Tnp=2*y*Tn-Tnm;
Tnm=Tn;
Tn =Tnp;
sum+= Tn*Coeffs[i];
}
return sum;
};
RealD approxD(RealD x)
{
RealD Un;
RealD Unm;
RealD Unp;
RealD y=( x-0.5*(hi+lo))/(0.5*(hi-lo));
RealD U0=1;
RealD U1=2*y;
RealD sum;
sum = Coeffs[1]*U0;
sum+= Coeffs[2]*U1*2.0;
Un =U1;
Unm=U0;
for(int i=2;i<order-1;i++){
Unp=2*y*Un-Unm;
Unm=Un;
Un =Unp;
sum+= Un*Coeffs[i+1]*(i+1.0);
}
return sum/(0.5*(hi-lo));
};
RealD approxInv(RealD z, RealD x0, int maxiter, RealD resid) {
RealD x = x0;
RealD eps;
int i;
for (i=0;i<maxiter;i++) {
eps = approx(x) - z;
if (fabs(eps / z) < resid)
return x;
x = x - eps / approxD(x);
}
return std::numeric_limits<double>::quiet_NaN();
}
// Implement the required interface
void operator() (LinearOperatorBase<Field> &Linop, const Field &in, Field &out) {
GridBase *grid=in.Grid();
int vol=grid->gSites();
typedef typename Field::vector_type vector_type;
Field T0(grid); T0 = in;
Field T1(grid);
Field T2(grid);
Field y(grid);
Field *Tnm = &T0;
Field *Tn = &T1;
Field *Tnp = &T2;
// Tn=T1 = (xscale M + mscale)in
RealD xscale = 2.0/(hi-lo);
RealD mscale = -(hi+lo)/(hi-lo);
Linop.HermOp(T0,y);
axpby(T1,xscale,mscale,y,in);
// sum = .5 c[0] T0 + c[1] T1
// out = ()*T0 + Coeffs[1]*T1;
axpby(out,0.5*Coeffs[0],Coeffs[1],T0,T1);
for(int n=2;n<order;n++){
Linop.HermOp(*Tn,y);
axpby(y,xscale,mscale,y,(*Tn));
axpby(*Tnp,2.0,-1.0,y,(*Tnm));
if ( Coeffs[n] != 0.0) {
axpy(out,Coeffs[n],*Tnp,out);
}
// Cycle pointers to avoid copies
Field *swizzle = Tnm;
Tnm =Tn;
Tn =Tnp;
Tnp =swizzle;
}
}
};
template<class Field>
class ChebyshevLanczos : public Chebyshev<Field> {
private:
std::vector<RealD> Coeffs;
int order;
RealD alpha;
RealD beta;
RealD mu;
public:
ChebyshevLanczos(RealD _alpha,RealD _beta,RealD _mu,int _order) :
alpha(_alpha),
beta(_beta),
mu(_mu)
{
order=_order;
Coeffs.resize(order);
for(int i=0;i<_order;i++){
Coeffs[i] = 0.0;
}
Coeffs[order-1]=1.0;
};
void csv(std::ostream &out){
for (RealD x=-1.2*alpha; x<1.2*alpha; x+=(2.0*alpha)/10000) {
RealD f = approx(x);
out<< x<<" "<<f<<std::endl;
}
return;
}
RealD approx(RealD xx) // Convenience for plotting the approximation
{
RealD Tn;
RealD Tnm;
RealD Tnp;
Real aa = alpha * alpha;
Real bb = beta * beta;
RealD x = ( 2.0 * (xx-mu)*(xx-mu) - (aa+bb) ) / (aa-bb);
RealD y= x;
RealD T0=1;
RealD T1=y;
RealD sum;
sum = 0.5*Coeffs[0]*T0;
sum+= Coeffs[1]*T1;
Tn =T1;
Tnm=T0;
for(int i=2;i<order;i++){
Tnp=2*y*Tn-Tnm;
Tnm=Tn;
Tn =Tnp;
sum+= Tn*Coeffs[i];
}
return sum;
};
// shift_Multiply in Rudy's code
void AminusMuSq(LinearOperatorBase<Field> &Linop, const Field &in, Field &out)
{
GridBase *grid=in.Grid();
Field tmp(grid);
RealD aa= alpha*alpha;
RealD bb= beta * beta;
Linop.HermOp(in,out);
out = out - mu*in;
Linop.HermOp(out,tmp);
tmp = tmp - mu * out;
out = (2.0/ (aa-bb) ) * tmp - ((aa+bb)/(aa-bb))*in;
};
// Implement the required interface
void operator() (LinearOperatorBase<Field> &Linop, const Field &in, Field &out) {
GridBase *grid=in.Grid();
int vol=grid->gSites();
Field T0(grid); T0 = in;
Field T1(grid);
Field T2(grid);
Field y(grid);
Field *Tnm = &T0;
Field *Tn = &T1;
Field *Tnp = &T2;
// Tn=T1 = (xscale M )*in
AminusMuSq(Linop,T0,T1);
// sum = .5 c[0] T0 + c[1] T1
out = (0.5*Coeffs[0])*T0 + Coeffs[1]*T1;
for(int n=2;n<order;n++){
AminusMuSq(Linop,*Tn,y);
*Tnp=2.0*y-(*Tnm);
out=out+Coeffs[n]* (*Tnp);
// Cycle pointers to avoid copies
Field *swizzle = Tnm;
Tnm =Tn;
Tn =Tnp;
Tnp =swizzle;
}
}
};
NAMESPACE_END(Grid);
#endif
-152
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@@ -1,152 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/approx/Forecast.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: paboyle <paboyle@ph.ed.ac.uk>
Author: David Murphy <dmurphy@phys.columbia.edu>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef INCLUDED_FORECAST_H
#define INCLUDED_FORECAST_H
NAMESPACE_BEGIN(Grid);
// Abstract base class.
// Takes a matrix (Mat), a source (phi), and a vector of Fields (chi)
// and returns a forecasted solution to the system D*psi = phi (psi).
template<class Matrix, class Field>
class Forecast
{
public:
virtual Field operator()(Matrix &Mat, const Field& phi, const std::vector<Field>& chi) = 0;
};
// Implementation of Brower et al.'s chronological inverter (arXiv:hep-lat/9509012),
// used to forecast solutions across poles of the EOFA heatbath.
//
// Modified from CPS (cps_pp/src/util/dirac_op/d_op_base/comsrc/minresext.C)
template<class Matrix, class Field>
class ChronoForecast : public Forecast<Matrix,Field>
{
public:
Field operator()(Matrix &Mat, const Field& phi, const std::vector<Field>& prev_solns)
{
int degree = prev_solns.size();
Field chi(phi); // forecasted solution
// Trivial cases
if(degree == 0){ chi = Zero(); return chi; }
else if(degree == 1){ return prev_solns[0]; }
// RealD dot;
ComplexD xp;
Field r(phi); // residual
Field Mv(phi);
std::vector<Field> v(prev_solns); // orthonormalized previous solutions
std::vector<Field> MdagMv(degree,phi);
// Array to hold the matrix elements
std::vector<std::vector<ComplexD>> G(degree, std::vector<ComplexD>(degree));
// Solution and source vectors
std::vector<ComplexD> a(degree);
std::vector<ComplexD> b(degree);
// Orthonormalize the vector basis
for(int i=0; i<degree; i++){
v[i] *= 1.0/std::sqrt(norm2(v[i]));
for(int j=i+1; j<degree; j++){ v[j] -= innerProduct(v[i],v[j]) * v[i]; }
}
// Perform sparse matrix multiplication and construct rhs
for(int i=0; i<degree; i++){
b[i] = innerProduct(v[i],phi);
Mat.M(v[i],Mv);
Mat.Mdag(Mv,MdagMv[i]);
G[i][i] = innerProduct(v[i],MdagMv[i]);
}
// Construct the matrix
for(int j=0; j<degree; j++){
for(int k=j+1; k<degree; k++){
G[j][k] = innerProduct(v[j],MdagMv[k]);
G[k][j] = conjugate(G[j][k]);
}}
// Gauss-Jordan elimination with partial pivoting
for(int i=0; i<degree; i++){
// Perform partial pivoting
int k = i;
for(int j=i+1; j<degree; j++){ if(abs(G[j][j]) > abs(G[k][k])){ k = j; } }
if(k != i){
xp = b[k];
b[k] = b[i];
b[i] = xp;
for(int j=0; j<degree; j++){
xp = G[k][j];
G[k][j] = G[i][j];
G[i][j] = xp;
}
}
// Convert matrix to upper triangular form
for(int j=i+1; j<degree; j++){
xp = G[j][i]/G[i][i];
b[j] -= xp * b[i];
for(int k=0; k<degree; k++){ G[j][k] -= xp*G[i][k]; }
}
}
// Use Gaussian elimination to solve equations and calculate initial guess
chi = Zero();
r = phi;
for(int i=degree-1; i>=0; i--){
a[i] = 0.0;
for(int j=i+1; j<degree; j++){ a[i] += G[i][j] * a[j]; }
a[i] = (b[i]-a[i])/G[i][i];
chi += a[i]*v[i];
r -= a[i]*MdagMv[i];
}
RealD true_r(0.0);
ComplexD tmp;
for(int i=0; i<degree; i++){
tmp = -b[i];
for(int j=0; j<degree; j++){ tmp += G[i][j]*a[j]; }
tmp = conjugate(tmp)*tmp;
true_r += std::sqrt(tmp.real());
}
RealD error = std::sqrt(norm2(r)/norm2(phi));
std::cout << GridLogMessage << "ChronoForecast: |res|/|src| = " << error << std::endl;
return chi;
};
};
NAMESPACE_END(Grid);
#endif
-129
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#ifndef GRID_JACOBIPOLYNOMIAL_H
#define GRID_JACOBIPOLYNOMIAL_H
#include <Grid/algorithms/LinearOperator.h>
NAMESPACE_BEGIN(Grid);
template<class Field>
class JacobiPolynomial : public OperatorFunction<Field> {
private:
using OperatorFunction<Field>::operator();
int order;
RealD hi;
RealD lo;
RealD alpha;
RealD beta;
public:
void csv(std::ostream &out){
csv(out,lo,hi);
}
void csv(std::ostream &out,RealD llo,RealD hhi){
RealD diff = hhi-llo;
RealD delta = diff*1.0e-5;
for (RealD x=llo-delta; x<=hhi; x+=delta) {
RealD f = approx(x);
out<< x<<" "<<f <<std::endl;
}
return;
}
JacobiPolynomial(){};
JacobiPolynomial(RealD _lo,RealD _hi,int _order,RealD _alpha, RealD _beta)
{
lo=_lo;
hi=_hi;
alpha=_alpha;
beta=_beta;
order=_order;
};
RealD approx(RealD x) // Convenience for plotting the approximation
{
RealD Tn;
RealD Tnm;
RealD Tnp;
RealD y=( x-0.5*(hi+lo))/(0.5*(hi-lo));
RealD T0=1.0;
RealD T1=(alpha-beta)*0.5+(alpha+beta+2.0)*0.5*y;
Tn =T1;
Tnm=T0;
for(int n=2;n<=order;n++){
RealD cnp = 2.0*n*(n+alpha+beta)*(2.0*n-2.0+alpha+beta);
RealD cny = (2.0*n-2.0+alpha+beta)*(2.0*n-1.0+alpha+beta)*(2.0*n+alpha+beta);
RealD cn1 = (2.0*n+alpha+beta-1.0)*(alpha*alpha-beta*beta);
RealD cnm = - 2.0*(n+alpha-1.0)*(n+beta-1.0)*(2.0*n+alpha+beta);
Tnp= ( cny * y *Tn + cn1 * Tn + cnm * Tnm )/ cnp;
Tnm=Tn;
Tn =Tnp;
}
return Tnp;
};
// Implement the required interface
void operator() (LinearOperatorBase<Field> &Linop, const Field &in, Field &out) {
GridBase *grid=in.Grid();
int vol=grid->gSites();
Field T0(grid);
Field T1(grid);
Field T2(grid);
Field y(grid);
Field *Tnm = &T0;
Field *Tn = &T1;
Field *Tnp = &T2;
// RealD T0=1.0;
T0=in;
// RealD y=( x-0.5*(hi+lo))/(0.5*(hi-lo));
// = x * 2/(hi-lo) - (hi+lo)/(hi-lo)
Linop.HermOp(T0,y);
RealD xscale = 2.0/(hi-lo);
RealD mscale = -(hi+lo)/(hi-lo);
Linop.HermOp(T0,y);
y=y*xscale+in*mscale;
// RealD T1=(alpha-beta)*0.5+(alpha+beta+2.0)*0.5*y;
RealD halfAmB = (alpha-beta)*0.5;
RealD halfApBp2= (alpha+beta+2.0)*0.5;
T1 = halfAmB * in + halfApBp2*y;
for(int n=2;n<=order;n++){
Linop.HermOp(*Tn,y);
y=xscale*y+mscale*(*Tn);
RealD cnp = 2.0*n*(n+alpha+beta)*(2.0*n-2.0+alpha+beta);
RealD cny = (2.0*n-2.0+alpha+beta)*(2.0*n-1.0+alpha+beta)*(2.0*n+alpha+beta);
RealD cn1 = (2.0*n+alpha+beta-1.0)*(alpha*alpha-beta*beta);
RealD cnm = - 2.0*(n+alpha-1.0)*(n+beta-1.0)*(2.0*n+alpha+beta);
// Tnp= ( cny * y *Tn + cn1 * Tn + cnm * Tnm )/ cnp;
cny=cny/cnp;
cn1=cn1/cnp;
cn1=cn1/cnp;
cnm=cnm/cnp;
*Tnp=cny*y + cn1 *(*Tn) + cnm * (*Tnm);
// Cycle pointers to avoid copies
Field *swizzle = Tnm;
Tnm =Tn;
Tn =Tnp;
Tnp =swizzle;
}
out=*Tnp;
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,57 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/approx/MultiShiftFunction.cc
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#include <Grid/GridCore.h>
NAMESPACE_BEGIN(Grid);
double MultiShiftFunction::approx(double x)
{
double a = norm;
for(int n=0;n<poles.size();n++){
a = a + residues[n]/(x+poles[n]);
}
return a;
}
void MultiShiftFunction::gnuplot(std::ostream &out)
{
out<<"f(x) = "<<norm<<"";
for(int n=0;n<poles.size();n++){
out<<"+("<<residues[n]<<"/(x+"<<poles[n]<<"))";
}
out<<";"<<std::endl;
}
void MultiShiftFunction::csv(std::ostream &out)
{
for (double x=lo; x<hi; x*=1.05) {
double f = approx(x);
double r = sqrt(x);
out<< x<<","<<r<<","<<f<<","<<r-f<<std::endl;
}
return;
}
NAMESPACE_END(Grid);
@@ -1,67 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/approx/MultiShiftFunction.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef MULTI_SHIFT_FUNCTION
#define MULTI_SHIFT_FUNCTION
NAMESPACE_BEGIN(Grid);
class MultiShiftFunction {
public:
int order;
std::vector<RealD> poles;
std::vector<RealD> residues;
std::vector<RealD> tolerances;
RealD norm;
RealD lo,hi;
MultiShiftFunction(int n,RealD _lo,RealD _hi): poles(n), residues(n), tolerances(n), lo(_lo), hi(_hi) {;};
RealD approx(RealD x);
void csv(std::ostream &out);
void gnuplot(std::ostream &out);
void Init(AlgRemez & remez,double tol,bool inverse)
{
order=remez.getDegree();
tolerances.resize(remez.getDegree(),tol);
poles.resize(remez.getDegree());
residues.resize(remez.getDegree());
remez.getBounds(lo,hi);
if ( inverse ) remez.getIPFE (&residues[0],&poles[0],&norm);
else remez.getPFE (&residues[0],&poles[0],&norm);
}
// Allow deferred initialisation
MultiShiftFunction(void){};
MultiShiftFunction(AlgRemez & remez,double tol,bool inverse)
{
Init(remez,tol,inverse);
}
};
NAMESPACE_END(Grid);
#endif
-80
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@@ -1,80 +0,0 @@
-----------------------------------------------------------------------------------
PAB. Took Mike Clark's AlgRemez from GitHub and (modified a little) include.
This is open source and license and readme and comments are preserved consistent
with the license. Mike, thankyou!
-----------------------------------------------------------------------------------
-----------------------------------------------------------------------------------
AlgRemez
The archive downloadable here contains an implementation of the Remez
algorithm which calculates optimal rational (and polynomial)
approximations to the nth root over a given spectral range. The Remez
algorithm, although in principle is extremely straightforward to
program, is quite difficult to get completely correct, e.g., the Maple
implementation of the algorithm does not always converge to the
correct answer.
To use this algorithm you need to install GMP, the GNU Multiple
Precision Library, and when configuring the install, you must include
the --enable-mpfr option (see the GMP manual for more details). You
also have to edit the Makefile for AlgRemez appropriately for your
system, namely to point corrrectly to the location of the GMP library.
The simple main program included with this archive invokes the
AlgRemez class to calculate an approximation given by command line
arguments. It is invoked by the following
./test y z n d lambda_low lambda_high precision,
where the function to be approximated is f(x) = x^(y/z), with degree
(n,d) over the spectral range [lambda_low, lambda_high], using
precision digits of precision in the arithmetic. So an example would
be
./test 1 2 5 5 0.0004 64 40
which corresponds to constructing a rational approximation to the
square root function, with degree (5,5) over the range [0.0004,64]
with 40 digits of precision used for the arithmetic. The parameters y
and z must be positive, the approximation to f(x) = x^(-y/z) is simply
the inverse of the approximation to f(x) = x^(y/z). After the
approximation has been constructed, the roots and poles of the
rational function are found, and then the partial fraction expansion
of both the rational function and it's inverse are found, the results
of which are output to a file called "approx.dat". In addition, the
error function of the approximation is output to "error.dat", where it
can be checked that the resultant approximation satisfies Chebychev's
criterion, namely all error maxima are equal in magnitude, and
adjacent maxima are oppostie in sign. There are some caveats here
however, the optimal polynomial approximation has complex roots, and
the root finding implemented here cannot (yet) handle complex roots.
In addition, the partial fraction expansion of rational approximations
is only found for the case n = d, i.e., the degree of numerator
polynomial equals that of the denominator polynomial. The convention
for the partial fraction expansion is that polar shifts are always
written added to x, not subtracted.
To do list
1. Include an exponential dampening factor in the function to be
approximated. This may sound trivial to implement, but for some
parameters, the algorithm seems to breakdown. Also, the roots in the
rational approximation sometimes become complex, which currently
breaks the stupidly simple root finding code.
2. Make the algorithm faster - it's too slow when running on qcdoc.
3. Add complex root finding.
4. Add more options for error minimisation - currently the code
minimises the relative error, should add options for absolute error,
and other norms.
There will be a forthcoming publication concerning the results
generated by this software, but in the meantime, if you use this
software, please cite it as
"M.A. Clark and A.D. Kennedy, https://github.com/mikeaclark/AlgRemez, 2005".
If you have any problems using the software, then please email scientist.mike@gmail.com.
-759
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@@ -1,759 +0,0 @@
/*
Mike Clark - 25th May 2005
alg_remez.C
AlgRemez is an implementation of the Remez algorithm, which in this
case is used for generating the optimal nth root rational
approximation.
Note this class requires the gnu multiprecision (GNU MP) library.
*/
#include<math.h>
#include<stdio.h>
#include<stdlib.h>
#include<string>
#include<iostream>
#include<iomanip>
#include<cassert>
#include<Grid/algorithms/approx/Remez.h>
// Constructor
AlgRemez::AlgRemez(double lower, double upper, long precision)
{
prec = precision;
bigfloat::setDefaultPrecision(prec);
apstrt = lower;
apend = upper;
apwidt = apend - apstrt;
std::cout<<"Approximation bounds are ["<<apstrt<<","<<apend<<"]\n";
std::cout<<"Precision of arithmetic is "<<precision<<std::endl;
alloc = 0;
n = 0;
d = 0;
foundRoots = 0;
// Only require the approximation spread to be less than 1 ulp
tolerance = 1e-15;
}
// Destructor
AlgRemez::~AlgRemez()
{
if (alloc) {
delete [] param;
delete [] roots;
delete [] poles;
delete [] xx;
delete [] mm;
delete [] a_power;
delete [] a;
}
}
// Free memory and reallocate as necessary
void AlgRemez::allocate(int num_degree, int den_degree)
{
// Arrays have previously been allocated, deallocate first, then allocate
if (alloc) {
delete [] param;
delete [] roots;
delete [] poles;
delete [] xx;
delete [] mm;
}
// Note use of new and delete in memory allocation - cannot run on qcdsp
param = new bigfloat[num_degree+den_degree+1];
roots = new bigfloat[num_degree];
poles = new bigfloat[den_degree];
xx = new bigfloat[num_degree+den_degree+3];
mm = new bigfloat[num_degree+den_degree+2];
if (!alloc) {
// The coefficients of the sum in the exponential
a = new bigfloat[SUM_MAX];
a_power = new int[SUM_MAX];
}
alloc = 1;
}
// Reset the bounds of the approximation
void AlgRemez::setBounds(double lower, double upper)
{
apstrt = lower;
apend = upper;
apwidt = apend - apstrt;
}
// Generate the rational approximation x^(pnum/pden)
double AlgRemez::generateApprox(int degree, unsigned long pnum,
unsigned long pden)
{
return generateApprox(degree, degree, pnum, pden);
}
double AlgRemez::generateApprox(int num_degree, int den_degree,
unsigned long pnum, unsigned long pden)
{
double *a_param = 0;
int *a_pow = 0;
return generateApprox(num_degree, den_degree, pnum, pden, 0, a_param, a_pow);
}
// Generate the rational approximation x^(pnum/pden)
double AlgRemez::generateApprox(int num_degree, int den_degree,
unsigned long pnum, unsigned long pden,
int a_len, double *a_param, int *a_pow)
{
std::cout<<"Degree of the approximation is ("<<num_degree<<","<<den_degree<<")\n";
std::cout<<"Approximating the function x^("<<pnum<<"/"<<pden<<")\n";
// Reallocate arrays, since degree has changed
if (num_degree != n || den_degree != d) allocate(num_degree,den_degree);
assert(a_len<=SUM_MAX);
step = new bigfloat[num_degree+den_degree+2];
a_length = a_len;
for (int j=0; j<a_len; j++) {
a[j]= a_param[j];
a_power[j] = a_pow[j];
}
power_num = pnum;
power_den = pden;
spread = 1.0e37;
iter = 0;
n = num_degree;
d = den_degree;
neq = n + d + 1;
initialGuess();
stpini(step);
while (spread > tolerance) { //iterate until convergance
if (iter++%100==0)
std::cout<<"Iteration " <<iter-1<<" spread "<<(double)spread<<" delta "<<(double)delta<<std::endl;
equations();
if (delta < tolerance) {
std::cout<<"Delta too small, try increasing precision\n";
assert(0);
};
assert( delta>= tolerance);
search(step);
}
int sign;
double error = (double)getErr(mm[0],&sign);
std::cout<<"Converged at "<<iter<<" iterations; error = "<<error<<std::endl;
// Once the approximation has been generated, calculate the roots
if(!root()) {
std::cout<<"Root finding failed\n";
} else {
foundRoots = 1;
}
delete [] step;
// Return the maximum error in the approximation
return error;
}
// Return the partial fraction expansion of the approximation x^(pnum/pden)
int AlgRemez::getPFE(double *Res, double *Pole, double *Norm) {
if (n!=d) {
std::cout<<"Cannot handle case: Numerator degree neq Denominator degree\n";
return 0;
}
if (!alloc) {
std::cout<<"Approximation not yet generated\n";
return 0;
}
if (!foundRoots) {
std::cout<<"Roots not found, so PFE cannot be taken\n";
return 0;
}
bigfloat *r = new bigfloat[n];
bigfloat *p = new bigfloat[d];
for (int i=0; i<n; i++) r[i] = roots[i];
for (int i=0; i<d; i++) p[i] = poles[i];
// Perform a partial fraction expansion
pfe(r, p, norm);
// Convert to double and return
*Norm = (double)norm;
for (int i=0; i<n; i++) Res[i] = (double)r[i];
for (int i=0; i<d; i++) Pole[i] = (double)p[i];
delete [] r;
delete [] p;
// Where the smallest shift is located
return 0;
}
// Return the partial fraction expansion of the approximation x^(-pnum/pden)
int AlgRemez::getIPFE(double *Res, double *Pole, double *Norm) {
if (n!=d) {
std::cout<<"Cannot handle case: Numerator degree neq Denominator degree\n";
return 0;
}
if (!alloc) {
std::cout<<"Approximation not yet generated\n";
return 0;
}
if (!foundRoots) {
std::cout<<"Roots not found, so PFE cannot be taken\n";
return 0;
}
bigfloat *r = new bigfloat[d];
bigfloat *p = new bigfloat[n];
// Want the inverse function
for (int i=0; i<n; i++) {
r[i] = poles[i];
p[i] = roots[i];
}
// Perform a partial fraction expansion
pfe(r, p, (bigfloat)1l/norm);
// Convert to double and return
*Norm = (double)((bigfloat)1l/(norm));
for (int i=0; i<n; i++) {
Res[i] = (double)r[i];
Pole[i] = (double)p[i];
}
delete [] r;
delete [] p;
// Where the smallest shift is located
return 0;
}
// Initial values of maximal and minimal errors
void AlgRemez::initialGuess() {
// Supply initial guesses for solution points
long ncheb = neq; // Degree of Chebyshev error estimate
bigfloat a, r;
// Find ncheb+1 extrema of Chebyshev polynomial
a = ncheb;
mm[0] = apstrt;
for (long i = 1; i < ncheb; i++) {
r = 0.5 * (1 - cos((M_PI * i)/(double) a));
//r *= sqrt_bf(r);
r = (exp((double)r)-1.0)/(exp(1.0)-1.0);
mm[i] = apstrt + r * apwidt;
}
mm[ncheb] = apend;
a = 2.0 * ncheb;
for (long i = 0; i <= ncheb; i++) {
r = 0.5 * (1 - cos(M_PI * (2*i+1)/(double) a));
//r *= sqrt_bf(r); // Squeeze to low end of interval
r = (exp((double)r)-1.0)/(exp(1.0)-1.0);
xx[i] = apstrt + r * apwidt;
}
}
// Initialise step sizes
void AlgRemez::stpini(bigfloat *step) {
xx[neq+1] = apend;
delta = 0.25;
step[0] = xx[0] - apstrt;
for (int i = 1; i < neq; i++) step[i] = xx[i] - xx[i-1];
step[neq] = step[neq-1];
}
// Search for error maxima and minima
void AlgRemez::search(bigfloat *step) {
bigfloat a, q, xm, ym, xn, yn, xx0, xx1;
int i, meq, emsign, ensign, steps;
meq = neq + 1;
bigfloat *yy = new bigfloat[meq];
bigfloat eclose = 1.0e30;
bigfloat farther = 0l;
xx0 = apstrt;
for (i = 0; i < meq; i++) {
steps = 0;
xx1 = xx[i]; // Next zero
if (i == meq-1) xx1 = apend;
xm = mm[i];
ym = getErr(xm,&emsign);
q = step[i];
xn = xm + q;
if (xn < xx0 || xn >= xx1) { // Cannot skip over adjacent boundaries
q = -q;
xn = xm;
yn = ym;
ensign = emsign;
} else {
yn = getErr(xn,&ensign);
if (yn < ym) {
q = -q;
xn = xm;
yn = ym;
ensign = emsign;
}
}
while(yn >= ym) { // March until error becomes smaller.
if (++steps > 10) break;
ym = yn;
xm = xn;
emsign = ensign;
a = xm + q;
if (a == xm || a <= xx0 || a >= xx1) break;// Must not skip over the zeros either side.
xn = a;
yn = getErr(xn,&ensign);
}
mm[i] = xm; // Position of maximum
yy[i] = ym; // Value of maximum
if (eclose > ym) eclose = ym;
if (farther < ym) farther = ym;
xx0 = xx1; // Walk to next zero.
} // end of search loop
q = (farther - eclose); // Decrease step size if error spread increased
if (eclose != 0.0) q /= eclose; // Relative error spread
if (q >= spread) delta *= 0.5; // Spread is increasing; decrease step size
spread = q;
for (i = 0; i < neq; i++) {
q = yy[i+1];
if (q != 0.0) q = yy[i] / q - (bigfloat)1l;
else q = 0.0625;
if (q > (bigfloat)0.25) q = 0.25;
q *= mm[i+1] - mm[i];
step[i] = q * delta;
}
step[neq] = step[neq-1];
for (i = 0; i < neq; i++) { // Insert new locations for the zeros.
xm = xx[i] - step[i];
if (xm <= apstrt) continue;
if (xm >= apend) continue;
if (xm <= mm[i]) xm = (bigfloat)0.5 * (mm[i] + xx[i]);
if (xm >= mm[i+1]) xm = (bigfloat)0.5 * (mm[i+1] + xx[i]);
xx[i] = xm;
}
delete [] yy;
}
// Solve the equations
void AlgRemez::equations(void) {
bigfloat x, y, z;
int i, j, ip;
bigfloat *aa;
bigfloat *AA = new bigfloat[(neq)*(neq)];
bigfloat *BB = new bigfloat[neq];
for (i = 0; i < neq; i++) { // set up the equations for solution by simq()
ip = neq * i; // offset to 1st element of this row of matrix
x = xx[i]; // the guess for this row
y = func(x); // right-hand-side vector
z = (bigfloat)1l;
aa = AA+ip;
for (j = 0; j <= n; j++) {
*aa++ = z;
z *= x;
}
z = (bigfloat)1l;
for (j = 0; j < d; j++) {
*aa++ = -y * z;
z *= x;
}
BB[i] = y * z; // Right hand side vector
}
// Solve the simultaneous linear equations.
if (simq(AA, BB, param, neq)) {
std::cout<<"simq failed\n";
exit(0);
}
delete [] AA;
delete [] BB;
}
// Evaluate the rational form P(x)/Q(x) using coefficients
// from the solution vector param
bigfloat AlgRemez::approx(const bigfloat x) {
bigfloat yn, yd;
int i;
// Work backwards toward the constant term.
yn = param[n]; // Highest order numerator coefficient
for (i = n-1; i >= 0; i--) yn = x * yn + param[i];
yd = x + param[n+d]; // Highest degree coefficient = 1.0
for (i = n+d-1; i > n; i--) yd = x * yd + param[i];
return(yn/yd);
}
// Compute size and sign of the approximation error at x
bigfloat AlgRemez::getErr(bigfloat x, int *sign) {
bigfloat e, f;
f = func(x);
e = approx(x) - f;
if (f != 0) e /= f;
if (e < (bigfloat)0.0) {
*sign = -1;
e = -e;
}
else *sign = 1;
return(e);
}
// Calculate function required for the approximation.
bigfloat AlgRemez::func(const bigfloat x) {
bigfloat z = (bigfloat)power_num / (bigfloat)power_den;
bigfloat y;
if (x == (bigfloat)1.0) y = (bigfloat)1.0;
else y = pow_bf(x,z);
if (a_length > 0) {
bigfloat sum = 0l;
for (int j=0; j<a_length; j++) sum += a[j]*pow_bf(x,a_power[j]);
return y * exp_bf(sum);
} else {
return y;
}
}
// Solve the system AX=B
int AlgRemez::simq(bigfloat A[], bigfloat B[], bigfloat X[], int n) {
int i, j, ij, ip, ipj, ipk, ipn;
int idxpiv, iback;
int k, kp, kp1, kpk, kpn;
int nip, nkp, nm1;
bigfloat em, q, rownrm, big, size, pivot, sum;
bigfloat *aa;
// simq() work vector
int *IPS = new int[(neq) * sizeof(int)];
nm1 = n - 1;
// Initialize IPS and X
ij = 0;
for (i = 0; i < n; i++) {
IPS[i] = i;
rownrm = 0.0;
for(j = 0; j < n; j++) {
q = abs_bf(A[ij]);
if(rownrm < q) rownrm = q;
++ij;
}
if (rownrm == (bigfloat)0l) {
std::cout<<"simq rownrm=0\n";
delete [] IPS;
return(1);
}
X[i] = (bigfloat)1.0 / rownrm;
}
for (k = 0; k < nm1; k++) {
big = 0.0;
idxpiv = 0;
for (i = k; i < n; i++) {
ip = IPS[i];
ipk = n*ip + k;
size = abs_bf(A[ipk]) * X[ip];
if (size > big) {
big = size;
idxpiv = i;
}
}
if (big == (bigfloat)0l) {
std::cout<<"simq big=0\n";
delete [] IPS;
return(2);
}
if (idxpiv != k) {
j = IPS[k];
IPS[k] = IPS[idxpiv];
IPS[idxpiv] = j;
}
kp = IPS[k];
kpk = n*kp + k;
pivot = A[kpk];
kp1 = k+1;
for (i = kp1; i < n; i++) {
ip = IPS[i];
ipk = n*ip + k;
em = -A[ipk] / pivot;
A[ipk] = -em;
nip = n*ip;
nkp = n*kp;
aa = A+nkp+kp1;
for (j = kp1; j < n; j++) {
ipj = nip + j;
A[ipj] = A[ipj] + em * *aa++;
}
}
}
kpn = n * IPS[n-1] + n - 1; // last element of IPS[n] th row
if (A[kpn] == (bigfloat)0l) {
std::cout<<"simq A[kpn]=0\n";
delete [] IPS;
return(3);
}
ip = IPS[0];
X[0] = B[ip];
for (i = 1; i < n; i++) {
ip = IPS[i];
ipj = n * ip;
sum = 0.0;
for (j = 0; j < i; j++) {
sum += A[ipj] * X[j];
++ipj;
}
X[i] = B[ip] - sum;
}
ipn = n * IPS[n-1] + n - 1;
X[n-1] = X[n-1] / A[ipn];
for (iback = 1; iback < n; iback++) {
//i goes (n-1),...,1
i = nm1 - iback;
ip = IPS[i];
nip = n*ip;
sum = 0.0;
aa = A+nip+i+1;
for (j= i + 1; j < n; j++)
sum += *aa++ * X[j];
X[i] = (X[i] - sum) / A[nip+i];
}
delete [] IPS;
return(0);
}
// Calculate the roots of the approximation
int AlgRemez::root() {
long i,j;
bigfloat x,dx=0.05;
bigfloat upper=1, lower=-100000;
bigfloat tol = 1e-20;
bigfloat *poly = new bigfloat[neq+1];
// First find the numerator roots
for (i=0; i<=n; i++) poly[i] = param[i];
for (i=n-1; i>=0; i--) {
roots[i] = rtnewt(poly,i+1,lower,upper,tol);
if (roots[i] == 0.0) {
std::cout<<"Failure to converge on root "<<i+1<<"/"<<n<<"\n";
return 0;
}
poly[0] = -poly[0]/roots[i];
for (j=1; j<=i; j++) poly[j] = (poly[j-1] - poly[j])/roots[i];
}
// Now find the denominator roots
poly[d] = 1l;
for (i=0; i<d; i++) poly[i] = param[n+1+i];
for (i=d-1; i>=0; i--) {
poles[i]=rtnewt(poly,i+1,lower,upper,tol);
if (poles[i] == 0.0) {
std::cout<<"Failure to converge on pole "<<i+1<<"/"<<d<<"\n";
return 0;
}
poly[0] = -poly[0]/poles[i];
for (j=1; j<=i; j++) poly[j] = (poly[j-1] - poly[j])/poles[i];
}
norm = param[n];
delete [] poly;
return 1;
}
// Evaluate the polynomial
bigfloat AlgRemez::polyEval(bigfloat x, bigfloat *poly, long size) {
bigfloat f = poly[size];
for (int i=size-1; i>=0; i--) f = f*x + poly[i];
return f;
}
// Evaluate the differential of the polynomial
bigfloat AlgRemez::polyDiff(bigfloat x, bigfloat *poly, long size) {
bigfloat df = (bigfloat)size*poly[size];
for (int i=size-1; i>0; i--) df = df*x + (bigfloat)i*poly[i];
return df;
}
// Newton's method to calculate roots
bigfloat AlgRemez::rtnewt(bigfloat *poly, long i, bigfloat x1,
bigfloat x2, bigfloat xacc) {
int j;
bigfloat df, dx, f, rtn;
rtn=(bigfloat)0.5*(x1+x2);
for (j=1; j<=JMAX;j++) {
f = polyEval(rtn, poly, i);
df = polyDiff(rtn, poly, i);
dx = f/df;
rtn -= dx;
if (abs_bf(dx) < xacc) return rtn;
}
std::cout<<"Maximum number of iterations exceeded in rtnewt\n";
return 0.0;
}
// Evaluate the partial fraction expansion of the rational function
// with res roots and poles poles. Result is overwritten on input
// arrays.
void AlgRemez::pfe(bigfloat *res, bigfloat *poles, bigfloat norm) {
int i,j,small;
bigfloat temp;
bigfloat *numerator = new bigfloat[n];
bigfloat *denominator = new bigfloat[d];
// Construct the polynomials explicitly
for (i=1; i<n; i++) {
numerator[i] = 0l;
denominator[i] = 0l;
}
numerator[0]=1l;
denominator[0]=1l;
for (j=0; j<n; j++) {
for (i=n-1; i>=0; i--) {
numerator[i] *= -res[j];
denominator[i] *= -poles[j];
if (i>0) {
numerator[i] += numerator[i-1];
denominator[i] += denominator[i-1];
}
}
}
// Convert to proper fraction form.
// Fraction is now in the form 1 + n/d, where O(n)+1=O(d)
for (i=0; i<n; i++) numerator[i] -= denominator[i];
// Find the residues of the partial fraction expansion and absorb the
// coefficients.
for (i=0; i<n; i++) {
res[i] = 0l;
for (j=n-1; j>=0; j--) {
res[i] = poles[i]*res[i]+numerator[j];
}
for (j=n-1; j>=0; j--) {
if (i!=j) res[i] /= poles[i]-poles[j];
}
res[i] *= norm;
}
// res now holds the residues
j = 0;
for (i=0; i<n; i++) poles[i] = -poles[i];
// Move the ordering of the poles from smallest to largest
for (j=0; j<n; j++) {
small = j;
for (i=j+1; i<n; i++) {
if (poles[i] < poles[small]) small = i;
}
if (small != j) {
temp = poles[small];
poles[small] = poles[j];
poles[j] = temp;
temp = res[small];
res[small] = res[j];
res[j] = temp;
}
}
delete [] numerator;
delete [] denominator;
}
double AlgRemez::evaluateApprox(double x) {
return (double)approx((bigfloat)x);
}
double AlgRemez::evaluateInverseApprox(double x) {
return 1.0/(double)approx((bigfloat)x);
}
double AlgRemez::evaluateFunc(double x) {
return (double)func((bigfloat)x);
}
double AlgRemez::evaluateInverseFunc(double x) {
return 1.0/(double)func((bigfloat)x);
}
void AlgRemez::csv(std::ostream & os)
{
double lambda_low = apstrt;
double lambda_high= apend;
for (double x=lambda_low; x<lambda_high; x*=1.05) {
double f = evaluateFunc(x);
double r = evaluateApprox(x);
os<< x<<","<<r<<","<<f<<","<<r-f<<std::endl;
}
return;
}
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/*
Mike Clark - 25th May 2005
alg_remez.h
AlgRemez is an implementation of the Remez algorithm, which in this
case is used for generating the optimal nth root rational
approximation.
Note this class requires the gnu multiprecision (GNU MP) library.
*/
#ifndef INCLUDED_ALG_REMEZ_H
#define INCLUDED_ALG_REMEZ_H
#include <stddef.h>
#include <Grid/GridStd.h>
#ifdef HAVE_LIBGMP
#include "bigfloat.h"
#else
#include "bigfloat_double.h"
#endif
#define JMAX 10000 //Maximum number of iterations of Newton's approximation
#define SUM_MAX 10 // Maximum number of terms in exponential
/*
*Usage examples
AlgRemez remez(lambda_low,lambda_high,precision);
error = remez.generateApprox(n,d,y,z);
remez.getPFE(res,pole,&norm);
remez.getIPFE(res,pole,&norm);
remez.csv(ostream &os);
*/
class AlgRemez
{
private:
char *cname;
// The approximation parameters
bigfloat *param, *roots, *poles;
bigfloat norm;
// The numerator and denominator degree (n=d)
int n, d;
// The bounds of the approximation
bigfloat apstrt, apwidt, apend;
// the numerator and denominator of the power we are approximating
unsigned long power_num;
unsigned long power_den;
// Flag to determine whether the arrays have been allocated
int alloc;
// Flag to determine whether the roots have been found
int foundRoots;
// Variables used to calculate the approximation
int nd1, iter;
bigfloat *xx, *mm, *step;
bigfloat delta, spread, tolerance;
// The exponential summation coefficients
bigfloat *a;
int *a_power;
int a_length;
// The number of equations we must solve at each iteration (n+d+1)
int neq;
// The precision of the GNU MP library
long prec;
// Initial values of maximal and minmal errors
void initialGuess();
// Solve the equations
void equations();
// Search for error maxima and minima
void search(bigfloat *step);
// Initialise step sizes
void stpini(bigfloat *step);
// Calculate the roots of the approximation
int root();
// Evaluate the polynomial
bigfloat polyEval(bigfloat x, bigfloat *poly, long size);
//complex_bf polyEval(complex_bf x, complex_bf *poly, long size);
// Evaluate the differential of the polynomial
bigfloat polyDiff(bigfloat x, bigfloat *poly, long size);
//complex_bf polyDiff(complex_bf x, complex_bf *poly, long size);
// Newton's method to calculate roots
bigfloat rtnewt(bigfloat *poly, long i, bigfloat x1, bigfloat x2, bigfloat xacc);
//complex_bf rtnewt(complex_bf *poly, long i, bigfloat x1, bigfloat x2, bigfloat xacc);
// Evaluate the partial fraction expansion of the rational function
// with res roots and poles poles. Result is overwritten on input
// arrays.
void pfe(bigfloat *res, bigfloat* poles, bigfloat norm);
// Calculate function required for the approximation
bigfloat func(bigfloat x);
// Compute size and sign of the approximation error at x
bigfloat getErr(bigfloat x, int *sign);
// Solve the system AX=B
int simq(bigfloat *A, bigfloat *B, bigfloat *X, int n);
// Free memory and reallocate as necessary
void allocate(int num_degree, int den_degree);
// Evaluate the rational form P(x)/Q(x) using coefficients from the
// solution vector param
bigfloat approx(bigfloat x);
public:
// Constructor
AlgRemez(double lower, double upper, long prec);
// Destructor
virtual ~AlgRemez();
int getDegree(void){
assert(n==d);
return n;
}
// Reset the bounds of the approximation
void setBounds(double lower, double upper);
// Reset the bounds of the approximation
void getBounds(double &lower, double &upper) {
lower=(double)apstrt;
upper=(double)apend;
}
// Generate the rational approximation x^(pnum/pden)
double generateApprox(int num_degree, int den_degree,
unsigned long power_num, unsigned long power_den,
int a_len, double* a_param, int* a_pow);
double generateApprox(int num_degree, int den_degree,
unsigned long power_num, unsigned long power_den);
double generateApprox(int degree, unsigned long power_num,
unsigned long power_den);
// Return the partial fraction expansion of the approximation x^(pnum/pden)
int getPFE(double *res, double *pole, double *norm);
// Return the partial fraction expansion of the approximation x^(-pnum/pden)
int getIPFE(double *res, double *pole, double *norm);
// Evaluate the rational form P(x)/Q(x) using coefficients from the
// solution vector param
double evaluateApprox(double x);
// Evaluate the rational form Q(x)/P(x) using coefficients from the
// solution vector param
double evaluateInverseApprox(double x);
// Calculate function required for the approximation
double evaluateFunc(double x);
// Calculate inverse function required for the approximation
double evaluateInverseFunc(double x);
// Dump csv of function, approx and error
void csv(std::ostream &os);
};
#endif // Include guard
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#include<math.h>
#include<stdio.h>
#include<stdlib.h>
#include<string>
#include<iostream>
#include<iomanip>
#include<cassert>
#include<Grid/algorithms/approx/RemezGeneral.h>
// Constructor
AlgRemezGeneral::AlgRemezGeneral(double lower, double upper, long precision,
bigfloat (*f)(bigfloat x, void *data), void *data): f(f),
data(data),
prec(precision),
apstrt(lower), apend(upper), apwidt(upper - lower),
n(0), d(0), pow_n(0), pow_d(0)
{
bigfloat::setDefaultPrecision(prec);
std::cout<<"Approximation bounds are ["<<apstrt<<","<<apend<<"]\n";
std::cout<<"Precision of arithmetic is "<<precision<<std::endl;
}
//Determine the properties of the numerator and denominator polynomials
void AlgRemezGeneral::setupPolyProperties(int num_degree, int den_degree, PolyType num_type_in, PolyType den_type_in){
pow_n = num_degree;
pow_d = den_degree;
if(pow_n % 2 == 0 && num_type_in == PolyType::Odd) assert(0);
if(pow_n % 2 == 1 && num_type_in == PolyType::Even) assert(0);
if(pow_d % 2 == 0 && den_type_in == PolyType::Odd) assert(0);
if(pow_d % 2 == 1 && den_type_in == PolyType::Even) assert(0);
num_type = num_type_in;
den_type = den_type_in;
num_pows.resize(pow_n+1);
den_pows.resize(pow_d+1);
int n_in = 0;
bool odd = num_type == PolyType::Full || num_type == PolyType::Odd;
bool even = num_type == PolyType::Full || num_type == PolyType::Even;
for(int i=0;i<=pow_n;i++){
num_pows[i] = -1;
if(i % 2 == 0 && even) num_pows[i] = n_in++;
if(i % 2 == 1 && odd) num_pows[i] = n_in++;
}
std::cout << n_in << " terms in numerator" << std::endl;
--n_in; //power is 1 less than the number of terms, eg pow=1 a x^1 + b x^0
int d_in = 0;
odd = den_type == PolyType::Full || den_type == PolyType::Odd;
even = den_type == PolyType::Full || den_type == PolyType::Even;
for(int i=0;i<=pow_d;i++){
den_pows[i] = -1;
if(i % 2 == 0 && even) den_pows[i] = d_in++;
if(i % 2 == 1 && odd) den_pows[i] = d_in++;
}
std::cout << d_in << " terms in denominator" << std::endl;
--d_in;
n = n_in;
d = d_in;
}
//Setup algorithm
void AlgRemezGeneral::reinitializeAlgorithm(){
spread = 1.0e37;
iter = 0;
neq = n + d + 1; //not +2 because highest-power term in denominator is fixed to 1
param.resize(neq);
yy.resize(neq+1);
//Initialize linear equation temporaries
A.resize(neq*neq);
B.resize(neq);
IPS.resize(neq);
//Initialize maximum and minimum errors
xx.resize(neq+2);
mm.resize(neq+1);
initialGuess();
//Initialize search steps
step.resize(neq+1);
stpini();
}
double AlgRemezGeneral::generateApprox(const int num_degree, const int den_degree,
const PolyType num_type_in, const PolyType den_type_in,
const double _tolerance, const int report_freq){
//Setup the properties of the polynomial
setupPolyProperties(num_degree, den_degree, num_type_in, den_type_in);
//Setup the algorithm
reinitializeAlgorithm();
bigfloat tolerance = _tolerance;
//Iterate until convergance
while (spread > tolerance) {
if (iter++ % report_freq==0)
std::cout<<"Iteration " <<iter-1<<" spread "<<(double)spread<<" delta "<<(double)delta << std::endl;
equations();
if (delta < tolerance) {
std::cout<<"Iteration " << iter-1 << " delta too small (" << delta << "<" << tolerance << "), try increasing precision\n";
assert(0);
};
assert( delta>= tolerance );
search();
}
int sign;
double error = (double)getErr(mm[0],&sign);
std::cout<<"Converged at "<<iter<<" iterations; error = "<<error<<std::endl;
// Return the maximum error in the approximation
return error;
}
// Initial values of maximal and minimal errors
void AlgRemezGeneral::initialGuess(){
// Supply initial guesses for solution points
long ncheb = neq; // Degree of Chebyshev error estimate
// Find ncheb+1 extrema of Chebyshev polynomial
bigfloat a = ncheb;
bigfloat r;
mm[0] = apstrt;
for (long i = 1; i < ncheb; i++) {
r = 0.5 * (1 - cos((M_PI * i)/(double) a));
//r *= sqrt_bf(r);
r = (exp((double)r)-1.0)/(exp(1.0)-1.0);
mm[i] = apstrt + r * apwidt;
}
mm[ncheb] = apend;
a = 2.0 * ncheb;
for (long i = 0; i <= ncheb; i++) {
r = 0.5 * (1 - cos(M_PI * (2*i+1)/(double) a));
//r *= sqrt_bf(r); // Squeeze to low end of interval
r = (exp((double)r)-1.0)/(exp(1.0)-1.0);
xx[i] = apstrt + r * apwidt;
}
}
// Initialise step sizes
void AlgRemezGeneral::stpini(){
xx[neq+1] = apend;
delta = 0.25;
step[0] = xx[0] - apstrt;
for (int i = 1; i < neq; i++) step[i] = xx[i] - xx[i-1];
step[neq] = step[neq-1];
}
// Search for error maxima and minima
void AlgRemezGeneral::search(){
bigfloat a, q, xm, ym, xn, yn, xx1;
int emsign, ensign, steps;
int meq = neq + 1;
bigfloat eclose = 1.0e30;
bigfloat farther = 0l;
bigfloat xx0 = apstrt;
for (int i = 0; i < meq; i++) {
steps = 0;
xx1 = xx[i]; // Next zero
if (i == meq-1) xx1 = apend;
xm = mm[i];
ym = getErr(xm,&emsign);
q = step[i];
xn = xm + q;
if (xn < xx0 || xn >= xx1) { // Cannot skip over adjacent boundaries
q = -q;
xn = xm;
yn = ym;
ensign = emsign;
} else {
yn = getErr(xn,&ensign);
if (yn < ym) {
q = -q;
xn = xm;
yn = ym;
ensign = emsign;
}
}
while(yn >= ym) { // March until error becomes smaller.
if (++steps > 10)
break;
ym = yn;
xm = xn;
emsign = ensign;
a = xm + q;
if (a == xm || a <= xx0 || a >= xx1)
break;// Must not skip over the zeros either side.
xn = a;
yn = getErr(xn,&ensign);
}
mm[i] = xm; // Position of maximum
yy[i] = ym; // Value of maximum
if (eclose > ym) eclose = ym;
if (farther < ym) farther = ym;
xx0 = xx1; // Walk to next zero.
} // end of search loop
q = (farther - eclose); // Decrease step size if error spread increased
if (eclose != 0.0) q /= eclose; // Relative error spread
if (q >= spread)
delta *= 0.5; // Spread is increasing; decrease step size
spread = q;
for (int i = 0; i < neq; i++) {
q = yy[i+1];
if (q != 0.0) q = yy[i] / q - (bigfloat)1l;
else q = 0.0625;
if (q > (bigfloat)0.25) q = 0.25;
q *= mm[i+1] - mm[i];
step[i] = q * delta;
}
step[neq] = step[neq-1];
for (int i = 0; i < neq; i++) { // Insert new locations for the zeros.
xm = xx[i] - step[i];
if (xm <= apstrt)
continue;
if (xm >= apend)
continue;
if (xm <= mm[i])
xm = (bigfloat)0.5 * (mm[i] + xx[i]);
if (xm >= mm[i+1])
xm = (bigfloat)0.5 * (mm[i+1] + xx[i]);
xx[i] = xm;
}
}
// Solve the equations
void AlgRemezGeneral::equations(){
bigfloat x, y, z;
bigfloat *aa;
for (int i = 0; i < neq; i++) { // set up the equations for solution by simq()
int ip = neq * i; // offset to 1st element of this row of matrix
x = xx[i]; // the guess for this row
y = func(x); // right-hand-side vector
z = (bigfloat)1l;
aa = A.data()+ip;
int t = 0;
for (int j = 0; j <= pow_n; j++) {
if(num_pows[j] != -1){ *aa++ = z; t++; }
z *= x;
}
assert(t == n+1);
z = (bigfloat)1l;
t = 0;
for (int j = 0; j < pow_d; j++) {
if(den_pows[j] != -1){ *aa++ = -y * z; t++; }
z *= x;
}
assert(t == d);
B[i] = y * z; // Right hand side vector
}
// Solve the simultaneous linear equations.
if (simq()){
std::cout<<"simq failed\n";
exit(0);
}
}
// Evaluate the rational form P(x)/Q(x) using coefficients
// from the solution vector param
bigfloat AlgRemezGeneral::approx(const bigfloat x) const{
// Work backwards toward the constant term.
int c = n;
bigfloat yn = param[c--]; // Highest order numerator coefficient
for (int i = pow_n-1; i >= 0; i--) yn = x * yn + (num_pows[i] != -1 ? param[c--] : bigfloat(0l));
c = n+d;
bigfloat yd = 1l; //Highest degree coefficient is 1.0
for (int i = pow_d-1; i >= 0; i--) yd = x * yd + (den_pows[i] != -1 ? param[c--] : bigfloat(0l));
return(yn/yd);
}
// Compute size and sign of the approximation error at x
bigfloat AlgRemezGeneral::getErr(bigfloat x, int *sign) const{
bigfloat f = func(x);
bigfloat e = approx(x) - f;
if (f != 0) e /= f;
if (e < (bigfloat)0.0) {
*sign = -1;
e = -e;
}
else *sign = 1;
return(e);
}
// Solve the system AX=B
int AlgRemezGeneral::simq(){
int ip, ipj, ipk, ipn;
int idxpiv;
int kp, kp1, kpk, kpn;
int nip, nkp;
bigfloat em, q, rownrm, big, size, pivot, sum;
bigfloat *aa;
bigfloat *X = param.data();
int n = neq;
int nm1 = n - 1;
// Initialize IPS and X
int ij = 0;
for (int i = 0; i < n; i++) {
IPS[i] = i;
rownrm = 0.0;
for(int j = 0; j < n; j++) {
q = abs_bf(A[ij]);
if(rownrm < q) rownrm = q;
++ij;
}
if (rownrm == (bigfloat)0l) {
std::cout<<"simq rownrm=0\n";
return(1);
}
X[i] = (bigfloat)1.0 / rownrm;
}
for (int k = 0; k < nm1; k++) {
big = 0.0;
idxpiv = 0;
for (int i = k; i < n; i++) {
ip = IPS[i];
ipk = n*ip + k;
size = abs_bf(A[ipk]) * X[ip];
if (size > big) {
big = size;
idxpiv = i;
}
}
if (big == (bigfloat)0l) {
std::cout<<"simq big=0\n";
return(2);
}
if (idxpiv != k) {
int j = IPS[k];
IPS[k] = IPS[idxpiv];
IPS[idxpiv] = j;
}
kp = IPS[k];
kpk = n*kp + k;
pivot = A[kpk];
kp1 = k+1;
for (int i = kp1; i < n; i++) {
ip = IPS[i];
ipk = n*ip + k;
em = -A[ipk] / pivot;
A[ipk] = -em;
nip = n*ip;
nkp = n*kp;
aa = A.data()+nkp+kp1;
for (int j = kp1; j < n; j++) {
ipj = nip + j;
A[ipj] = A[ipj] + em * *aa++;
}
}
}
kpn = n * IPS[n-1] + n - 1; // last element of IPS[n] th row
if (A[kpn] == (bigfloat)0l) {
std::cout<<"simq A[kpn]=0\n";
return(3);
}
ip = IPS[0];
X[0] = B[ip];
for (int i = 1; i < n; i++) {
ip = IPS[i];
ipj = n * ip;
sum = 0.0;
for (int j = 0; j < i; j++) {
sum += A[ipj] * X[j];
++ipj;
}
X[i] = B[ip] - sum;
}
ipn = n * IPS[n-1] + n - 1;
X[n-1] = X[n-1] / A[ipn];
for (int iback = 1; iback < n; iback++) {
//i goes (n-1),...,1
int i = nm1 - iback;
ip = IPS[i];
nip = n*ip;
sum = 0.0;
aa = A.data()+nip+i+1;
for (int j= i + 1; j < n; j++)
sum += *aa++ * X[j];
X[i] = (X[i] - sum) / A[nip+i];
}
return(0);
}
void AlgRemezGeneral::csv(std::ostream & os) const{
os << "Numerator" << std::endl;
for(int i=0;i<=pow_n;i++){
os << getCoeffNum(i) << "*x^" << i;
if(i!=pow_n) os << " + ";
}
os << std::endl;
os << "Denominator" << std::endl;
for(int i=0;i<=pow_d;i++){
os << getCoeffDen(i) << "*x^" << i;
if(i!=pow_d) os << " + ";
}
os << std::endl;
//For a true minimax solution the errors should all be equal and the signs should oscillate +-+-+- etc
int sign;
os << "Errors at maxima: coordinate, error, (sign)" << std::endl;
for(int i=0;i<neq+1;i++){
os << mm[i] << " " << getErr(mm[i],&sign) << " (" << sign << ")" << std::endl;
}
os << "Scan over range:" << std::endl;
int npt = 60;
bigfloat dlt = (apend - apstrt)/bigfloat(npt-1);
for (bigfloat x=apstrt; x<=apend; x = x + dlt) {
double f = evaluateFunc(x);
double r = evaluateApprox(x);
os<< x<<","<<r<<","<<f<<","<<r-f<<std::endl;
}
return;
}
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/*
C.Kelly Jan 2020 based on implementation by M. Clark May 2005
AlgRemezGeneral is an implementation of the Remez algorithm for approximating an arbitrary function by a rational polynomial
It includes optional restriction to odd/even polynomials for the numerator and/or denominator
*/
#ifndef INCLUDED_ALG_REMEZ_GENERAL_H
#define INCLUDED_ALG_REMEZ_GENERAL_H
#include <stddef.h>
#include <Grid/GridStd.h>
#ifdef HAVE_LIBGMP
#include "bigfloat.h"
#else
#include "bigfloat_double.h"
#endif
class AlgRemezGeneral{
public:
enum PolyType { Even, Odd, Full };
private:
// In GSL-style, pass the function as a function pointer. Any data required to evaluate the function is passed in as a void pointer
bigfloat (*f)(bigfloat x, void *data);
void *data;
// The approximation parameters
std::vector<bigfloat> param;
bigfloat norm;
// The number of non-zero terms in the numerator and denominator
int n, d;
// The numerator and denominator degree (i.e. the largest power)
int pow_n, pow_d;
// Specify if the numerator and/or denominator are odd/even polynomials
PolyType num_type;
PolyType den_type;
std::vector<int> num_pows; //contains the mapping, with -1 if not present
std::vector<int> den_pows;
// The bounds of the approximation
bigfloat apstrt, apwidt, apend;
// Variables used to calculate the approximation
int nd1, iter;
std::vector<bigfloat> xx;
std::vector<bigfloat> mm;
std::vector<bigfloat> step;
bigfloat delta, spread;
// Variables used in search
std::vector<bigfloat> yy;
// Variables used in solving linear equations
std::vector<bigfloat> A;
std::vector<bigfloat> B;
std::vector<int> IPS;
// The number of equations we must solve at each iteration (n+d+1)
int neq;
// The precision of the GNU MP library
long prec;
// Initialize member variables associated with the polynomial's properties
void setupPolyProperties(int num_degree, int den_degree, PolyType num_type_in, PolyType den_type_in);
// Initial values of maximal and minmal errors
void initialGuess();
// Initialise step sizes
void stpini();
// Initialize the algorithm
void reinitializeAlgorithm();
// Solve the equations
void equations();
// Search for error maxima and minima
void search();
// Calculate function required for the approximation
inline bigfloat func(bigfloat x) const{
return f(x, data);
}
// Compute size and sign of the approximation error at x
bigfloat getErr(bigfloat x, int *sign) const;
// Solve the system AX=B where X = param
int simq();
// Evaluate the rational form P(x)/Q(x) using coefficients from the solution vector param
bigfloat approx(bigfloat x) const;
public:
AlgRemezGeneral(double lower, double upper, long prec,
bigfloat (*f)(bigfloat x, void *data), void *data);
inline int getDegree(void) const{
assert(n==d);
return n;
}
// Reset the bounds of the approximation
inline void setBounds(double lower, double upper) {
apstrt = lower;
apend = upper;
apwidt = apend - apstrt;
}
// Get the bounds of the approximation
inline void getBounds(double &lower, double &upper) const{
lower=(double)apstrt;
upper=(double)apend;
}
// Run the algorithm to generate the rational approximation
double generateApprox(int num_degree, int den_degree,
PolyType num_type, PolyType den_type,
const double tolerance = 1e-15, const int report_freq = 1000);
inline double generateApprox(int num_degree, int den_degree,
const double tolerance = 1e-15, const int report_freq = 1000){
return generateApprox(num_degree, den_degree, Full, Full, tolerance, report_freq);
}
// Evaluate the rational form P(x)/Q(x) using coefficients from the
// solution vector param
inline double evaluateApprox(double x) const{
return (double)approx((bigfloat)x);
}
// Evaluate the rational form Q(x)/P(x) using coefficients from the solution vector param
inline double evaluateInverseApprox(double x) const{
return 1.0/(double)approx((bigfloat)x);
}
// Calculate function required for the approximation
inline double evaluateFunc(double x) const{
return (double)func((bigfloat)x);
}
// Calculate inverse function required for the approximation
inline double evaluateInverseFunc(double x) const{
return 1.0/(double)func((bigfloat)x);
}
// Dump csv of function, approx and error
void csv(std::ostream &os = std::cout) const;
// Get the coefficient of the term x^i in the numerator
inline double getCoeffNum(const int i) const{
return num_pows[i] == -1 ? 0. : double(param[num_pows[i]]);
}
// Get the coefficient of the term x^i in the denominator
inline double getCoeffDen(const int i) const{
if(i == pow_d) return 1.0;
else return den_pows[i] == -1 ? 0. : double(param[den_pows[i]+n+1]);
}
};
#endif
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/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/approx/ZMobius.cc
Copyright (C) 2015
Author: Christopher Kelly <ckelly@phys.columbia.edu>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#include <Grid/algorithms/approx/ZMobius.h>
#include <Grid/algorithms/approx/RemezGeneral.h>
NAMESPACE_BEGIN(Grid);
NAMESPACE_BEGIN(Approx);
//Compute the tanh approximation
inline double epsilonMobius(const double x, const std::vector<ComplexD> &w){
int Ls = w.size();
ComplexD fxp = 1., fmp = 1.;
for(int i=0;i<Ls;i++){
fxp = fxp * ( w[i] + x );
fmp = fmp * ( w[i] - x );
}
return ((fxp - fmp)/(fxp + fmp)).real();
}
inline double epsilonMobius(const double x, const std::vector<RealD> &w){
int Ls = w.size();
double fxp = 1., fmp = 1.;
for(int i=0;i<Ls;i++){
fxp = fxp * ( w[i] + x );
fmp = fmp * ( w[i] - x );
}
return (fxp - fmp)/(fxp + fmp);
}
//Compute the tanh approximation in a form suitable for the Remez
bigfloat epsilonMobius(bigfloat x, void* data){
const std::vector<RealD> &omega = *( (std::vector<RealD> const*)data );
bigfloat fxp(1.0);
bigfloat fmp(1.0);
for(int i=0;i<omega.size();i++){
fxp = fxp * ( bigfloat(omega[i]) + x);
fmp = fmp * ( bigfloat(omega[i]) - x);
}
return (fxp - fmp)/(fxp + fmp);
}
//Compute the Zmobius Omega parameters suitable for eigenvalue range -lambda_bound <= lambda <= lambda_bound
//Note omega_i = 1/(b_i + c_i) where b_i and c_i are the Mobius parameters
void computeZmobiusOmega(std::vector<ComplexD> &omega_out, const int Ls_out,
const std::vector<RealD> &omega_in, const int Ls_in,
const RealD lambda_bound){
assert(omega_in.size() == Ls_in);
omega_out.resize(Ls_out);
//Use the Remez algorithm to generate the appropriate rational polynomial
//For odd polynomial, to satisfy Haar condition must take either positive or negative half of range (cf https://arxiv.org/pdf/0803.0439.pdf page 6)
AlgRemezGeneral remez(0, lambda_bound, 64, &epsilonMobius, (void*)&omega_in);
remez.generateApprox(Ls_out-1, Ls_out,AlgRemezGeneral::Odd, AlgRemezGeneral::Even, 1e-15, 100);
remez.csv(std::cout);
//The rational approximation has the form [ f(x) - f(-x) ] / [ f(x) + f(-x) ] where f(x) = \Prod_{i=0}^{L_s-1} ( \omega_i + x )
//cf https://academiccommons.columbia.edu/doi/10.7916/D8T72HD7 pg 102
//omega_i are therefore the negative of the complex roots of f(x)
//We can find the roots by recognizing that the eigenvalues of a matrix A are the roots of the characteristic polynomial
// \rho(\lambda) = det( A - \lambda I ) where I is the unit matrix
//The matrix whose characteristic polynomial is an arbitrary monic polynomial a0 + a1 x + a2 x^2 + ... x^n is the companion matrix
// A = | 0 1 0 0 0 .... 0 |
// | 0 0 1 0 0 .... 0 |
// | : : : : : : |
// | 0 0 0 0 0 1
// | -a0 -a1 -a2 ... ... -an|
//Note the Remez defines the largest power to have unit coefficient
std::vector<RealD> coeffs(Ls_out+1);
for(int i=0;i<Ls_out+1;i+=2) coeffs[i] = coeffs[i] = remez.getCoeffDen(i); //even powers
for(int i=1;i<Ls_out+1;i+=2) coeffs[i] = coeffs[i] = remez.getCoeffNum(i); //odd powers
std::vector<std::complex<RealD> > roots(Ls_out);
//Form the companion matrix
Eigen::MatrixXd compn(Ls_out,Ls_out);
for(int i=0;i<Ls_out-1;i++) compn(i,0) = 0.;
compn(Ls_out - 1, 0) = -coeffs[0];
for(int j=1;j<Ls_out;j++){
for(int i=0;i<Ls_out-1;i++) compn(i,j) = i == j-1 ? 1. : 0.;
compn(Ls_out - 1, j) = -coeffs[j];
}
//Eigensolve
Eigen::EigenSolver<Eigen::MatrixXd> slv(compn, false);
const auto & ev = slv.eigenvalues();
for(int i=0;i<Ls_out;i++)
omega_out[i] = -ev(i);
//Sort ascending (smallest at start of vector!)
std::sort(omega_out.begin(), omega_out.end(),
[&](const ComplexD &a, const ComplexD &b){ return a.real() < b.real() || (a.real() == b.real() && a.imag() < b.imag()); });
//McGlynn thesis pg 122 suggest improved iteration counts if magnitude of omega diminishes towards the center of the 5th dimension
std::vector<ComplexD> omega_tmp = omega_out;
int s_low=0, s_high=Ls_out-1, ss=0;
for(int s_from = Ls_out-1; s_from >= 0; s_from--){ //loop from largest omega
int s_to;
if(ss % 2 == 0){
s_to = s_low++;
}else{
s_to = s_high--;
}
omega_out[s_to] = omega_tmp[s_from];
++ss;
}
std::cout << "Resulting omega_i:" << std::endl;
for(int i=0;i<Ls_out;i++)
std::cout << omega_out[i] << std::endl;
std::cout << "Test result matches the approximate polynomial found by the Remez" << std::endl;
std::cout << "<x> <remez approx> <poly approx> <diff poly approx remez approx> <exact> <diff poly approx exact>\n";
int npt = 60;
double dlt = lambda_bound/double(npt-1);
for (int i =0; i<npt; i++){
double x = i*dlt;
double r = remez.evaluateApprox(x);
double p = epsilonMobius(x, omega_out);
double e = epsilonMobius(x, omega_in);
std::cout << x<< " " << r << " " << p <<" " <<r-p << " " << e << " " << e-p << std::endl;
}
}
//mobius_param = b+c with b-c=1
void computeZmobiusOmega(std::vector<ComplexD> &omega_out, const int Ls_out, const RealD mobius_param, const int Ls_in, const RealD lambda_bound){
std::vector<RealD> omega_in(Ls_in, 1./mobius_param);
computeZmobiusOmega(omega_out, Ls_out, omega_in, Ls_in, lambda_bound);
}
//ZMobius class takes gamma_i = (b+c) omega_i as its input, where b, c are factored out
void computeZmobiusGamma(std::vector<ComplexD> &gamma_out,
const RealD mobius_param_out, const int Ls_out,
const RealD mobius_param_in, const int Ls_in,
const RealD lambda_bound){
computeZmobiusOmega(gamma_out, Ls_out, mobius_param_in, Ls_in, lambda_bound);
for(int i=0;i<Ls_out;i++) gamma_out[i] = gamma_out[i] * mobius_param_out;
}
//Assumes mobius_param_out == mobius_param_in
void computeZmobiusGamma(std::vector<ComplexD> &gamma_out, const int Ls_out, const RealD mobius_param, const int Ls_in, const RealD lambda_bound){
computeZmobiusGamma(gamma_out, mobius_param, Ls_out, mobius_param, Ls_in, lambda_bound);
}
NAMESPACE_END(Approx);
NAMESPACE_END(Grid);
-57
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@@ -1,57 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/approx/ZMobius.h
Copyright (C) 2015
Author: Christopher Kelly <ckelly@phys.columbia.edu>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_ZMOBIUS_APPROX_H
#define GRID_ZMOBIUS_APPROX_H
#include <Grid/GridCore.h>
NAMESPACE_BEGIN(Grid);
NAMESPACE_BEGIN(Approx);
//Compute the Zmobius Omega parameters suitable for eigenvalue range -lambda_bound <= lambda <= lambda_bound
//Note omega_i = 1/(b_i + c_i) where b_i and c_i are the Mobius parameters
void computeZmobiusOmega(std::vector<ComplexD> &omega_out, const int Ls_out,
const std::vector<RealD> &omega_in, const int Ls_in,
const RealD lambda_bound);
//mobius_param = b+c with b-c=1
void computeZmobiusOmega(std::vector<ComplexD> &omega_out, const int Ls_out, const RealD mobius_param, const int Ls_in, const RealD lambda_bound);
//ZMobius class takes gamma_i = (b+c) omega_i as its input, where b, c are factored out
void computeZmobiusGamma(std::vector<ComplexD> &gamma_out,
const RealD mobius_param_out, const int Ls_out,
const RealD mobius_param_in, const int Ls_in,
const RealD lambda_bound);
//Assumes mobius_param_out == mobius_param_in
void computeZmobiusGamma(std::vector<ComplexD> &gamma_out, const int Ls_out, const RealD mobius_param, const int Ls_in, const RealD lambda_bound);
NAMESPACE_END(Approx);
NAMESPACE_END(Grid);
#endif
-730
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@@ -1,730 +0,0 @@
/* -*- Mode: C; comment-column: 22; fill-column: 79; compile-command: "gcc -o zolotarev zolotarev.c -ansi -pedantic -lm -DTEST"; -*- */
#define VERSION Source Time-stamp: <2015-05-18 16:32:08 neo>
/* These C routines evalute the optimal rational approximation to the signum
* function for epsilon < |x| < 1 using Zolotarev's theorem.
*
* To obtain reliable results for high degree approximations (large n) it is
* necessary to compute using sufficiently high precision arithmetic. To this
* end the code has been parameterised to work with the preprocessor names
* INTERNAL_PRECISION and PRECISION set to float, double, or long double as
* appropriate. INTERNAL_PRECISION is used in computing the Zolotarev
* coefficients, which are converted to PRECISION before being returned to the
* caller. Presumably even higher precision could be obtained using GMP or
* similar package, but bear in mind that rounding errors might also be
* significant in evaluating the resulting polynomial. The convergence criteria
* have been written in a precision-independent form. */
#include <math.h>
#include <stdlib.h>
#include <stdio.h>
#define MAX(a,b) ((a) > (b) ? (a) : (b))
#define MIN(a,b) ((a) < (b) ? (a) : (b))
#ifndef INTERNAL_PRECISION
#define INTERNAL_PRECISION double
#endif
#include "Zolotarev.h"
#define ZOLOTAREV_INTERNAL
#undef ZOLOTAREV_DATA
#define ZOLOTAREV_DATA izd
#undef ZPRECISION
#define ZPRECISION INTERNAL_PRECISION
#include "Zolotarev.h"
#undef ZOLOTAREV_INTERNAL
/* The ANSI standard appears not to know what pi is */
#ifndef M_PI
#define M_PI ((INTERNAL_PRECISION) 3.141592653589793238462643383279502884197\
169399375105820974944592307816406286208998628034825342117068)
#endif
#define ZERO ((INTERNAL_PRECISION) 0)
#define ONE ((INTERNAL_PRECISION) 1)
#define TWO ((INTERNAL_PRECISION) 2)
#define THREE ((INTERNAL_PRECISION) 3)
#define FOUR ((INTERNAL_PRECISION) 4)
#define HALF (ONE/TWO)
/* The following obscenity seems to be the simplest (?) way to coerce the C
* preprocessor to convert the value of a preprocessor token into a string. */
#define PP2(x) #x
#define PP1(a,b,c) a ## b(c)
#define STRINGIFY(name) PP1(PP,2,name)
/* Compute the partial fraction expansion coefficients (alpha) from the
* factored form */
NAMESPACE_BEGIN(Grid);
NAMESPACE_BEGIN(Approx);
static void construct_partfrac(izd *z) {
int dn = z -> dn, dd = z -> dd, type = z -> type;
int j, k, da = dd + 1 + type;
INTERNAL_PRECISION A = z -> A, *a = z -> a, *ap = z -> ap, *alpha;
alpha = (INTERNAL_PRECISION*) malloc(da * sizeof(INTERNAL_PRECISION));
for (j = 0; j < dd; j++)
for (k = 0, alpha[j] = A; k < dd; k++)
alpha[j] *=
(k < dn ? ap[j] - a[k] : ONE) / (k == j ? ONE : ap[j] - ap[k]);
if(type == 1) /* implicit pole at zero? */
for (k = 0, alpha[dd] = A * (dn > dd ? - a[dd] : ONE); k < dd; k++) {
alpha[dd] *= a[k] / ap[k];
alpha[k] *= (dn > dd ? ap[k] - a[dd] : ONE) / ap[k];
}
alpha[da-1] = dn == da - 1 ? A : ZERO;
z -> alpha = alpha;
z -> da = da;
return;
}
/* Convert factored polynomial into dense polynomial. The input is the overall
* factor A and the roots a[i], such that p = A product(x - a[i], i = 1..d) */
static INTERNAL_PRECISION *poly_factored_to_dense(INTERNAL_PRECISION A,
INTERNAL_PRECISION *a,
int d) {
INTERNAL_PRECISION *p;
int i, j;
p = (INTERNAL_PRECISION *) malloc((d + 2) * sizeof(INTERNAL_PRECISION));
p[0] = A;
for (i = 0; i < d; i++) {
p[i+1] = p[i];
for (j = i; j > 0; j--) p[j] = p[j-1] - a[i]*p[j];
p[0] *= - a[i];
}
return p;
}
/* Convert a rational function of the form R0(x) = x p(x^2)/q(x^2) (type 0) or
* R1(x) = p(x^2)/[x q(x^2)] (type 1) into its continued fraction
* representation. We assume that 0 <= deg(q) - deg(p) <= 1 for type 0 and 0 <=
* deg(p) - deg(q) <= 1 for type 1. On input p and q are in factored form, and
* deg(q) = dq, deg(p) = dp. The output is the continued fraction coefficients
* beta, where R(x) = beta[0] x + 1/(beta[1] x + 1/(...)).
*
* The method used is as follows. There are four cases to consider:
*
* 0.i. Type 0, deg p = deg q
*
* 0.ii. Type 0, deg p = deg q - 1
*
* 1.i. Type 1, deg p = deg q
*
* 1.ii. Type 1, deg p = deg q + 1
*
* and these are connected by two transformations:
*
* A. To obtain a continued fraction expansion of type 1 we use a single-step
* polynomial division we find beta and r(x) such that p(x) = beta x q(x) +
* r(x), with deg(r) = deg(q). This implies that p(x^2) = beta x^2 q(x^2) +
* r(x^2), and thus R1(x) = x beta + r(x^2)/(x q(x^2)) = x beta + 1/R0(x)
* with R0(x) = x q(x^2)/r(x^2).
*
* B. A continued fraction expansion of type 0 is obtained in a similar, but
* not identical, manner. We use the polynomial division algorithm to compute
* the quotient beta and the remainder r that satisfy p(x) = beta q(x) + r(x)
* with deg(r) = deg(q) - 1. We thus have x p(x^2) = x beta q(x^2) + x r(x^2),
* so R0(x) = x beta + x r(x^2)/q(x^2) = x beta + 1/R1(x) with R1(x) = q(x^2) /
* (x r(x^2)).
*
* Note that the deg(r) must be exactly deg(q) for (A) and deg(q) - 1 for (B)
* because p and q have disjoint roots all of multiplicity 1. This means that
* the division algorithm requires only a single polynomial subtraction step.
*
* The transformations between the cases form the following finite state
* automaton:
*
* +------+ +------+ +------+ +------+
* | | | | ---(A)---> | | | |
* | 0.ii | ---(B)---> | 1.ii | | 0.i | <---(A)--- | 1.i |
* | | | | <---(B)--- | | | |
* +------+ +------+ +------+ +------+
*/
static INTERNAL_PRECISION *contfrac_A(INTERNAL_PRECISION *,
INTERNAL_PRECISION *,
INTERNAL_PRECISION *,
INTERNAL_PRECISION *, int, int);
static INTERNAL_PRECISION *contfrac_B(INTERNAL_PRECISION *,
INTERNAL_PRECISION *,
INTERNAL_PRECISION *,
INTERNAL_PRECISION *, int, int);
static void construct_contfrac(izd *z){
INTERNAL_PRECISION *r, A = z -> A, *p = z -> a, *q = z -> ap;
int dp = z -> dn, dq = z -> dd, type = z -> type;
z -> db = 2 * dq + 1 + type;
z -> beta = (INTERNAL_PRECISION *)
malloc(z -> db * sizeof(INTERNAL_PRECISION));
p = poly_factored_to_dense(A, p, dp);
q = poly_factored_to_dense(ONE, q, dq);
r = (INTERNAL_PRECISION *) malloc((MAX(dp,dq) + 1) *
sizeof(INTERNAL_PRECISION));
if (type == 0) (void) contfrac_B(z -> beta, p, q, r, dp, dq);
else (void) contfrac_A(z -> beta, p, q, r, dp, dq);
free(p); free(q); free(r);
return;
}
static INTERNAL_PRECISION *contfrac_A(INTERNAL_PRECISION *beta,
INTERNAL_PRECISION *p,
INTERNAL_PRECISION *q,
INTERNAL_PRECISION *r, int dp, int dq) {
INTERNAL_PRECISION quot, *rb;
int j;
/* p(x) = x beta q(x) + r(x); dp = dq or dp = dq + 1 */
quot = dp == dq ? ZERO : p[dp] / q[dq];
r[0] = p[0];
for (j = 1; j <= dp; j++) r[j] = p[j] - quot * q[j-1];
#ifdef DEBUG
printf("%s: Continued Fraction form: deg p = %2d, deg q = %2d, beta = %g\n",
__FUNCTION__, dp, dq, (float) quot);
for (j = 0; j <= dq + 1; j++)
printf("\tp[%2d] = %14.6g\tq[%2d] = %14.6g\tr[%2d] = %14.6g\n",
j, (float) (j > dp ? ZERO : p[j]),
j, (float) (j == 0 ? ZERO : q[j-1]),
j, (float) (j == dp ? ZERO : r[j]));
#endif /* DEBUG */
*(rb = contfrac_B(beta, q, r, p, dq, dq)) = quot;
return rb + 1;
}
static INTERNAL_PRECISION *contfrac_B(INTERNAL_PRECISION *beta,
INTERNAL_PRECISION *p,
INTERNAL_PRECISION *q,
INTERNAL_PRECISION *r, int dp, int dq) {
INTERNAL_PRECISION quot, *rb;
int j;
/* p(x) = beta q(x) + r(x); dp = dq or dp = dq - 1 */
quot = dp == dq ? p[dp] / q[dq] : ZERO;
for (j = 0; j < dq; j++) r[j] = p[j] - quot * q[j];
#ifdef DEBUG
printf("%s: Continued Fraction form: deg p = %2d, deg q = %2d, beta = %g\n",
__FUNCTION__, dp, dq, (float) quot);
for (j = 0; j <= dq; j++)
printf("\tp[%2d] = %14.6g\tq[%2d] = %14.6g\tr[%2d] = %14.6g\n",
j, (float) (j > dp ? ZERO : p[j]),
j, (float) q[j],
j, (float) (j == dq ? ZERO : r[j]));
#endif /* DEBUG */
*(rb = dq > 0 ? contfrac_A(beta, q, r, p, dq, dq-1) : beta) = quot;
return rb + 1;
}
/* The global variable U is used to hold the argument u throughout the AGM
* recursion. The global variables F and K are set in the innermost
* instantiation of the recursive function AGM to the values of the elliptic
* integrals F(u,k) and K(k) respectively. They must be made thread local to
* make this code thread-safe in a multithreaded environment. */
static INTERNAL_PRECISION U, F, K; /* THREAD LOCAL */
/* Recursive implementation of Gauss' arithmetico-geometric mean, which is the
* kernel of the method used to compute the Jacobian elliptic functions
* sn(u,k), cn(u,k), and dn(u,k) with parameter k (where 0 < k < 1), as well
* as the elliptic integral F(s,k) satisfying F(sn(u,k)) = u and the complete
* elliptic integral K(k).
*
* The algorithm used is a recursive implementation of the Gauss (Landen)
* transformation.
*
* The function returns the value of sn(u,k'), where k' is the dual parameter,
* and also sets the values of the global variables F and K. The latter is
* used to determine the sign of cn(u,k').
*
* The algorithm is deemed to have converged when b ceases to increase. This
* works whatever INTERNAL_PRECISION is specified. */
static INTERNAL_PRECISION AGM(INTERNAL_PRECISION a,
INTERNAL_PRECISION b,
INTERNAL_PRECISION s) {
static INTERNAL_PRECISION pb = -ONE;
INTERNAL_PRECISION c, d, xi;
if (b <= pb) {
pb = -ONE;
F = asin(s) / a; /* Here, a is the AGM */
K = M_PI / (TWO * a);
return sin(U * a);
}
pb = b;
c = a - b;
d = a + b;
xi = AGM(HALF*d, sqrt(a*b), ONE + c*c == ONE ?
HALF*s*d/a : (a - sqrt(a*a - s*s*c*d))/(c*s));
return 2*a*xi / (d + c*xi*xi);
}
/* Computes sn(u,k), cn(u,k), dn(u,k), F(u,k), and K(k). It is essentially a
* wrapper for the routine AGM. The sign of cn(u,k) is defined to be -1 if
* K(k) < u < 3*K(k) and +1 otherwise, and thus sign is computed by some quite
* unnecessarily obfuscated bit manipulations. */
static void sncndnFK(INTERNAL_PRECISION u, INTERNAL_PRECISION k,
INTERNAL_PRECISION* sn, INTERNAL_PRECISION* cn,
INTERNAL_PRECISION* dn, INTERNAL_PRECISION* elF,
INTERNAL_PRECISION* elK) {
int sgn;
U = u;
*sn = AGM(ONE, sqrt(ONE - k*k), u);
sgn = ((int) (fabs(u) / K)) % 4; /* sgn = 0, 1, 2, 3 */
sgn ^= sgn >> 1; /* (sgn & 1) = 0, 1, 1, 0 */
sgn = 1 - ((sgn & 1) << 1); /* sgn = 1, -1, -1, 1 */
*cn = ((INTERNAL_PRECISION) sgn) * sqrt(ONE - *sn * *sn);
*dn = sqrt(ONE - k*k* *sn * *sn);
*elF = F;
*elK = K;
}
/* Compute the coefficients for the optimal rational approximation R(x) to
* sgn(x) of degree n over the interval epsilon < |x| < 1 using Zolotarev's
* formula.
*
* Set type = 0 for the Zolotarev approximation, which is zero at x = 0, and
* type = 1 for the approximation which is infinite at x = 0. */
zolotarev_data* zolotarev(ZOLO_PRECISION epsilon, int n, int type) {
INTERNAL_PRECISION A, c, cp, kp, ksq, sn, cn, dn, Kp, Kj, z, z0, t, M, F,
l, invlambda, xi, xisq, *tv, s, opl;
int m, czero, ts;
zolotarev_data *zd;
izd *d = (izd*) malloc(sizeof(izd));
d -> type = type;
d -> epsilon = (INTERNAL_PRECISION) epsilon;
d -> n = n;
d -> dd = n / 2;
d -> dn = d -> dd - 1 + n % 2; /* n even: dn = dd - 1, n odd: dn = dd */
d -> deg_denom = 2 * d -> dd;
d -> deg_num = 2 * d -> dn + 1;
d -> a = (INTERNAL_PRECISION*) malloc((1 + d -> dn) *
sizeof(INTERNAL_PRECISION));
d -> ap = (INTERNAL_PRECISION*) malloc(d -> dd *
sizeof(INTERNAL_PRECISION));
ksq = d -> epsilon * d -> epsilon;
kp = sqrt(ONE - ksq);
sncndnFK(ZERO, kp, &sn, &cn, &dn, &F, &Kp); /* compute Kp = K(kp) */
z0 = TWO * Kp / (INTERNAL_PRECISION) n;
M = ONE;
A = ONE / d -> epsilon;
sncndnFK(HALF * z0, kp, &sn, &cn, &dn, &F, &Kj); /* compute xi */
xi = ONE / dn;
xisq = xi * xi;
invlambda = xi;
for (m = 0; m < d -> dd; m++) {
czero = 2 * (m + 1) == n; /* n even and m = dd -1 */
z = z0 * ((INTERNAL_PRECISION) m + ONE);
sncndnFK(z, kp, &sn, &cn, &dn, &F, &Kj);
t = cn / sn;
c = - t*t;
if (!czero) (d -> a)[d -> dn - 1 - m] = ksq / c;
z = z0 * ((INTERNAL_PRECISION) m + HALF);
sncndnFK(z, kp, &sn, &cn, &dn, &F, &Kj);
t = cn / sn;
cp = - t*t;
(d -> ap)[d -> dd - 1 - m] = ksq / cp;
M *= (ONE - c) / (ONE - cp);
A *= (czero ? -ksq : c) * (ONE - cp) / (cp * (ONE - c));
invlambda *= (ONE - c*xisq) / (ONE - cp*xisq);
}
invlambda /= M;
d -> A = TWO / (ONE + invlambda) * A;
d -> Delta = (invlambda - ONE) / (invlambda + ONE);
d -> gamma = (INTERNAL_PRECISION*) malloc((1 + d -> n) *
sizeof(INTERNAL_PRECISION));
l = ONE / invlambda;
opl = ONE + l;
sncndnFK(sqrt( d -> type == 1
? (THREE + l) / (FOUR * opl)
: (ONE + THREE*l) / (opl*opl*opl)
), sqrt(ONE - l*l), &sn, &cn, &dn, &F, &Kj);
s = M * F;
for (m = 0; m < d -> n; m++) {
sncndnFK(s + TWO*Kp*m/n, kp, &sn, &cn, &dn, &F, &Kj);
d -> gamma[m] = d -> epsilon / dn;
}
/* If R(x) is a Zolotarev rational approximation of degree (n,m) with maximum
* error Delta, then (1 - Delta^2) / R(x) is also an optimal Chebyshev
* approximation of degree (m,n) */
if (d -> type == 1) {
d -> A = (ONE - d -> Delta * d -> Delta) / d -> A;
tv = d -> a; d -> a = d -> ap; d -> ap = tv;
ts = d -> dn; d -> dn = d -> dd; d -> dd = ts;
ts = d -> deg_num; d -> deg_num = d -> deg_denom; d -> deg_denom = ts;
}
construct_partfrac(d);
construct_contfrac(d);
/* Converting everything to ZOLO_PRECISION for external use only */
zd = (zolotarev_data*) malloc(sizeof(zolotarev_data));
zd -> A = (ZOLO_PRECISION) d -> A;
zd -> Delta = (ZOLO_PRECISION) d -> Delta;
zd -> epsilon = (ZOLO_PRECISION) d -> epsilon;
zd -> n = d -> n;
zd -> type = d -> type;
zd -> dn = d -> dn;
zd -> dd = d -> dd;
zd -> da = d -> da;
zd -> db = d -> db;
zd -> deg_num = d -> deg_num;
zd -> deg_denom = d -> deg_denom;
zd -> a = (ZOLO_PRECISION*) malloc(zd -> dn * sizeof(ZOLO_PRECISION));
for (m = 0; m < zd -> dn; m++) zd -> a[m] = (ZOLO_PRECISION) d -> a[m];
free(d -> a);
zd -> ap = (ZOLO_PRECISION*) malloc(zd -> dd * sizeof(ZOLO_PRECISION));
for (m = 0; m < zd -> dd; m++) zd -> ap[m] = (ZOLO_PRECISION) d -> ap[m];
free(d -> ap);
zd -> alpha = (ZOLO_PRECISION*) malloc(zd -> da * sizeof(ZOLO_PRECISION));
for (m = 0; m < zd -> da; m++) zd -> alpha[m] = (ZOLO_PRECISION) d -> alpha[m];
free(d -> alpha);
zd -> beta = (ZOLO_PRECISION*) malloc(zd -> db * sizeof(ZOLO_PRECISION));
for (m = 0; m < zd -> db; m++) zd -> beta[m] = (ZOLO_PRECISION) d -> beta[m];
free(d -> beta);
zd -> gamma = (ZOLO_PRECISION*) malloc(zd -> n * sizeof(ZOLO_PRECISION));
for (m = 0; m < zd -> n; m++) zd -> gamma[m] = (ZOLO_PRECISION) d -> gamma[m];
free(d -> gamma);
free(d);
return zd;
}
void zolotarev_free(zolotarev_data *zdata)
{
free(zdata -> a);
free(zdata -> ap);
free(zdata -> alpha);
free(zdata -> beta);
free(zdata -> gamma);
free(zdata);
}
zolotarev_data* higham(ZOLO_PRECISION epsilon, int n) {
INTERNAL_PRECISION A, M, c, cp, z, z0, t, epssq;
int m, czero;
zolotarev_data *zd;
izd *d = (izd*) malloc(sizeof(izd));
d -> type = 0;
d -> epsilon = (INTERNAL_PRECISION) epsilon;
d -> n = n;
d -> dd = n / 2;
d -> dn = d -> dd - 1 + n % 2; /* n even: dn = dd - 1, n odd: dn = dd */
d -> deg_denom = 2 * d -> dd;
d -> deg_num = 2 * d -> dn + 1;
d -> a = (INTERNAL_PRECISION*) malloc((1 + d -> dn) *
sizeof(INTERNAL_PRECISION));
d -> ap = (INTERNAL_PRECISION*) malloc(d -> dd *
sizeof(INTERNAL_PRECISION));
A = (INTERNAL_PRECISION) n;
z0 = M_PI / A;
A = n % 2 == 0 ? A : ONE / A;
M = d -> epsilon * A;
epssq = d -> epsilon * d -> epsilon;
for (m = 0; m < d -> dd; m++) {
czero = 2 * (m + 1) == n; /* n even and m = dd - 1*/
if (!czero) {
z = z0 * ((INTERNAL_PRECISION) m + ONE);
t = tan(z);
c = - t*t;
(d -> a)[d -> dn - 1 - m] = c;
M *= epssq - c;
}
z = z0 * ((INTERNAL_PRECISION) m + HALF);
t = tan(z);
cp = - t*t;
(d -> ap)[d -> dd - 1 - m] = cp;
M /= epssq - cp;
}
d -> gamma = (INTERNAL_PRECISION*) malloc((1 + d -> n) *
sizeof(INTERNAL_PRECISION));
for (m = 0; m < d -> n; m++) d -> gamma[m] = ONE;
d -> A = A;
d -> Delta = ONE - M;
construct_partfrac(d);
construct_contfrac(d);
/* Converting everything to PRECISION for external use only */
zd = (zolotarev_data*) malloc(sizeof(zolotarev_data));
zd -> A = (ZOLO_PRECISION) d -> A;
zd -> Delta = (ZOLO_PRECISION) d -> Delta;
zd -> epsilon = (ZOLO_PRECISION) d -> epsilon;
zd -> n = d -> n;
zd -> type = d -> type;
zd -> dn = d -> dn;
zd -> dd = d -> dd;
zd -> da = d -> da;
zd -> db = d -> db;
zd -> deg_num = d -> deg_num;
zd -> deg_denom = d -> deg_denom;
zd -> a = (ZOLO_PRECISION*) malloc(zd -> dn * sizeof(ZOLO_PRECISION));
for (m = 0; m < zd -> dn; m++) zd -> a[m] = (ZOLO_PRECISION) d -> a[m];
free(d -> a);
zd -> ap = (ZOLO_PRECISION*) malloc(zd -> dd * sizeof(ZOLO_PRECISION));
for (m = 0; m < zd -> dd; m++) zd -> ap[m] = (ZOLO_PRECISION) d -> ap[m];
free(d -> ap);
zd -> alpha = (ZOLO_PRECISION*) malloc(zd -> da * sizeof(ZOLO_PRECISION));
for (m = 0; m < zd -> da; m++) zd -> alpha[m] = (ZOLO_PRECISION) d -> alpha[m];
free(d -> alpha);
zd -> beta = (ZOLO_PRECISION*) malloc(zd -> db * sizeof(ZOLO_PRECISION));
for (m = 0; m < zd -> db; m++) zd -> beta[m] = (ZOLO_PRECISION) d -> beta[m];
free(d -> beta);
zd -> gamma = (ZOLO_PRECISION*) malloc(zd -> n * sizeof(ZOLO_PRECISION));
for (m = 0; m < zd -> n; m++) zd -> gamma[m] = (ZOLO_PRECISION) d -> gamma[m];
free(d -> gamma);
free(d);
return zd;
}
NAMESPACE_END(Approx);
NAMESPACE_END(Grid);
#ifdef TEST
#undef ZERO
#define ZERO ((ZOLO_PRECISION) 0)
#undef ONE
#define ONE ((ZOLO_PRECISION) 1)
#undef TWO
#define TWO ((ZOLO_PRECISION) 2)
/* Evaluate the rational approximation R(x) using the factored form */
static ZOLO_PRECISION zolotarev_eval(ZOLO_PRECISION x, zolotarev_data* rdata) {
int m;
ZOLO_PRECISION R;
if (rdata -> type == 0) {
R = rdata -> A * x;
for (m = 0; m < rdata -> deg_denom/2; m++)
R *= (2*(m+1) > rdata -> deg_num ? ONE : x*x - rdata -> a[m]) /
(x*x - rdata -> ap[m]);
} else {
R = rdata -> A / x;
for (m = 0; m < rdata -> deg_num/2; m++)
R *= (x*x - rdata -> a[m]) /
(2*(m+1) > rdata -> deg_denom ? ONE : x*x - rdata -> ap[m]);
}
return R;
}
/* Evaluate the rational approximation R(x) using the partial fraction form */
static ZOLO_PRECISION zolotarev_partfrac_eval(ZOLO_PRECISION x, zolotarev_data* rdata) {
int m;
ZOLO_PRECISION R = rdata -> alpha[rdata -> da - 1];
for (m = 0; m < rdata -> dd; m++)
R += rdata -> alpha[m] / (x * x - rdata -> ap[m]);
if (rdata -> type == 1) R += rdata -> alpha[rdata -> dd] / (x * x);
return R * x;
}
/* Evaluate the rational approximation R(x) using continued fraction form.
*
* If x = 0 and type = 1 then the result should be INF, whereas if x = 0 and
* type = 0 then the result should be 0, but division by zero will occur at
* intermediate stages of the evaluation. For IEEE implementations with
* non-signalling overflow this will work correctly since 1/(1/0) = 1/INF = 0,
* but with signalling overflow you will get an error message. */
static ZOLO_PRECISION zolotarev_contfrac_eval(ZOLO_PRECISION x, zolotarev_data* rdata) {
int m;
ZOLO_PRECISION R = rdata -> beta[0] * x;
for (m = 1; m < rdata -> db; m++) R = rdata -> beta[m] * x + ONE / R;
return R;
}
/* Evaluate the rational approximation R(x) using Cayley form */
static ZOLO_PRECISION zolotarev_cayley_eval(ZOLO_PRECISION x, zolotarev_data* rdata) {
int m;
ZOLO_PRECISION T;
T = rdata -> type == 0 ? ONE : -ONE;
for (m = 0; m < rdata -> n; m++)
T *= (rdata -> gamma[m] - x) / (rdata -> gamma[m] + x);
return (ONE - T) / (ONE + T);
}
/* Test program. Apart from printing out the parameters for R(x) it produces
* the following data files for plotting (unless NPLOT is defined):
*
* zolotarev-fn is a plot of R(x) for |x| < 1.2. This should look like sgn(x).
*
* zolotarev-err is a plot of the error |R(x) - sgn(x)| scaled by 1/Delta. This
* should oscillate deg_num + deg_denom + 2 times between +1 and -1 over the
* domain epsilon <= |x| <= 1.
*
* If ALLPLOTS is defined then zolotarev-partfrac (zolotarev-contfrac) is a
* plot of the difference between the values of R(x) computed using the
* factored form and the partial fraction (continued fraction) form, scaled by
* 1/Delta. It should be zero everywhere. */
int main(int argc, char** argv) {
int m, n, plotpts = 5000, type = 0;
float eps, x, ypferr, ycferr, ycaylerr, maxypferr, maxycferr, maxycaylerr;
zolotarev_data *rdata;
ZOLO_PRECISION y;
FILE *plot_function, *plot_error,
*plot_partfrac, *plot_contfrac, *plot_cayley;
if (argc < 3 || argc > 4) {
fprintf(stderr, "Usage: %s epsilon n [type]\n", *argv);
exit(EXIT_FAILURE);
}
sscanf(argv[1], "%g", &eps); /* First argument is epsilon */
sscanf(argv[2], "%d", &n); /* Second argument is n */
if (argc == 4) sscanf(argv[3], "%d", &type); /* Third argument is type */
if (type < 0 || type > 2) {
fprintf(stderr, "%s: type must be 0 (Zolotarev R(0) = 0),\n"
"\t\t1 (Zolotarev R(0) = Inf, or 2 (Higham)\n", *argv);
exit(EXIT_FAILURE);
}
rdata = type == 2
? higham((ZOLO_PRECISION) eps, n)
: zolotarev((ZOLO_PRECISION) eps, n, type);
printf("Zolotarev Test: R(epsilon = %g, n = %d, type = %d)\n\t"
STRINGIFY(VERSION) "\n\t" STRINGIFY(HVERSION)
"\n\tINTERNAL_PRECISION = " STRINGIFY(INTERNAL_PRECISION)
"\tZOLO_PRECISION = " STRINGIFY(ZOLO_PRECISION)
"\n\n\tRational approximation of degree (%d,%d), %s at x = 0\n"
"\tDelta = %g (maximum error)\n\n"
"\tA = %g (overall factor)\n",
(float) rdata -> epsilon, rdata -> n, type,
rdata -> deg_num, rdata -> deg_denom,
rdata -> type == 1 ? "infinite" : "zero",
(float) rdata -> Delta, (float) rdata -> A);
for (m = 0; m < MIN(rdata -> dd, rdata -> dn); m++)
printf("\ta[%2d] = %14.8g\t\ta'[%2d] = %14.8g\n",
m + 1, (float) rdata -> a[m], m + 1, (float) rdata -> ap[m]);
if (rdata -> dd > rdata -> dn)
printf("\t\t\t\t\ta'[%2d] = %14.8g\n",
rdata -> dn + 1, (float) rdata -> ap[rdata -> dn]);
if (rdata -> dd < rdata -> dn)
printf("\ta[%2d] = %14.8g\n",
rdata -> dd + 1, (float) rdata -> a[rdata -> dd]);
printf("\n\tPartial fraction coefficients\n");
printf("\talpha[ 0] = %14.8g\n",
(float) rdata -> alpha[rdata -> da - 1]);
for (m = 0; m < rdata -> dd; m++)
printf("\talpha[%2d] = %14.8g\ta'[%2d] = %14.8g\n",
m + 1, (float) rdata -> alpha[m], m + 1, (float) rdata -> ap[m]);
if (rdata -> type == 1)
printf("\talpha[%2d] = %14.8g\ta'[%2d] = %14.8g\n",
rdata -> dd + 1, (float) rdata -> alpha[rdata -> dd],
rdata -> dd + 1, (float) ZERO);
printf("\n\tContinued fraction coefficients\n");
for (m = 0; m < rdata -> db; m++)
printf("\tbeta[%2d] = %14.8g\n", m, (float) rdata -> beta[m]);
printf("\n\tCayley transform coefficients\n");
for (m = 0; m < rdata -> n; m++)
printf("\tgamma[%2d] = %14.8g\n", m, (float) rdata -> gamma[m]);
#ifndef NPLOT
plot_function = fopen("zolotarev-fn.dat", "w");
plot_error = fopen("zolotarev-err.dat", "w");
#ifdef ALLPLOTS
plot_partfrac = fopen("zolotarev-partfrac.dat", "w");
plot_contfrac = fopen("zolotarev-contfrac.dat", "w");
plot_cayley = fopen("zolotarev-cayley.dat", "w");
#endif /* ALLPLOTS */
for (m = 0, maxypferr = maxycferr = maxycaylerr = 0.0; m <= plotpts; m++) {
x = 2.4 * (float) m / plotpts - 1.2;
if (rdata -> type == 0 || fabs(x) * (float) plotpts > 1.0) {
/* skip x = 0 for type 1, as R(0) is singular */
y = zolotarev_eval((ZOLO_PRECISION) x, rdata);
fprintf(plot_function, "%g %g\n", x, (float) y);
fprintf(plot_error, "%g %g\n",
x, (float)((y - ((x > 0.0 ? ONE : -ONE))) / rdata -> Delta));
ypferr = (float)((zolotarev_partfrac_eval((ZOLO_PRECISION) x, rdata) - y)
/ rdata -> Delta);
ycferr = (float)((zolotarev_contfrac_eval((ZOLO_PRECISION) x, rdata) - y)
/ rdata -> Delta);
ycaylerr = (float)((zolotarev_cayley_eval((ZOLO_PRECISION) x, rdata) - y)
/ rdata -> Delta);
if (fabs(x) < 1.0 && fabs(x) > rdata -> epsilon) {
maxypferr = MAX(maxypferr, fabs(ypferr));
maxycferr = MAX(maxycferr, fabs(ycferr));
maxycaylerr = MAX(maxycaylerr, fabs(ycaylerr));
}
#ifdef ALLPLOTS
fprintf(plot_partfrac, "%g %g\n", x, ypferr);
fprintf(plot_contfrac, "%g %g\n", x, ycferr);
fprintf(plot_cayley, "%g %g\n", x, ycaylerr);
#endif /* ALLPLOTS */
}
}
#ifdef ALLPLOTS
fclose(plot_cayley);
fclose(plot_contfrac);
fclose(plot_partfrac);
#endif /* ALLPLOTS */
fclose(plot_error);
fclose(plot_function);
printf("\n\tMaximum PF error = %g (relative to Delta)\n", maxypferr);
printf("\tMaximum CF error = %g (relative to Delta)\n", maxycferr);
printf("\tMaximum Cayley error = %g (relative to Delta)\n", maxycaylerr);
#endif /* NPLOT */
free(rdata -> a);
free(rdata -> ap);
free(rdata -> alpha);
free(rdata -> beta);
free(rdata -> gamma);
free(rdata);
return EXIT_SUCCESS;
}
#endif /* TEST */
-89
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@@ -1,89 +0,0 @@
/* -*- Mode: C; comment-column: 22; fill-column: 79; -*- */
#ifdef __cplusplus
#include <Grid/Namespace.h>
NAMESPACE_BEGIN(Grid);
NAMESPACE_BEGIN(Approx);
#endif
#define HVERSION Header Time-stamp: <14-OCT-2004 09:26:51.00 adk@MISSCONTRARY>
#ifndef ZOLOTAREV_INTERNAL
#ifndef ZOLO_PRECISION
#define ZOLO_PRECISION double
#endif
#define ZPRECISION ZOLO_PRECISION
#define ZOLOTAREV_DATA zolotarev_data
#endif
/* This struct contains the coefficients which parameterise an optimal rational
* approximation to the signum function.
*
* The parameterisations used are:
*
* Factored form for type 0 (R0(0) = 0)
*
* R0(x) = A * x * prod(x^2 - a[j], j = 0 .. dn-1) / prod(x^2 - ap[j], j = 0
* .. dd-1),
*
* where deg_num = 2*dn + 1 and deg_denom = 2*dd.
*
* Factored form for type 1 (R1(0) = infinity)
*
* R1(x) = (A / x) * prod(x^2 - a[j], j = 0 .. dn-1) / prod(x^2 - ap[j], j = 0
* .. dd-1),
*
* where deg_num = 2*dn and deg_denom = 2*dd + 1.
*
* Partial fraction form
*
* R(x) = alpha[da] * x + sum(alpha[j] * x / (x^2 - ap[j]), j = 0 .. da-1)
*
* where da = dd for type 0 and da = dd + 1 with ap[dd] = 0 for type 1.
*
* Continued fraction form
*
* R(x) = beta[db-1] * x + 1 / (beta[db-2] * x + 1 / (beta[db-3] * x + ...))
*
* with the final coefficient being beta[0], with d' = 2 * dd + 1 for type 0
* and db = 2 * dd + 2 for type 1.
*
* Cayley form (Chiu's domain wall formulation)
*
* R(x) = (1 - T(x)) / (1 + T(x))
*
* where T(x) = prod((x - gamma[j]) / (x + gamma[j]), j = 0 .. n-1)
*/
typedef struct {
ZPRECISION *a, /* zeros of numerator, a[0 .. dn-1] */
*ap, /* poles (zeros of denominator), ap[0 .. dd-1] */
A, /* overall factor */
*alpha, /* coefficients of partial fraction, alpha[0 .. da-1] */
*beta, /* coefficients of continued fraction, beta[0 .. db-1] */
*gamma, /* zeros of numerator of T in Cayley form */
Delta, /* maximum error, |R(x) - sgn(x)| <= Delta */
epsilon; /* minimum x value, epsilon < |x| < 1 */
int n, /* approximation degree */
type, /* 0: R(0) = 0, 1: R(0) = infinity */
dn, dd, da, db, /* number of elements of a, ap, alpha, and beta */
deg_num, /* degree of numerator = deg_denom +/- 1 */
deg_denom; /* degree of denominator */
} ZOLOTAREV_DATA;
#ifndef ZOLOTAREV_INTERNAL
/* zolotarev(epsilon, n, type) returns a pointer to an initialised
* zolotarev_data structure. The arguments must satisfy the constraints that
* epsilon > 0, n > 0, and type = 0 or 1. */
ZOLOTAREV_DATA* higham(ZOLO_PRECISION epsilon, int n) ;
ZOLOTAREV_DATA* zolotarev(ZOLO_PRECISION epsilon, int n, int type);
void zolotarev_free(zolotarev_data *zdata);
#endif
#ifdef __cplusplus
NAMESPACE_END(Approx);
NAMESPACE_END(Grid);
#endif
-208
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@@ -1,208 +0,0 @@
/*
Mike Clark - 25th May 2005
bigfloat.h
Simple C++ wrapper for multiprecision datatype used by AlgRemez
algorithm
*/
#ifndef INCLUDED_BIGFLOAT_H
#define INCLUDED_BIGFLOAT_H
#define __GMP_WITHIN_CONFIGURE
#include <gmp.h>
#include <mpf2mpfr.h>
#include <mpfr.h>
#undef __GMP_WITHIN_CONFIGURE
class bigfloat {
private:
mpf_t x;
public:
bigfloat() { mpf_init(x); }
bigfloat(const bigfloat& y) { mpf_init_set(x, y.x); }
bigfloat(const unsigned long u) { mpf_init_set_ui(x, u); }
bigfloat(const long i) { mpf_init_set_si(x, i); }
bigfloat(const int i) {mpf_init_set_si(x,(long)i);}
bigfloat(const float d) { mpf_init_set_d(x, (double)d); }
bigfloat(const double d) { mpf_init_set_d(x, d); }
bigfloat(const char *str) { mpf_init_set_str(x, (char*)str, 10); }
~bigfloat(void) { mpf_clear(x); }
operator double (void) const { return (double)mpf_get_d(x); }
static void setDefaultPrecision(unsigned long dprec) {
unsigned long bprec = (unsigned long)(3.321928094 * (double)dprec);
mpf_set_default_prec(bprec);
}
void setPrecision(unsigned long dprec) {
unsigned long bprec = (unsigned long)(3.321928094 * (double)dprec);
mpf_set_prec(x,bprec);
}
unsigned long getPrecision(void) const { return mpf_get_prec(x); }
unsigned long getDefaultPrecision(void) const { return mpf_get_default_prec(); }
bigfloat& operator=(const bigfloat& y) {
mpf_set(x, y.x);
return *this;
}
bigfloat& operator=(const unsigned long y) {
mpf_set_ui(x, y);
return *this;
}
bigfloat& operator=(const signed long y) {
mpf_set_si(x, y);
return *this;
}
bigfloat& operator=(const float y) {
mpf_set_d(x, (double)y);
return *this;
}
bigfloat& operator=(const double y) {
mpf_set_d(x, y);
return *this;
}
size_t write(void);
size_t read(void);
/* Arithmetic Functions */
bigfloat& operator+=(const bigfloat& y) { return *this = *this + y; }
bigfloat& operator-=(const bigfloat& y) { return *this = *this - y; }
bigfloat& operator*=(const bigfloat& y) { return *this = *this * y; }
bigfloat& operator/=(const bigfloat& y) { return *this = *this / y; }
friend bigfloat operator+(const bigfloat& x, const bigfloat& y) {
bigfloat a;
mpf_add(a.x,x.x,y.x);
return a;
}
friend bigfloat operator+(const bigfloat& x, const unsigned long y) {
bigfloat a;
mpf_add_ui(a.x,x.x,y);
return a;
}
friend bigfloat operator-(const bigfloat& x, const bigfloat& y) {
bigfloat a;
mpf_sub(a.x,x.x,y.x);
return a;
}
friend bigfloat operator-(const unsigned long x, const bigfloat& y) {
bigfloat a;
mpf_ui_sub(a.x,x,y.x);
return a;
}
friend bigfloat operator-(const bigfloat& x, const unsigned long y) {
bigfloat a;
mpf_sub_ui(a.x,x.x,y);
return a;
}
friend bigfloat operator-(const bigfloat& x) {
bigfloat a;
mpf_neg(a.x,x.x);
return a;
}
friend bigfloat operator*(const bigfloat& x, const bigfloat& y) {
bigfloat a;
mpf_mul(a.x,x.x,y.x);
return a;
}
friend bigfloat operator*(const bigfloat& x, const unsigned long y) {
bigfloat a;
mpf_mul_ui(a.x,x.x,y);
return a;
}
friend bigfloat operator/(const bigfloat& x, const bigfloat& y){
bigfloat a;
mpf_div(a.x,x.x,y.x);
return a;
}
friend bigfloat operator/(const unsigned long x, const bigfloat& y){
bigfloat a;
mpf_ui_div(a.x,x,y.x);
return a;
}
friend bigfloat operator/(const bigfloat& x, const unsigned long y){
bigfloat a;
mpf_div_ui(a.x,x.x,y);
return a;
}
friend bigfloat sqrt_bf(const bigfloat& x){
bigfloat a;
mpf_sqrt(a.x,x.x);
return a;
}
friend bigfloat sqrt_bf(const unsigned long x){
bigfloat a;
mpf_sqrt_ui(a.x,x);
return a;
}
friend bigfloat abs_bf(const bigfloat& x){
bigfloat a;
mpf_abs(a.x,x.x);
return a;
}
friend bigfloat pow_bf(const bigfloat& a, long power) {
bigfloat b;
mpf_pow_ui(b.x,a.x,power);
return b;
}
friend bigfloat pow_bf(const bigfloat& a, bigfloat &power) {
bigfloat b;
mpfr_pow(b.x,a.x,power.x,GMP_RNDN);
return b;
}
friend bigfloat exp_bf(const bigfloat& a) {
bigfloat b;
mpfr_exp(b.x,a.x,GMP_RNDN);
return b;
}
/* Comparison Functions */
friend int operator>(const bigfloat& x, const bigfloat& y) {
int test;
test = mpf_cmp(x.x,y.x);
if (test > 0) return 1;
else return 0;
}
friend int operator<(const bigfloat& x, const bigfloat& y) {
int test;
test = mpf_cmp(x.x,y.x);
if (test < 0) return 1;
else return 0;
}
friend int sgn(const bigfloat&);
};
#endif
-195
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@@ -1,195 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/approx/bigfloat_double.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef INCLUDED_BIGFLOAT_DOUBLE_H
#define INCLUDED_BIGFLOAT_DOUBLE_H
#include <math.h>
typedef double mfloat;
class bigfloat {
private:
mfloat x;
public:
bigfloat() { }
bigfloat(const bigfloat& y) { x=y.x; }
bigfloat(const unsigned long u) { x=u; }
bigfloat(const long i) { x=i; }
bigfloat(const int i) { x=i;}
bigfloat(const float d) { x=d;}
bigfloat(const double d) { x=d;}
bigfloat(const char *str) { x=std::stod(std::string(str));}
~bigfloat(void) { }
operator double (void) const { return (double)x; }
static void setDefaultPrecision(unsigned long dprec) {
}
void setPrecision(unsigned long dprec) {
}
unsigned long getPrecision(void) const { return 64; }
unsigned long getDefaultPrecision(void) const { return 64; }
bigfloat& operator=(const bigfloat& y) { x=y.x; return *this; }
bigfloat& operator=(const unsigned long y) { x=y; return *this; }
bigfloat& operator=(const signed long y) { x=y; return *this; }
bigfloat& operator=(const float y) { x=y; return *this; }
bigfloat& operator=(const double y) { x=y; return *this; }
size_t write(void);
size_t read(void);
/* Arithmetic Functions */
bigfloat& operator+=(const bigfloat& y) { return *this = *this + y; }
bigfloat& operator-=(const bigfloat& y) { return *this = *this - y; }
bigfloat& operator*=(const bigfloat& y) { return *this = *this * y; }
bigfloat& operator/=(const bigfloat& y) { return *this = *this / y; }
friend bigfloat operator+(const bigfloat& x, const bigfloat& y) {
bigfloat a;
a.x=x.x+y.x;
return a;
}
friend bigfloat operator+(const bigfloat& x, const unsigned long y) {
bigfloat a;
a.x=x.x+y;
return a;
}
friend bigfloat operator-(const bigfloat& x, const bigfloat& y) {
bigfloat a;
a.x=x.x-y.x;
return a;
}
friend bigfloat operator-(const unsigned long x, const bigfloat& y) {
bigfloat bx(x);
return bx-y;
}
friend bigfloat operator-(const bigfloat& x, const unsigned long y) {
bigfloat by(y);
return x-by;
}
friend bigfloat operator-(const bigfloat& x) {
bigfloat a;
a.x=-x.x;
return a;
}
friend bigfloat operator*(const bigfloat& x, const bigfloat& y) {
bigfloat a;
a.x=x.x*y.x;
return a;
}
friend bigfloat operator*(const bigfloat& x, const unsigned long y) {
bigfloat a;
a.x=x.x*y;
return a;
}
friend bigfloat operator/(const bigfloat& x, const bigfloat& y){
bigfloat a;
a.x=x.x/y.x;
return a;
}
friend bigfloat operator/(const unsigned long x, const bigfloat& y){
bigfloat bx(x);
return bx/y;
}
friend bigfloat operator/(const bigfloat& x, const unsigned long y){
bigfloat by(y);
return x/by;
}
friend bigfloat sqrt_bf(const bigfloat& x){
bigfloat a;
a.x= sqrt(x.x);
return a;
}
friend bigfloat sqrt_bf(const unsigned long x){
bigfloat a(x);
return sqrt_bf(a);
}
friend bigfloat abs_bf(const bigfloat& x){
bigfloat a;
a.x=fabs(x.x);
return a;
}
friend bigfloat pow_bf(const bigfloat& a, long power) {
bigfloat b;
b.x=pow(a.x,power);
return b;
}
friend bigfloat pow_bf(const bigfloat& a, bigfloat &power) {
bigfloat b;
b.x=pow(a.x,power.x);
return b;
}
friend bigfloat exp_bf(const bigfloat& a) {
bigfloat b;
b.x=exp(a.x);
return b;
}
/* Comparison Functions */
friend int operator>(const bigfloat& x, const bigfloat& y) {
return x.x>y.x;
}
friend int operator<(const bigfloat& x, const bigfloat& y) {
return x.x<y.x;
}
friend int sgn(const bigfloat& x) {
if ( x.x>=0 ) return 1;
else return 0;
}
/* Miscellaneous Functions */
// friend bigfloat& random(void);
};
#endif
-34
View File
@@ -1,34 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: BatchedBlas.h
Copyright (C) 2023
Author: Peter Boyle <pboyle@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#include <Grid/GridCore.h>
#include <Grid/algorithms/blas/BatchedBlas.h>
NAMESPACE_BEGIN(Grid);
gridblasHandle_t GridBLAS::gridblasHandle;
int GridBLAS::gridblasInit;
NAMESPACE_END(Grid);
-895
View File
@@ -1,895 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: BatchedBlas.h
Copyright (C) 2023
Author: Peter Boyle <pboyle@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
#ifdef GRID_HIP
#include <hipblas/hipblas.h>
#endif
#ifdef GRID_CUDA
#include <cublas_v2.h>
#endif
#ifdef GRID_SYCL
#include <oneapi/mkl.hpp>
#endif
#if 0
#define GRID_ONE_MKL
#endif
#ifdef GRID_ONE_MKL
#include <oneapi/mkl.hpp>
#endif
///////////////////////////////////////////////////////////////////////
// Need to rearrange lattice data to be in the right format for a
// batched multiply. Might as well make these static, dense packed
///////////////////////////////////////////////////////////////////////
NAMESPACE_BEGIN(Grid);
#ifdef GRID_HIP
typedef hipblasHandle_t gridblasHandle_t;
#endif
#ifdef GRID_CUDA
typedef cublasHandle_t gridblasHandle_t;
#endif
#ifdef GRID_SYCL
typedef cl::sycl::queue *gridblasHandle_t;
#endif
#ifdef GRID_ONE_MKL
typedef cl::sycl::queue *gridblasHandle_t;
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP) && !defined(GRID_ONE_MKL)
typedef int32_t gridblasHandle_t;
#endif
enum GridBLASOperation_t { GridBLAS_OP_N, GridBLAS_OP_T, GridBLAS_OP_C } ;
class GridBLAS {
public:
static gridblasHandle_t gridblasHandle;
static int gridblasInit;
static void Init(void)
{
if ( ! gridblasInit ) {
#ifdef GRID_CUDA
std::cout << "cublasCreate"<<std::endl;
cublasCreate(&gridblasHandle);
cublasSetPointerMode(gridblasHandle, CUBLAS_POINTER_MODE_DEVICE);
#endif
#ifdef GRID_HIP
std::cout << "hipblasCreate"<<std::endl;
hipblasCreate(&gridblasHandle);
#endif
#ifdef GRID_SYCL
gridblasHandle = theGridAccelerator;
#endif
#ifdef GRID_ONE_MKL
cl::sycl::gpu_selector selector;
cl::sycl::device selectedDevice { selector };
cl::sycl::property_list q_prop{cl::sycl::property::queue::in_order()};
gridblasHandle =new sycl::queue (selectedDevice,q_prop);
#endif
gridblasInit=1;
}
}
// Force construct once
GridBLAS() { Init(); };
~GridBLAS() { };
/////////////////////////////////////////////////////////////////////////////////////
// BLAS GEMM conventions:
/////////////////////////////////////////////////////////////////////////////////////
// - C = alpha A * B + beta C
// Dimensions:
// - C_m.n
// - A_m.k
// - B_k.n
// - Flops = 8 M N K
// - Bytes = 2*sizeof(word) * (MN+MK+KN)
// M=60, N=12
// Flop/Byte = 8 . 60.60.12 / (60.12+60.60+60.12)/16 = 4 so expect about 4 TF/s on a GCD
/////////////////////////////////////////////////////////////////////////////////////
void synchronise(void)
{
#ifdef GRID_HIP
auto err = hipDeviceSynchronize();
assert(err==hipSuccess);
#endif
#ifdef GRID_CUDA
auto err = cudaDeviceSynchronize();
assert(err==cudaSuccess);
#endif
#ifdef GRID_SYCL
accelerator_barrier();
#endif
#ifdef GRID_ONE_MKL
gridblasHandle->wait();
#endif
}
void gemmBatched(int m,int n, int k,
ComplexD alpha,
deviceVector<ComplexD*> &Amk, // pointer list to matrices
deviceVector<ComplexD*> &Bkn,
ComplexD beta,
deviceVector<ComplexD*> &Cmn)
{
gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
m,n,k,
alpha,
Amk,
Bkn,
beta,
Cmn);
}
void gemmBatched(int m,int n, int k,
ComplexF alpha,
deviceVector<ComplexF*> &Amk, // pointer list to matrices
deviceVector<ComplexF*> &Bkn,
ComplexF beta,
deviceVector<ComplexF*> &Cmn)
{
gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
m,n,k,
alpha,
Amk,
Bkn,
beta,
Cmn);
}
void gemmBatched(int m,int n, int k,
RealD alpha,
deviceVector<RealD*> &Amk, // pointer list to matrices
deviceVector<RealD*> &Bkn,
RealD beta,
deviceVector<RealD*> &Cmn)
{
gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
m,n,k,
alpha,
Amk,
Bkn,
beta,
Cmn);
}
void gemmBatched(int m,int n, int k,
RealF alpha,
deviceVector<RealF*> &Amk, // pointer list to matrices
deviceVector<RealF*> &Bkn,
RealF beta,
deviceVector<RealF*> &Cmn)
{
gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
m,n,k,
alpha,
Amk,
Bkn,
beta,
Cmn);
}
void gemmBatched(GridBLASOperation_t OpA,
GridBLASOperation_t OpB,
int m,int n, int k,
ComplexD alpha,
deviceVector<ComplexD*> &Amk, // pointer list to matrices
deviceVector<ComplexD*> &Bkn,
ComplexD beta,
deviceVector<ComplexD*> &Cmn)
{
RealD t2=usecond();
int32_t batchCount = Amk.size();
assert(Bkn.size()==batchCount);
assert(Cmn.size()==batchCount);
assert(OpA!=GridBLAS_OP_T); // Complex case expect no transpose
assert(OpB!=GridBLAS_OP_T);
int lda = m; // m x k column major
int ldb = k; // k x n column major
int ldc = m; // m x b column major
if(OpA!=GridBLAS_OP_N)
lda = k;
if(OpB!=GridBLAS_OP_N)
ldb = n;
static deviceVector<ComplexD> alpha_p(1);
static deviceVector<ComplexD> beta_p(1);
// can prestore the 1 and the zero on device
acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(ComplexD));
acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(ComplexD));
RealD t0=usecond();
// std::cout << "ZgemmBatched mnk "<<m<<","<<n<<","<<k<<" count "<<batchCount<<std::endl;
#ifdef GRID_HIP
hipblasOperation_t hOpA;
hipblasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
auto err = hipblasZgemmBatched(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(hipblasDoubleComplex *) &alpha_p[0],
(hipblasDoubleComplex **)&Amk[0], lda,
(hipblasDoubleComplex **)&Bkn[0], ldb,
(hipblasDoubleComplex *) &beta_p[0],
(hipblasDoubleComplex **)&Cmn[0], ldc,
batchCount);
// std::cout << " hipblas return code " <<(int)err<<std::endl;
assert(err==HIPBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_CUDA
cublasOperation_t hOpA;
cublasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
auto err = cublasZgemmBatched(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(cuDoubleComplex *) &alpha_p[0],
(cuDoubleComplex **)&Amk[0], lda,
(cuDoubleComplex **)&Bkn[0], ldb,
(cuDoubleComplex *) &beta_p[0],
(cuDoubleComplex **)&Cmn[0], ldc,
batchCount);
assert(err==CUBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_SYCL
int64_t m64=m;
int64_t n64=n;
int64_t k64=k;
int64_t lda64=lda;
int64_t ldb64=ldb;
int64_t ldc64=ldc;
int64_t batchCount64=batchCount;
oneapi::mkl::transpose iOpA;
oneapi::mkl::transpose iOpB;
if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
&iOpA,
&iOpB,
&m64,&n64,&k64,
(ComplexD *) &alpha_p[0],
(const ComplexD **)&Amk[0], (const int64_t *)&lda64,
(const ComplexD **)&Bkn[0], (const int64_t *)&ldb64,
(ComplexD *) &beta_p[0],
(ComplexD **)&Cmn[0], (const int64_t *)&ldc64,
(int64_t)1,&batchCount64,std::vector<sycl::event>());
synchronise();
#if 0
// This code was used to check the mat mul on Sunspot/OneMKL
std::cerr << " Called SYCL batched ZGEMM OpA "<< OpA << " OpB "<<OpB <<std::endl;
std::vector<ComplexD> A(m*k); // pointer list to matrices
std::vector<ComplexD> B(k*n);
std::vector<ComplexD> C(m*n);
// int sda = lda*k;
// int sdb = ldb*k;
// int sdc = ldc*n;
std::cerr << " Checking the GEMM results "<<std::endl;
for (int p = 0; p < 1; ++p) {
ComplexD * Amk_p; // pointer list to matrices
ComplexD * Bkn_p; // pointer list to matrices
ComplexD * Cmn_p; // pointer list to matrices
acceleratorCopyFromDevice((void *)&Amk[p],(void *)&Amk_p,sizeof(ComplexD*));
acceleratorCopyFromDevice((void *)&Bkn[p],(void *)&Bkn_p,sizeof(ComplexD*));
acceleratorCopyFromDevice((void *)&Cmn[p],(void *)&Cmn_p,sizeof(ComplexD*));
std::cerr << " p " << p << " copied pointers "<<std::endl;
acceleratorCopyFromDevice((void *)Amk_p,(void *)&A[0],m*k*sizeof(ComplexD));
acceleratorCopyFromDevice((void *)Bkn_p,(void *)&B[0],k*n*sizeof(ComplexD));
acceleratorCopyFromDevice((void *)Cmn_p,(void *)&C[0],m*n*sizeof(ComplexD));
std::cerr << " p " << p << " copied matrices "<<std::endl;
std::cerr << " C[0] "<<C[0]<<std::endl;
std::cerr << " A[0] "<<A[0]<<std::endl;
std::cerr << " B[0] "<<B[0]<<std::endl;
std::cerr << " m "<<m<<std::endl;
std::cerr << " n "<<n<<std::endl;
std::cerr << " k "<<k<<std::endl;
for (int mm = 0; mm < m; ++mm) {
for (int nn = 0; nn < n; ++nn) {
ComplexD c_mn(0.0);
for (int kk = 0; kk < k; ++kk) {
int idx_a, idx_b;
// int lda = m; // m x k column major
// int ldb = k; // k x n column major
// int ldc = m; // m x b column major
if(OpA!=GridBLAS_OP_N) {
idx_a =kk + mm*lda;
} else {
idx_a =mm + kk*lda;
}
if(OpB!=GridBLAS_OP_N) {
idx_b =nn + kk*ldb;
} else {
idx_b =kk + nn*ldb;
}
// std::cerr << " idx_a "<<idx_a<<" idx_b "<<idx_b<<std::endl;
ComplexD Ac = A[idx_a];
ComplexD Bc = B[idx_b];
if(OpA==GridBLAS_OP_C) Ac = conjugate(Ac);
if(OpB==GridBLAS_OP_C) Bc = conjugate(Bc);
c_mn += Ac*Bc;
}
std::cerr << " beta "<<beta<<" alpha "<<alpha<<" C_"<<mm<<","<<nn<<" "<<c_mn<<" "<<C[mm + nn*ldc]<<std::endl;
}
}
}
#endif
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
// Need a default/reference implementation; use Eigen
if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_C) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.adjoint() ;
});
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_C) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn.adjoint() ;
} );
} else {
assert(0);
}
#endif
RealD t1=usecond();
RealD flops = 8.0*m*n*k*batchCount;
RealD bytes = 1.0*sizeof(ComplexD)*(m*k+k*n+m*n)*batchCount;
// std::cout <<GridLogMessage<< " batched Blas copy "<<(t0-t2)/1.e3 <<" ms "<<std::endl;
// std::cout <<GridLogMessage<< " batched Blas zGemm call "<<m<<","<<n<<","<<k<<" "<< flops/(t1-t0)/1.e3 <<" GF/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
// std::cout <<GridLogMessage<< " batched Blas zGemm call "<<m<<","<<n<<","<<k<<" "<< bytes/(t1-t0)/1.e3 <<" GB/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
}
void gemmBatched(GridBLASOperation_t OpA,
GridBLASOperation_t OpB,
int m,int n, int k,
ComplexF alpha,
deviceVector<ComplexF*> &Amk, // pointer list to matrices
deviceVector<ComplexF*> &Bkn,
ComplexF beta,
deviceVector<ComplexF*> &Cmn)
{
RealD t2=usecond();
int32_t batchCount = Amk.size();
assert(OpA!=GridBLAS_OP_T); // Complex case expect no transpose
assert(OpB!=GridBLAS_OP_T);
int lda = m; // m x k column major
int ldb = k; // k x n column major
int ldc = m; // m x b column major
if(OpA!=GridBLAS_OP_N)
lda = k;
if(OpB!=GridBLAS_OP_N)
ldb = n;
static deviceVector<ComplexF> alpha_p(1);
static deviceVector<ComplexF> beta_p(1);
// can prestore the 1 and the zero on device
acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(ComplexF));
acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(ComplexF));
RealD t0=usecond();
assert(Bkn.size()==batchCount);
assert(Cmn.size()==batchCount);
#ifdef GRID_HIP
hipblasOperation_t hOpA;
hipblasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
auto err = hipblasCgemmBatched(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(hipblasComplex *) &alpha_p[0],
(hipblasComplex **)&Amk[0], lda,
(hipblasComplex **)&Bkn[0], ldb,
(hipblasComplex *) &beta_p[0],
(hipblasComplex **)&Cmn[0], ldc,
batchCount);
assert(err==HIPBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_CUDA
cublasOperation_t hOpA;
cublasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
auto err = cublasCgemmBatched(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(cuComplex *) &alpha_p[0],
(cuComplex **)&Amk[0], lda,
(cuComplex **)&Bkn[0], ldb,
(cuComplex *) &beta_p[0],
(cuComplex **)&Cmn[0], ldc,
batchCount);
assert(err==CUBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_SYCL
int64_t m64=m;
int64_t n64=n;
int64_t k64=k;
int64_t lda64=lda;
int64_t ldb64=ldb;
int64_t ldc64=ldc;
int64_t batchCount64=batchCount;
oneapi::mkl::transpose iOpA;
oneapi::mkl::transpose iOpB;
if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
&iOpA,
&iOpB,
&m64,&n64,&k64,
(ComplexF *) &alpha_p[0],
(const ComplexF **)&Amk[0], (const int64_t *)&lda64,
(const ComplexF **)&Bkn[0], (const int64_t *)&ldb64,
(ComplexF *) &beta_p[0],
(ComplexF **)&Cmn[0], (const int64_t *)&ldc64,
(int64_t)1,&batchCount64,std::vector<sycl::event>());
synchronise();
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
// Need a default/reference implementation; use Eigen
if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_C) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.adjoint() ;
});
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_C) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn.adjoint() ;
} );
} else {
assert(0);
}
#endif
RealD t1=usecond();
RealD flops = 8.0*m*n*k*batchCount;
RealD bytes = 1.0*sizeof(ComplexF)*(m*k+k*n+m*n)*batchCount;
}
///////////////////////////////////////////////////////////////////////////
// Single precision real GEMM
///////////////////////////////////////////////////////////////////////////
void gemmBatched(GridBLASOperation_t OpA,
GridBLASOperation_t OpB,
int m,int n, int k,
RealF alpha,
deviceVector<RealF*> &Amk, // pointer list to matrices
deviceVector<RealF*> &Bkn,
RealF beta,
deviceVector<RealF*> &Cmn)
{
RealD t2=usecond();
int32_t batchCount = Amk.size();
assert(OpA!=GridBLAS_OP_C); // Real case no conjugate
assert(OpB!=GridBLAS_OP_C);
int lda = m; // m x k column major
int ldb = k; // k x n column major
int ldc = m; // m x b column major
if(OpA!=GridBLAS_OP_N)
lda = k;
if(OpB!=GridBLAS_OP_N)
ldb = n;
static deviceVector<RealF> alpha_p(1);
static deviceVector<RealF> beta_p(1);
// can prestore the 1 and the zero on device
acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(RealF));
acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(RealF));
RealD t0=usecond();
assert(Bkn.size()==batchCount);
assert(Cmn.size()==batchCount);
#ifdef GRID_HIP
hipblasOperation_t hOpA;
hipblasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
auto err = hipblasSgemmBatched(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(float *) &alpha_p[0],
(float **)&Amk[0], lda,
(float **)&Bkn[0], ldb,
(float *) &beta_p[0],
(float **)&Cmn[0], ldc,
batchCount);
assert(err==HIPBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_CUDA
cublasOperation_t hOpA;
cublasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
auto err = cublasSgemmBatched(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(float *) &alpha_p[0],
(float **)&Amk[0], lda,
(float **)&Bkn[0], ldb,
(float *) &beta_p[0],
(float **)&Cmn[0], ldc,
batchCount);
assert(err==CUBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_SYCL
int64_t m64=m;
int64_t n64=n;
int64_t k64=k;
int64_t lda64=lda;
int64_t ldb64=ldb;
int64_t ldc64=ldc;
int64_t batchCount64=batchCount;
oneapi::mkl::transpose iOpA;
oneapi::mkl::transpose iOpB;
if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
&iOpA,
&iOpB,
&m64,&n64,&k64,
(float *) &alpha_p[0],
(const float **)&Amk[0], (const int64_t *)&lda64,
(const float **)&Bkn[0], (const int64_t *)&ldb64,
(float *) &beta_p[0],
(float **)&Cmn[0], (const int64_t *)&ldc64,
(int64_t)1,&batchCount64,std::vector<sycl::event>());
synchronise();
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
// Need a default/reference implementation; use Eigen
if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
} );
} else {
assert(0);
}
#endif
RealD t1=usecond();
RealD flops = 2.0*m*n*k*batchCount;
RealD bytes = 1.0*sizeof(RealF)*(m*k+k*n+m*n)*batchCount;
}
///////////////////////////////////////////////////////////////////////////
// Double precision real GEMM
///////////////////////////////////////////////////////////////////////////
void gemmBatched(GridBLASOperation_t OpA,
GridBLASOperation_t OpB,
int m,int n, int k,
RealD alpha,
deviceVector<RealD*> &Amk, // pointer list to matrices
deviceVector<RealD*> &Bkn,
RealD beta,
deviceVector<RealD*> &Cmn)
{
RealD t2=usecond();
int32_t batchCount = Amk.size();
assert(OpA!=GridBLAS_OP_C); // Real case no conjugate
assert(OpB!=GridBLAS_OP_C);
int lda = m; // m x k column major
int ldb = k; // k x n column major
int ldc = m; // m x b column major
if(OpA!=GridBLAS_OP_N)
lda = k;
if(OpB!=GridBLAS_OP_N)
ldb = n;
static deviceVector<RealD> alpha_p(1);
static deviceVector<RealD> beta_p(1);
// can prestore the 1 and the zero on device
acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(RealD));
acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(RealD));
RealD t0=usecond();
assert(Bkn.size()==batchCount);
assert(Cmn.size()==batchCount);
#ifdef GRID_HIP
hipblasOperation_t hOpA;
hipblasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
auto err = hipblasDgemmBatched(gridblasHandle,
HIPBLAS_OP_N,
HIPBLAS_OP_N,
m,n,k,
(double *) &alpha_p[0],
(double **)&Amk[0], lda,
(double **)&Bkn[0], ldb,
(double *) &beta_p[0],
(double **)&Cmn[0], ldc,
batchCount);
assert(err==HIPBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_CUDA
cublasOperation_t hOpA;
cublasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
auto err = cublasDgemmBatched(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(double *) &alpha_p[0],
(double **)&Amk[0], lda,
(double **)&Bkn[0], ldb,
(double *) &beta_p[0],
(double **)&Cmn[0], ldc,
batchCount);
assert(err==CUBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_SYCL
int64_t m64=m;
int64_t n64=n;
int64_t k64=k;
int64_t lda64=lda;
int64_t ldb64=ldb;
int64_t ldc64=ldc;
int64_t batchCount64=batchCount;
oneapi::mkl::transpose iOpA;
oneapi::mkl::transpose iOpB;
if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
&iOpA,
&iOpB,
&m64,&n64,&k64,
(double *) &alpha_p[0],
(const double **)&Amk[0], (const int64_t *)&lda64,
(const double **)&Bkn[0], (const int64_t *)&ldb64,
(double *) &beta_p[0],
(double **)&Cmn[0], (const int64_t *)&ldc64,
(int64_t)1,&batchCount64,std::vector<sycl::event>());
synchronise();
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
// Need a default/reference implementation; use Eigen
if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
});
} else {
assert(0);
}
#endif
RealD t1=usecond();
RealD flops = 2.0*m*n*k*batchCount;
RealD bytes = 1.0*sizeof(RealD)*(m*k+k*n+m*n)*batchCount;
}
template<class CComplex>
double benchmark(int M, int N, int K, int BATCH)
{
int32_t N_A = M*K*BATCH;
int32_t N_B = K*N*BATCH;
int32_t N_C = M*N*BATCH;
deviceVector<CComplex> A(N_A); acceleratorMemSet(&A[0],0,N_A*sizeof(CComplex));
deviceVector<CComplex> B(N_B); acceleratorMemSet(&B[0],0,N_B*sizeof(CComplex));
deviceVector<CComplex> C(N_C); acceleratorMemSet(&C[0],0,N_C*sizeof(CComplex));
CComplex alpha(1.0);
CComplex beta (1.0);
RealD flops = 8.0*M*N*K*BATCH;
int ncall=1000;
deviceVector<CComplex *> As(BATCH);
deviceVector<CComplex *> Bs(BATCH);
deviceVector<CComplex *> Cs(BATCH);
for(int b = 0 ; b < BATCH;b++) {
CComplex *ptr;
ptr = &A[b*M*K]; acceleratorPut(As[b],ptr);
ptr = &B[b*K*N]; acceleratorPut(Bs[b],ptr);
ptr = &C[b*M*N]; acceleratorPut(Cs[b],ptr);
}
// Warm up call
gemmBatched(M,N,K,
alpha,
As, // m x k
Bs, // k x n
beta,
Cs);
synchronise();
RealD t0 = usecond();
for(int i=0;i<ncall;i++){
gemmBatched(M,N,K,
alpha,
As, // m x k
Bs, // k x n
beta,
Cs);
synchronise();
}
RealD t1 = usecond();
RealD bytes = 1.0*sizeof(CComplex)*(M*N*2+N*K+M*K)*BATCH;
flops = 8.0*M*N*K*BATCH*ncall;
flops = flops/(t1-t0)/1.e3;
return flops; // Returns gigaflops
}
};
NAMESPACE_END(Grid);
-157
View File
@@ -1,157 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ImplicitlyRestartedLanczos.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_DEFLATION_H
#define GRID_DEFLATION_H
namespace Grid {
template<class Field>
class ZeroGuesser: public LinearFunction<Field> {
public:
using LinearFunction<Field>::operator();
virtual void operator()(const Field &src, Field &guess) { guess = Zero(); };
};
template<class Field>
class DoNothingGuesser: public LinearFunction<Field> {
public:
using LinearFunction<Field>::operator();
virtual void operator()(const Field &src, Field &guess) { };
};
template<class Field>
class SourceGuesser: public LinearFunction<Field> {
public:
using LinearFunction<Field>::operator();
virtual void operator()(const Field &src, Field &guess) { guess = src; };
};
////////////////////////////////
// Fine grid deflation
////////////////////////////////
template<class Field>
class DeflatedGuesser: public LinearFunction<Field> {
private:
const std::vector<Field> &evec;
const std::vector<RealD> &eval;
const unsigned int N;
public:
using LinearFunction<Field>::operator();
DeflatedGuesser(const std::vector<Field> & _evec,const std::vector<RealD> & _eval)
: DeflatedGuesser(_evec, _eval, _evec.size())
{}
DeflatedGuesser(const std::vector<Field> & _evec, const std::vector<RealD> & _eval, const unsigned int _N)
: evec(_evec), eval(_eval), N(_N)
{
assert(evec.size()==eval.size());
assert(N <= evec.size());
}
virtual void operator()(const Field &src,Field &guess) {
guess = Zero();
for (int i=0;i<N;i++) {
const Field& tmp = evec[i];
axpy(guess,TensorRemove(innerProduct(tmp,src)) / eval[i],tmp,guess);
}
guess.Checkerboard() = src.Checkerboard();
}
};
template<class FineField, class CoarseField>
class LocalCoherenceDeflatedGuesser: public LinearFunction<FineField> {
private:
const std::vector<FineField> &subspace;
const std::vector<CoarseField> &evec_coarse;
const std::vector<RealD> &eval_coarse;
public:
using LinearFunction<FineField>::operator();
LocalCoherenceDeflatedGuesser(const std::vector<FineField> &_subspace,
const std::vector<CoarseField> &_evec_coarse,
const std::vector<RealD> &_eval_coarse)
: subspace(_subspace),
evec_coarse(_evec_coarse),
eval_coarse(_eval_coarse)
{
}
void operator()(const FineField &src,FineField &guess) {
int N = (int)evec_coarse.size();
CoarseField src_coarse(evec_coarse[0].Grid());
CoarseField guess_coarse(evec_coarse[0].Grid()); guess_coarse = Zero();
blockProject(src_coarse,src,subspace);
for (int i=0;i<N;i++) {
const CoarseField & tmp = evec_coarse[i];
axpy(guess_coarse,TensorRemove(innerProduct(tmp,src_coarse)) / eval_coarse[i],tmp,guess_coarse);
}
blockPromote(guess_coarse,guess,subspace);
guess.Checkerboard() = src.Checkerboard();
};
void operator()(const std::vector<FineField> &src,std::vector<FineField> &guess) {
int Nevec = (int)evec_coarse.size();
int Nsrc = (int)src.size();
// make temp variables
std::vector<CoarseField> src_coarse(Nsrc,evec_coarse[0].Grid());
std::vector<CoarseField> guess_coarse(Nsrc,evec_coarse[0].Grid());
//Preporcessing
std::cout << GridLogMessage << "Start BlockProject for loop" << std::endl;
for (int j=0;j<Nsrc;j++)
{
guess_coarse[j] = Zero();
std::cout << GridLogMessage << "BlockProject iter: " << j << std::endl;
blockProject(src_coarse[j],src[j],subspace);
}
//deflation set up for eigen vector batchsize 1 and source batch size equal number of sources
std::cout << GridLogMessage << "Start ProjectAccum for loop" << std::endl;
for (int i=0;i<Nevec;i++)
{
std::cout << GridLogMessage << "ProjectAccum Nvec: " << i << std::endl;
const CoarseField & tmp = evec_coarse[i];
for (int j=0;j<Nsrc;j++)
{
axpy(guess_coarse[j],TensorRemove(innerProduct(tmp,src_coarse[j])) / eval_coarse[i],tmp,guess_coarse[j]);
}
}
//postprocessing
std::cout << GridLogMessage << "Start BlockPromote for loop" << std::endl;
for (int j=0;j<Nsrc;j++)
{
std::cout << GridLogMessage << "BlockProject iter: " << j << std::endl;
blockPromote(guess_coarse[j],guess[j],subspace);
guess[j].Checkerboard() = src[j].Checkerboard();
}
};
};
}
#endif
@@ -1,376 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: MultiRHSBlockCGLinalg.h
Copyright (C) 2024
Author: Peter Boyle <pboyle@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
/* Need helper object for BLAS accelerated mrhs blockCG */
template<class Field>
class MultiRHSBlockCGLinalg
{
public:
typedef typename Field::scalar_type scalar;
typedef typename Field::scalar_object scalar_object;
typedef typename Field::vector_object vector_object;
deviceVector<scalar> BLAS_X; // nrhs x vol -- the sources
deviceVector<scalar> BLAS_Y; // nrhs x vol -- the result
deviceVector<scalar> BLAS_C; // nrhs x nrhs -- the coefficients
deviceVector<scalar> BLAS_Cred; // nrhs x nrhs x oSites -- reduction buffer
deviceVector<scalar *> Xdip;
deviceVector<scalar *> Ydip;
deviceVector<scalar *> Cdip;
MultiRHSBlockCGLinalg() {};
~MultiRHSBlockCGLinalg(){ Deallocate(); };
void Deallocate(void)
{
Xdip.resize(0);
Ydip.resize(0);
Cdip.resize(0);
BLAS_Cred.resize(0);
BLAS_C.resize(0);
BLAS_X.resize(0);
BLAS_Y.resize(0);
}
void MaddMatrix(std::vector<Field> &AP, Eigen::MatrixXcd &m , const std::vector<Field> &X,const std::vector<Field> &Y,RealD scale=1.0)
{
std::vector<Field> Y_copy(AP.size(),AP[0].Grid());
for(int r=0;r<AP.size();r++){
Y_copy[r] = Y[r];
}
MulMatrix(AP,m,X);
for(int r=0;r<AP.size();r++){
AP[r] = scale*AP[r]+Y_copy[r];
}
}
void MulMatrix(std::vector<Field> &Y, Eigen::MatrixXcd &m , const std::vector<Field> &X)
{
typedef typename Field::scalar_type scomplex;
GridBase *grid;
uint64_t vol;
uint64_t words;
int nrhs = Y.size();
grid = X[0].Grid();
vol = grid->lSites();
words = sizeof(scalar_object)/sizeof(scalar);
int64_t vw = vol * words;
RealD t0 = usecond();
BLAS_X.resize(nrhs * vw); // cost free if size doesn't change
BLAS_Y.resize(nrhs * vw); // cost free if size doesn't change
BLAS_C.resize(nrhs * nrhs);// cost free if size doesn't change
RealD t1 = usecond();
/////////////////////////////////////////////
// Copy in the multi-rhs sources
/////////////////////////////////////////////
for(int r=0;r<nrhs;r++){
int64_t offset = r*vw;
autoView(x_v,X[r],AcceleratorRead);
acceleratorCopyDeviceToDevice(&x_v[0],&BLAS_X[offset],sizeof(scalar_object)*vol);
}
// Assumes Eigen storage contiguous
acceleratorCopyToDevice(&m(0,0),&BLAS_C[0],BLAS_C.size()*sizeof(scalar));
/*
* in Fortran column major notation (cuBlas order)
*
* Xxr = [X1(x)][..][Xn(x)]
* Yxr = [Y1(x)][..][Ym(x)]
* Y = X . C
*/
deviceVector<scalar *> Xd(1);
deviceVector<scalar *> Yd(1);
deviceVector<scalar *> Cd(1);
scalar * Xh = & BLAS_X[0];
scalar * Yh = & BLAS_Y[0];
scalar * Ch = & BLAS_C[0];
acceleratorPut(Xd[0],Xh);
acceleratorPut(Yd[0],Yh);
acceleratorPut(Cd[0],Ch);
RealD t2 = usecond();
GridBLAS BLAS;
/////////////////////////////////////////
// Y = X*C (transpose?)
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
vw,nrhs,nrhs,
scalar(1.0),
Xd,
Cd,
scalar(0.0), // wipe out Y
Yd);
BLAS.synchronise();
RealD t3 = usecond();
// Copy back Y = m X
for(int r=0;r<nrhs;r++){
int64_t offset = r*vw;
autoView(y_v,Y[r],AcceleratorWrite);
acceleratorCopyDeviceToDevice(&BLAS_Y[offset],&y_v[0],sizeof(scalar_object)*vol);
}
RealD t4 = usecond();
std::cout <<GridLogPerformance << "MulMatrix alloc took "<< t1-t0<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "MulMatrix preamble took "<< t2-t1<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "MulMatrix blas took "<< t3-t2<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "MulMatrix copy took "<< t4-t3<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "MulMatrix total "<< t4-t0<<" us"<<std::endl;
}
void InnerProductMatrix(Eigen::MatrixXcd &m , const std::vector<Field> &X, const std::vector<Field> &Y)
{
#if 0
int nrhs;
GridBase *grid;
uint64_t vol;
uint64_t words;
nrhs = X.size();
assert(X.size()==Y.size());
conformable(X[0],Y[0]);
grid = X[0].Grid();
vol = grid->lSites();
words = sizeof(scalar_object)/sizeof(scalar);
int64_t vw = vol * words;
RealD t0 = usecond();
BLAS_X.resize(nrhs * vw); // cost free if size doesn't change
BLAS_Y.resize(nrhs * vw); // cost free if size doesn't change
BLAS_C.resize(nrhs * nrhs);// cost free if size doesn't change
RealD t1 = usecond();
/////////////////////////////////////////////
// Copy in the multi-rhs sources
/////////////////////////////////////////////
for(int r=0;r<nrhs;r++){
int64_t offset = r*vw;
autoView(x_v,X[r],AcceleratorRead);
acceleratorCopyDeviceToDevice(&x_v[0],&BLAS_X[offset],sizeof(scalar_object)*vol);
autoView(y_v,Y[r],AcceleratorRead);
acceleratorCopyDeviceToDevice(&y_v[0],&BLAS_Y[offset],sizeof(scalar_object)*vol);
}
RealD t2 = usecond();
/*
* in Fortran column major notation (cuBlas order)
*
* Xxr = [X1(x)][..][Xn(x)]
*
* Yxr = [Y1(x)][..][Ym(x)]
*
* C_rs = X^dag Y
*/
deviceVector<scalar *> Xd(1);
deviceVector<scalar *> Yd(1);
deviceVector<scalar *> Cd(1);
scalar * Xh = & BLAS_X[0];
scalar * Yh = & BLAS_Y[0];
scalar * Ch = & BLAS_C[0];
acceleratorPut(Xd[0],Xh);
acceleratorPut(Yd[0],Yh);
acceleratorPut(Cd[0],Ch);
GridBLAS BLAS;
RealD t3 = usecond();
/////////////////////////////////////////
// C_rs = X^dag Y
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_C,GridBLAS_OP_N,
nrhs,nrhs,vw,
ComplexD(1.0),
Xd,
Yd,
ComplexD(0.0), // wipe out C
Cd);
BLAS.synchronise();
RealD t4 = usecond();
std::vector<scalar> HOST_C(BLAS_C.size()); // nrhs . nrhs -- the coefficients
acceleratorCopyFromDevice(&BLAS_C[0],&HOST_C[0],BLAS_C.size()*sizeof(scalar));
grid->GlobalSumVector(&HOST_C[0],nrhs*nrhs);
RealD t5 = usecond();
for(int rr=0;rr<nrhs;rr++){
for(int r=0;r<nrhs;r++){
int off = r+nrhs*rr;
m(r,rr)=HOST_C[off];
}
}
RealD t6 = usecond();
uint64_t M=nrhs;
uint64_t N=nrhs;
uint64_t K=vw;
RealD bytes = 1.0*sizeof(ComplexD)*(M*N*2+N*K+M*K);
RealD flops = 8.0*M*N*K;
flops = flops/(t4-t3)/1.e3;
bytes = bytes/(t4-t3)/1.e3;
std::cout <<GridLogPerformance<< "InnerProductMatrix m,n,k "<< M<<","<<N<<","<<K<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix alloc t1 "<< t1-t0<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix cp t2 "<< t2-t1<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix setup t3 "<< t3-t2<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix blas t4 "<< t4-t3<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix blas "<< flops<<" GF/s"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix blas "<< bytes<<" GB/s"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix gsum t5 "<< t5-t4<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix cp t6 "<< t6-t5<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix took "<< t6-t0<<" us"<<std::endl;
#else
int nrhs;
GridBase *grid;
uint64_t vol;
uint64_t words;
nrhs = X.size();
assert(X.size()==Y.size());
conformable(X[0],Y[0]);
grid = X[0].Grid();
int rd0 = grid->_rdimensions[0] * grid->_rdimensions[1];
vol = grid->oSites()/rd0;
words = rd0*sizeof(vector_object)/sizeof(scalar);
int64_t vw = vol * words;
assert(vw == grid->lSites()*sizeof(scalar_object)/sizeof(scalar));
RealD t0 = usecond();
BLAS_X.resize(nrhs * vw); // cost free if size doesn't change
BLAS_Y.resize(nrhs * vw); // cost free if size doesn't change
BLAS_Cred.resize(nrhs * nrhs * vol);// cost free if size doesn't change
RealD t1 = usecond();
/////////////////////////////////////////////
// Copy in the multi-rhs sources -- layout batched BLAS ready
/////////////////////////////////////////////
for(int r=0;r<nrhs;r++){
autoView(x_v,X[r],AcceleratorRead);
autoView(y_v,Y[r],AcceleratorRead);
scalar *from_x=(scalar *)&x_v[0];
scalar *from_y=(scalar *)&y_v[0];
scalar *BX = &BLAS_X[0];
scalar *BY = &BLAS_Y[0];
accelerator_for(ssw,vw,1,{
uint64_t ss=ssw/words;
uint64_t w=ssw%words;
uint64_t offset = w+r*words+ss*nrhs*words; // [ss][rhs][words]
BX[offset] = from_x[ssw];
BY[offset] = from_y[ssw];
});
}
RealD t2 = usecond();
/*
* in Fortran column major notation (cuBlas order)
*
* Xxr = [X1(x)][..][Xn(x)]
*
* Yxr = [Y1(x)][..][Ym(x)]
*
* C_rs = X^dag Y
*/
Xdip.resize(vol);
Ydip.resize(vol);
Cdip.resize(vol);
std::vector<scalar *> Xh(vol);
std::vector<scalar *> Yh(vol);
std::vector<scalar *> Ch(vol);
for(uint64_t ss=0;ss<vol;ss++){
Xh[ss] = & BLAS_X[ss*nrhs*words];
Yh[ss] = & BLAS_Y[ss*nrhs*words];
Ch[ss] = & BLAS_Cred[ss*nrhs*nrhs];
}
acceleratorCopyToDevice(&Xh[0],&Xdip[0],vol*sizeof(scalar *));
acceleratorCopyToDevice(&Yh[0],&Ydip[0],vol*sizeof(scalar *));
acceleratorCopyToDevice(&Ch[0],&Cdip[0],vol*sizeof(scalar *));
GridBLAS BLAS;
RealD t3 = usecond();
/////////////////////////////////////////
// C_rs = X^dag Y
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_C,GridBLAS_OP_N,
nrhs,nrhs,words,
ComplexD(1.0),
Xdip,
Ydip,
ComplexD(0.0), // wipe out C
Cdip);
BLAS.synchronise();
RealD t4 = usecond();
std::vector<scalar> HOST_C(BLAS_Cred.size()); // nrhs . nrhs -- the coefficients
acceleratorCopyFromDevice(&BLAS_Cred[0],&HOST_C[0],BLAS_Cred.size()*sizeof(scalar));
RealD t5 = usecond();
m = Eigen::MatrixXcd::Zero(nrhs,nrhs);
for(int ss=0;ss<vol;ss++){
Eigen::Map<Eigen::MatrixXcd> eC((std::complex<double> *)&HOST_C[ss*nrhs*nrhs],nrhs,nrhs);
m = m + eC;
}
RealD t6l = usecond();
grid->GlobalSumVector((scalar *) &m(0,0),nrhs*nrhs);
RealD t6 = usecond();
uint64_t M=nrhs;
uint64_t N=nrhs;
uint64_t K=vw;
RealD xybytes = grid->lSites()*sizeof(scalar_object);
RealD bytes = 1.0*sizeof(ComplexD)*(M*N*2+N*K+M*K);
RealD flops = 8.0*M*N*K;
flops = flops/(t4-t3)/1.e3;
bytes = bytes/(t4-t3)/1.e3;
xybytes = 4*xybytes/(t2-t1)/1.e3;
std::cout <<GridLogPerformance<< "InnerProductMatrix m,n,k "<< M<<","<<N<<","<<K<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix alloc t1 "<< t1-t0<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix cp t2 "<< t2-t1<<" us "<<xybytes<<" GB/s"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix setup t3 "<< t3-t2<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix blas t4 "<< t4-t3<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix blas "<< flops<<" GF/s"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix blas "<< bytes<<" GB/s"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix cp t5 "<< t5-t4<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix lsum t6l "<< t6l-t5<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix gsum t6 "<< t6-t6l<<" us"<<std::endl;
std::cout <<GridLogPerformance<< "InnerProductMatrix took "<< t6-t0<<" us"<<std::endl;
#endif
}
};
NAMESPACE_END(Grid);
@@ -1,513 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: MultiRHSDeflation.h
Copyright (C) 2023
Author: Peter Boyle <pboyle@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
/*
MultiRHS block projection
Import basis -> nblock x nbasis x (block x internal)
Import vector of fine lattice objects -> nblock x nrhs x (block x internal)
=> coarse_(nrhs x nbasis )^block = via batched GEMM
//template<class vobj,class CComplex,int nbasis,class VLattice>
//inline void blockProject(Lattice<iVector<CComplex,nbasis > > &coarseData,
// const VLattice &fineData,
// const VLattice &Basis)
*/
template<class Field>
class MultiRHSBlockProject
{
public:
typedef typename Field::scalar_type scalar;
typedef typename Field::scalar_object scalar_object;
typedef Field Fermion;
int nbasis;
GridBase *coarse_grid;
GridBase *fine_grid;
uint64_t block_vol;
uint64_t fine_vol;
uint64_t coarse_vol;
uint64_t words;
// Row major layout "C" order:
// BLAS_V[coarse_vol][nbasis][block_vol][words]
// BLAS_F[coarse_vol][nrhs][block_vol][words]
// BLAS_C[coarse_vol][nrhs][nbasis]
/*
* in Fortran column major notation (cuBlas order)
*
* Vxb = [v1(x)][..][vn(x)] ... x coarse vol
*
* Fxr = [r1(x)][..][rm(x)] ... x coarse vol
*
* Block project:
* C_br = V^dag F x coarse vol
*
* Block promote:
* F_xr = Vxb Cbr x coarse_vol
*/
deviceVector<scalar> BLAS_V; // words * block_vol * nbasis x coarse_vol
deviceVector<scalar> BLAS_F; // nrhs x fine_vol * words -- the sources
deviceVector<scalar> BLAS_C; // nrhs x coarse_vol * nbasis -- the coarse coeffs
RealD blasNorm2(deviceVector<scalar> &blas)
{
scalar ss(0.0);
std::vector<scalar> tmp(blas.size());
acceleratorCopyFromDevice(&blas[0],&tmp[0],blas.size()*sizeof(scalar));
for(int64_t s=0;s<blas.size();s++){
ss=ss+tmp[s]*adj(tmp[s]);
}
coarse_grid->GlobalSum(ss);
return real(ss);
}
MultiRHSBlockProject(){};
~MultiRHSBlockProject(){ Deallocate(); };
void Deallocate(void)
{
nbasis=0;
coarse_grid=nullptr;
fine_grid=nullptr;
fine_vol=0;
block_vol=0;
coarse_vol=0;
words=0;
BLAS_V.resize(0);
BLAS_F.resize(0);
BLAS_C.resize(0);
}
void Allocate(int _nbasis,GridBase *_fgrid,GridBase *_cgrid)
{
nbasis=_nbasis;
fine_grid=_fgrid;
coarse_grid=_cgrid;
fine_vol = fine_grid->lSites();
coarse_vol = coarse_grid->lSites();
block_vol = fine_vol/coarse_vol;
words = sizeof(scalar_object)/sizeof(scalar);
BLAS_V.resize (fine_vol * words * nbasis );
}
void ImportFineGridVectors(std::vector <Field > &vecs, deviceVector<scalar> &blas)
{
int nvec = vecs.size();
typedef typename Field::vector_object vobj;
// std::cout << GridLogMessage <<" BlockProjector importing "<<nvec<< " fine grid vectors" <<std::endl;
assert(vecs[0].Grid()==fine_grid);
subdivides(coarse_grid,fine_grid); // require they map
int _ndimension = coarse_grid->_ndimension;
assert(block_vol == fine_grid->oSites() / coarse_grid->oSites());
Coordinate block_r (_ndimension);
for(int d=0 ; d<_ndimension;d++){
block_r[d] = fine_grid->_rdimensions[d] / coarse_grid->_rdimensions[d];
}
uint64_t sz = blas.size();
acceleratorMemSet(&blas[0],0,blas.size()*sizeof(scalar));
Coordinate fine_rdimensions = fine_grid->_rdimensions;
Coordinate coarse_rdimensions = coarse_grid->_rdimensions;
int64_t bv= block_vol;
for(int v=0;v<vecs.size();v++){
// std::cout << " BlockProjector importing vector"<<v<<" "<<norm2(vecs[v])<<std::endl;
autoView( fineData , vecs[v], AcceleratorRead);
auto blasData_p = &blas[0];
auto fineData_p = &fineData[0];
int64_t osites = fine_grid->oSites();
// loop over fine sites
const int Nsimd = vobj::Nsimd();
// std::cout << "sz "<<sz<<std::endl;
// std::cout << "prod "<<Nsimd * coarse_grid->oSites() * block_vol * nvec * words<<std::endl;
assert(sz == Nsimd * coarse_grid->oSites() * block_vol * nvec * words);
uint64_t lwords= words; // local variable for copy in to GPU
accelerator_for(sf,osites,Nsimd,{
#ifdef GRID_SIMT
{
int lane=acceleratorSIMTlane(Nsimd); // buffer lane
#else
for(int lane=0;lane<Nsimd;lane++) {
#endif
// One thread per fine site
Coordinate coor_f(_ndimension);
Coordinate coor_b(_ndimension);
Coordinate coor_c(_ndimension);
// Fine site to fine coor
Lexicographic::CoorFromIndex(coor_f,sf,fine_rdimensions);
for(int d=0;d<_ndimension;d++) coor_b[d] = coor_f[d]%block_r[d];
for(int d=0;d<_ndimension;d++) coor_c[d] = coor_f[d]/block_r[d];
int sc;// coarse site
int sb;// block site
Lexicographic::IndexFromCoor(coor_c,sc,coarse_rdimensions);
Lexicographic::IndexFromCoor(coor_b,sb,block_r);
scalar_object data = extractLane(lane,fineData[sf]);
// BLAS layout address calculation
// words * block_vol * nbasis x coarse_vol
// coarse oSite x block vole x lanes
int64_t site = (lane*osites + sc*bv)*nvec
+ v*bv
+ sb;
// assert(site*lwords<sz);
scalar_object * ptr = (scalar_object *)&blasData_p[site*lwords];
*ptr = data;
#ifdef GRID_SIMT
}
#else
}
#endif
});
// std::cout << " import fine Blas norm "<<blasNorm2(blas)<<std::endl;
// std::cout << " BlockProjector imported vector"<<v<<std::endl;
}
}
void ExportFineGridVectors(std::vector <Field> &vecs, deviceVector<scalar> &blas)
{
typedef typename Field::vector_object vobj;
int nvec = vecs.size();
assert(vecs[0].Grid()==fine_grid);
subdivides(coarse_grid,fine_grid); // require they map
int _ndimension = coarse_grid->_ndimension;
assert(block_vol == fine_grid->oSites() / coarse_grid->oSites());
Coordinate block_r (_ndimension);
for(int d=0 ; d<_ndimension;d++){
block_r[d] = fine_grid->_rdimensions[d] / coarse_grid->_rdimensions[d];
}
Coordinate fine_rdimensions = fine_grid->_rdimensions;
Coordinate coarse_rdimensions = coarse_grid->_rdimensions;
// std::cout << " export fine Blas norm "<<blasNorm2(blas)<<std::endl;
int64_t bv= block_vol;
for(int v=0;v<vecs.size();v++){
autoView( fineData , vecs[v], AcceleratorWrite);
auto blasData_p = &blas[0];
auto fineData_p = &fineData[0];
int64_t osites = fine_grid->oSites();
uint64_t lwords = words;
// std::cout << " Nsimd is "<<vobj::Nsimd() << std::endl;
// std::cout << " lwords is "<<lwords << std::endl;
// std::cout << " sizeof(scalar_object) is "<<sizeof(scalar_object) << std::endl;
// loop over fine sites
accelerator_for(sf,osites,vobj::Nsimd(),{
#ifdef GRID_SIMT
{
int lane=acceleratorSIMTlane(vobj::Nsimd()); // buffer lane
#else
for(int lane=0;lane<vobj::Nsimd();lane++) {
#endif
// One thread per fine site
Coordinate coor_f(_ndimension);
Coordinate coor_b(_ndimension);
Coordinate coor_c(_ndimension);
Lexicographic::CoorFromIndex(coor_f,sf,fine_rdimensions);
for(int d=0;d<_ndimension;d++) coor_b[d] = coor_f[d]%block_r[d];
for(int d=0;d<_ndimension;d++) coor_c[d] = coor_f[d]/block_r[d];
int sc;
int sb;
Lexicographic::IndexFromCoor(coor_c,sc,coarse_rdimensions);
Lexicographic::IndexFromCoor(coor_b,sb,block_r);
// BLAS layout address calculation
// words * block_vol * nbasis x coarse_vol
int64_t site = (lane*osites + sc*bv)*nvec
+ v*bv
+ sb;
scalar_object * ptr = (scalar_object *)&blasData_p[site*lwords];
scalar_object data = *ptr;
insertLane(lane,fineData[sf],data);
#ifdef GRID_SIMT
}
#else
}
#endif
});
}
}
template<class vobj>
void ImportCoarseGridVectors(std::vector <Lattice<vobj> > &vecs, deviceVector<scalar> &blas)
{
int nvec = vecs.size();
typedef typename vobj::scalar_object coarse_scalar_object;
// std::cout << " BlockProjector importing "<<nvec<< " coarse grid vectors" <<std::endl;
assert(vecs[0].Grid()==coarse_grid);
int _ndimension = coarse_grid->_ndimension;
uint64_t sz = blas.size();
Coordinate coarse_rdimensions = coarse_grid->_rdimensions;
for(int v=0;v<vecs.size();v++){
// std::cout << " BlockProjector importing coarse vector"<<v<<" "<<norm2(vecs[v])<<std::endl;
autoView( coarseData , vecs[v], AcceleratorRead);
auto blasData_p = &blas[0];
auto coarseData_p = &coarseData[0];
int64_t osites = coarse_grid->oSites();
// loop over fine sites
const int Nsimd = vobj::Nsimd();
uint64_t cwords=sizeof(typename vobj::scalar_object)/sizeof(scalar);
assert(cwords==nbasis);
accelerator_for(sc,osites,Nsimd,{
#ifdef GRID_SIMT
{
int lane=acceleratorSIMTlane(Nsimd); // buffer lane
#else
for(int lane=0;lane<Nsimd;lane++) {
#endif
// C_br per site
int64_t blas_site = (lane*osites + sc)*nvec*cwords + v*cwords;
coarse_scalar_object data = extractLane(lane,coarseData[sc]);
coarse_scalar_object * ptr = (coarse_scalar_object *)&blasData_p[blas_site];
*ptr = data;
#ifdef GRID_SIMT
}
#else
}
#endif
});
// std::cout << " import coarsee Blas norm "<<blasNorm2(blas)<<std::endl;
}
}
template<class vobj>
void ExportCoarseGridVectors(std::vector <Lattice<vobj> > &vecs, deviceVector<scalar> &blas)
{
int nvec = vecs.size();
typedef typename vobj::scalar_object coarse_scalar_object;
// std::cout << GridLogMessage<<" BlockProjector exporting "<<nvec<< " coarse grid vectors" <<std::endl;
assert(vecs[0].Grid()==coarse_grid);
int _ndimension = coarse_grid->_ndimension;
uint64_t sz = blas.size();
Coordinate coarse_rdimensions = coarse_grid->_rdimensions;
// std::cout << " export coarsee Blas norm "<<blasNorm2(blas)<<std::endl;
for(int v=0;v<vecs.size();v++){
// std::cout << " BlockProjector exporting coarse vector"<<v<<std::endl;
autoView( coarseData , vecs[v], AcceleratorWrite);
auto blasData_p = &blas[0];
auto coarseData_p = &coarseData[0];
int64_t osites = coarse_grid->oSites();
// loop over fine sites
const int Nsimd = vobj::Nsimd();
uint64_t cwords=sizeof(typename vobj::scalar_object)/sizeof(scalar);
assert(cwords==nbasis);
accelerator_for(sc,osites,Nsimd,{
// Wrap in a macro "FOR_ALL_LANES(lane,{ ... });
#ifdef GRID_SIMT
{
int lane=acceleratorSIMTlane(Nsimd); // buffer lane
#else
for(int lane=0;lane<Nsimd;lane++) {
#endif
int64_t blas_site = (lane*osites + sc)*nvec*cwords + v*cwords;
coarse_scalar_object * ptr = (coarse_scalar_object *)&blasData_p[blas_site];
coarse_scalar_object data = *ptr;
insertLane(lane,coarseData[sc],data);
#ifdef GRID_SIMT
}
#else
}
#endif
});
}
}
void ImportBasis(std::vector < Field > &vecs)
{
// std::cout << " BlockProjector Import basis size "<<vecs.size()<<std::endl;
ImportFineGridVectors(vecs,BLAS_V);
}
template<class cobj>
void blockProject(std::vector<Field> &fine,std::vector< Lattice<cobj> > & coarse)
{
int nrhs=fine.size();
int _nbasis = sizeof(typename cobj::scalar_object)/sizeof(scalar);
// std::cout << "blockProject nbasis " <<nbasis<<" " << _nbasis<<std::endl;
assert(nbasis==_nbasis);
BLAS_F.resize (fine_vol * words * nrhs );
BLAS_C.resize (coarse_vol * nbasis * nrhs );
/////////////////////////////////////////////
// Copy in the multi-rhs sources to same data layout
/////////////////////////////////////////////
// std::cout << "BlockProject import fine"<<std::endl;
ImportFineGridVectors(fine,BLAS_F);
deviceVector<scalar *> Vd(coarse_vol);
deviceVector<scalar *> Fd(coarse_vol);
deviceVector<scalar *> Cd(coarse_vol);
// std::cout << "BlockProject pointers"<<std::endl;
for(int c=0;c<coarse_vol;c++){
// BLAS_V[coarse_vol][nbasis][block_vol][words]
// BLAS_F[coarse_vol][nrhs][block_vol][words]
// BLAS_C[coarse_vol][nrhs][nbasis]
scalar * Vh = & BLAS_V[c*nbasis*block_vol*words];
scalar * Fh = & BLAS_F[c*nrhs*block_vol*words];
scalar * Ch = & BLAS_C[c*nrhs*nbasis];
acceleratorPut(Vd[c],Vh);
acceleratorPut(Fd[c],Fh);
acceleratorPut(Cd[c],Ch);
}
GridBLAS BLAS;
// std::cout << "BlockProject BLAS"<<std::endl;
int64_t vw = block_vol * words;
/////////////////////////////////////////
// C_br = V^dag R
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_C,GridBLAS_OP_N,
nbasis,nrhs,vw,
scalar(1.0),
Vd,
Fd,
scalar(0.0), // wipe out C
Cd);
BLAS.synchronise();
// std::cout << "BlockProject done"<<std::endl;
ExportCoarseGridVectors(coarse, BLAS_C);
// std::cout << "BlockProject done"<<std::endl;
}
template<class cobj>
void blockPromote(std::vector<Field> &fine,std::vector<Lattice<cobj> > & coarse)
{
int nrhs=fine.size();
int _nbasis = sizeof(typename cobj::scalar_object)/sizeof(scalar);
assert(nbasis==_nbasis);
BLAS_F.resize (fine_vol * words * nrhs );
BLAS_C.resize (coarse_vol * nbasis * nrhs );
ImportCoarseGridVectors(coarse, BLAS_C);
GridBLAS BLAS;
deviceVector<scalar *> Vd(coarse_vol);
deviceVector<scalar *> Fd(coarse_vol);
deviceVector<scalar *> Cd(coarse_vol);
for(int c=0;c<coarse_vol;c++){
// BLAS_V[coarse_vol][nbasis][block_vol][words]
// BLAS_F[coarse_vol][nrhs][block_vol][words]
// BLAS_C[coarse_vol][nrhs][nbasis]
scalar * Vh = & BLAS_V[c*nbasis*block_vol*words];
scalar * Fh = & BLAS_F[c*nrhs*block_vol*words];
scalar * Ch = & BLAS_C[c*nrhs*nbasis];
acceleratorPut(Vd[c],Vh);
acceleratorPut(Fd[c],Fh);
acceleratorPut(Cd[c],Ch);
}
/////////////////////////////////////////
// Block promote:
// F_xr = Vxb Cbr (x coarse_vol)
/////////////////////////////////////////
int64_t vw = block_vol * words;
BLAS.gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
vw,nrhs,nbasis,
scalar(1.0),
Vd,
Cd,
scalar(0.0), // wipe out C
Fd);
BLAS.synchronise();
// std::cout << " blas call done"<<std::endl;
ExportFineGridVectors(fine, BLAS_F);
// std::cout << " exported "<<std::endl;
}
};
NAMESPACE_END(Grid);
@@ -1,233 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: MultiRHSDeflation.h
Copyright (C) 2023
Author: Peter Boyle <pboyle@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
/* Need helper object for BLAS accelerated mrhs projection
i) MultiRHS Deflation
Import Evecs -> nev x vol x internal
Import vector of Lattice objects -> nrhs x vol x internal
=> Cij (nrhs x Nev) via GEMM.
=> Guess (nrhs x vol x internal) = C x evecs (via GEMM)
Export
ii) MultiRHS block projection
Import basis -> nblock x nbasis x (block x internal)
Import vector of fine lattice objects -> nblock x nrhs x (block x internal)
=> coarse_(nrhs x nbasis )^block = via batched GEMM
iii) Alternate interface:
Import higher dim Lattice object-> vol x nrhs layout
*/
template<class Field>
class MultiRHSDeflation
{
public:
typedef typename Field::scalar_type scalar;
typedef typename Field::scalar_object scalar_object;
int nev;
std::vector<RealD> eval;
GridBase *grid;
uint64_t vol;
uint64_t words;
deviceVector<scalar> BLAS_E; // nev x vol -- the eigenbasis (up to a 1/sqrt(lambda))
deviceVector<scalar> BLAS_R; // nrhs x vol -- the sources
deviceVector<scalar> BLAS_G; // nrhs x vol -- the guess
deviceVector<scalar> BLAS_C; // nrhs x nev -- the coefficients
MultiRHSDeflation(){};
~MultiRHSDeflation(){ Deallocate(); };
void Deallocate(void)
{
nev=0;
grid=nullptr;
vol=0;
words=0;
BLAS_E.resize(0);
BLAS_R.resize(0);
BLAS_C.resize(0);
BLAS_G.resize(0);
}
void Allocate(int _nev,GridBase *_grid)
{
nev=_nev;
grid=_grid;
vol = grid->lSites();
words = sizeof(scalar_object)/sizeof(scalar);
eval.resize(nev);
BLAS_E.resize (vol * words * nev );
std::cout << GridLogMessage << " Allocate for "<<nev<<" eigenvectors and volume "<<vol<<std::endl;
}
void ImportEigenVector(Field &evec,RealD &_eval, int ev)
{
// std::cout << " ev " <<ev<<" eval "<<_eval<< std::endl;
assert(ev<eval.size());
eval[ev] = _eval;
int64_t offset = ev*vol*words;
autoView(v,evec,AcceleratorRead);
acceleratorCopyDeviceToDevice(&v[0],&BLAS_E[offset],sizeof(scalar_object)*vol);
}
void ImportEigenBasis(std::vector<Field> &evec,std::vector<RealD> &_eval)
{
ImportEigenBasis(evec,_eval,0,evec.size());
}
// Could use to import a batch of eigenvectors
void ImportEigenBasis(std::vector<Field> &evec,std::vector<RealD> &_eval, int _ev0, int _nev)
{
assert(_ev0+_nev<=evec.size());
Allocate(_nev,evec[0].Grid());
// Imports a sub-batch of eigenvectors, _ev0, ..., _ev0+_nev-1
for(int e=0;e<nev;e++){
std::cout << "Importing eigenvector "<<e<<" evalue "<<_eval[_ev0+e]<<std::endl;
ImportEigenVector(evec[_ev0+e],_eval[_ev0+e],e);
}
}
void DeflateSources(std::vector<Field> &source,std::vector<Field> & guess)
{
int nrhs = source.size();
assert(source.size()==guess.size());
assert(grid == guess[0].Grid());
conformable(guess[0],source[0]);
int64_t vw = vol * words;
RealD t0 = usecond();
BLAS_R.resize(nrhs * vw); // cost free if size doesn't change
BLAS_G.resize(nrhs * vw); // cost free if size doesn't change
BLAS_C.resize(nev * nrhs);// cost free if size doesn't change
/////////////////////////////////////////////
// Copy in the multi-rhs sources
/////////////////////////////////////////////
// for(int r=0;r<nrhs;r++){
// std::cout << " source["<<r<<"] = "<<norm2(source[r])<<std::endl;
// }
for(int r=0;r<nrhs;r++){
int64_t offset = r*vw;
autoView(v,source[r],AcceleratorRead);
acceleratorCopyDeviceToDevice(&v[0],&BLAS_R[offset],sizeof(scalar_object)*vol);
}
/*
* in Fortran column major notation (cuBlas order)
*
* Exe = [e1(x)][..][en(x)]
*
* Rxr = [r1(x)][..][rm(x)]
*
* C_er = E^dag R
* C_er = C_er / lambda_e
* G_xr = Exe Cer
*/
deviceVector<scalar *> Ed(1);
deviceVector<scalar *> Rd(1);
deviceVector<scalar *> Cd(1);
deviceVector<scalar *> Gd(1);
scalar * Eh = & BLAS_E[0];
scalar * Rh = & BLAS_R[0];
scalar * Ch = & BLAS_C[0];
scalar * Gh = & BLAS_G[0];
acceleratorPut(Ed[0],Eh);
acceleratorPut(Rd[0],Rh);
acceleratorPut(Cd[0],Ch);
acceleratorPut(Gd[0],Gh);
GridBLAS BLAS;
/////////////////////////////////////////
// C_er = E^dag R
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_C,GridBLAS_OP_N,
nev,nrhs,vw,
scalar(1.0),
Ed,
Rd,
scalar(0.0), // wipe out C
Cd);
BLAS.synchronise();
assert(BLAS_C.size()==nev*nrhs);
std::vector<scalar> HOST_C(BLAS_C.size()); // nrhs . nev -- the coefficients
acceleratorCopyFromDevice(&BLAS_C[0],&HOST_C[0],BLAS_C.size()*sizeof(scalar));
grid->GlobalSumVector(&HOST_C[0],nev*nrhs);
for(int e=0;e<nev;e++){
RealD lam(1.0/eval[e]);
for(int r=0;r<nrhs;r++){
int off = e+nev*r;
HOST_C[off]=HOST_C[off] * lam;
// std::cout << "C["<<e<<"]["<<r<<"] ="<<HOST_C[off]<< " eval[e] "<<eval[e] <<std::endl;
}
}
acceleratorCopyToDevice(&HOST_C[0],&BLAS_C[0],BLAS_C.size()*sizeof(scalar));
/////////////////////////////////////////
// Guess G_xr = Exe Cer
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
vw,nrhs,nev,
scalar(1.0),
Ed, // x . nev
Cd, // nev . nrhs
scalar(0.0),
Gd);
BLAS.synchronise();
///////////////////////////////////////
// Copy out the multirhs
///////////////////////////////////////
for(int r=0;r<nrhs;r++){
int64_t offset = r*vw;
autoView(v,guess[r],AcceleratorWrite);
acceleratorCopyDeviceToDevice(&BLAS_G[offset],&v[0],sizeof(scalar_object)*vol);
}
RealD t1 = usecond();
std::cout << GridLogMessage << "MultiRHSDeflation for "<<nrhs<<" sources with "<<nev<<" eigenvectors took " << (t1-t0)/1e3 <<" ms"<<std::endl;
}
};
NAMESPACE_END(Grid);
-599
View File
@@ -1,599 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/AdefGeneric.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_ALGORITHMS_ITERATIVE_GENERIC_PCG
#define GRID_ALGORITHMS_ITERATIVE_GENERIC_PCG
/*
* Compared to Tang-2009: P=Pleft. P^T = PRight Q=MssInv.
* Script A = SolverMatrix
* Script P = Preconditioner
*
* Implement ADEF-2
*
* Vstart = P^Tx + Qb
* M1 = P^TM + Q
* M2=M3=1
*/
NAMESPACE_BEGIN(Grid);
template<class Field>
class TwoLevelCG : public LinearFunction<Field>
{
public:
RealD Tolerance;
Integer MaxIterations;
GridBase *grid;
// Fine operator, Smoother, CoarseSolver
LinearOperatorBase<Field> &_FineLinop;
LinearFunction<Field> &_Smoother;
// more most opertor functions
TwoLevelCG(RealD tol,
Integer maxit,
LinearOperatorBase<Field> &FineLinop,
LinearFunction<Field> &Smoother,
GridBase *fine) :
Tolerance(tol),
MaxIterations(maxit),
_FineLinop(FineLinop),
_Smoother(Smoother)
{
grid = fine;
};
virtual void operator() (const Field &src, Field &x)
{
std::cout << GridLogMessage<<"HDCG: fPcg starting single RHS"<<std::endl;
RealD f;
RealD rtzp,rtz,a,d,b;
RealD rptzp;
/////////////////////////////
// Set up history vectors
/////////////////////////////
int mmax = 5;
std::cout << GridLogMessage<<"HDCG: fPcg allocating"<<std::endl;
std::vector<Field> p(mmax,grid);
std::vector<Field> mmp(mmax,grid);
std::vector<RealD> pAp(mmax);
Field z(grid);
Field tmp(grid);
Field mp (grid);
Field r (grid);
Field mu (grid);
std::cout << GridLogMessage<<"HDCG: fPcg allocated"<<std::endl;
//Initial residual computation & set up
RealD guess = norm2(x);
std::cout << GridLogMessage<<"HDCG: fPcg guess nrm "<<guess<<std::endl;
RealD src_nrm = norm2(src);
std::cout << GridLogMessage<<"HDCG: fPcg src nrm "<<src_nrm<<std::endl;
if ( src_nrm == 0.0 ) {
std::cout << GridLogMessage<<"HDCG: fPcg given trivial source norm "<<src_nrm<<std::endl;
x=Zero();
}
RealD tn;
GridStopWatch HDCGTimer;
HDCGTimer.Start();
//////////////////////////
// x0 = Vstart -- possibly modify guess
//////////////////////////
Vstart(x,src);
// r0 = b -A x0
_FineLinop.HermOp(x,mmp[0]);
axpy (r, -1.0,mmp[0], src); // Recomputes r=src-Ax0
{
double n1 = norm2(x);
double n2 = norm2(mmp[0]);
double n3 = norm2(r);
std::cout<<GridLogMessage<<"x,vstart,r = "<<n1<<" "<<n2<<" "<<n3<<std::endl;
}
//////////////////////////////////
// Compute z = M1 x
//////////////////////////////////
PcgM1(r,z);
rtzp =real(innerProduct(r,z));
///////////////////////////////////////
// Solve for Mss mu = P A z and set p = z-mu
// Def2 p = 1 - Q Az = Pright z
// Other algos M2 is trivial
///////////////////////////////////////
PcgM2(z,p[0]);
RealD ssq = norm2(src);
RealD rsq = ssq*Tolerance*Tolerance;
std::cout << GridLogMessage<<"HDCG: k=0 residual "<<rtzp<<" rsq "<<rsq<<"\n";
Field pp(grid);
for (int k=0;k<=MaxIterations;k++){
int peri_k = k % mmax;
int peri_kp = (k+1) % mmax;
rtz=rtzp;
d= PcgM3(p[peri_k],mmp[peri_k]);
a = rtz/d;
// Memorise this
pAp[peri_k] = d;
axpy(x,a,p[peri_k],x);
RealD rn = axpy_norm(r,-a,mmp[peri_k],r);
// Compute z = M x
PcgM1(r,z);
{
RealD n1,n2;
n1=norm2(r);
n2=norm2(z);
std::cout << GridLogMessage<<"HDCG::fPcg iteration "<<k<<" : vector r,z "<<n1<<" "<<n2<<"\n";
}
rtzp =real(innerProduct(r,z));
std::cout << GridLogMessage<<"HDCG::fPcg iteration "<<k<<" : inner rtzp "<<rtzp<<"\n";
// PcgM2(z,p[0]);
PcgM2(z,mu); // ADEF-2 this is identity. Axpy possible to eliminate
p[peri_kp]=mu;
// Standard search direction p -> z + b p
b = (rtzp)/rtz;
int northog;
// k=zero <=> peri_kp=1; northog = 1
// k=1 <=> peri_kp=2; northog = 2
// ... ... ...
// k=mmax-2<=> peri_kp=mmax-1; northog = mmax-1
// k=mmax-1<=> peri_kp=0; northog = 1
// northog = (peri_kp==0)?1:peri_kp; // This is the fCG(mmax) algorithm
northog = (k>mmax-1)?(mmax-1):k; // This is the fCG-Tr(mmax-1) algorithm
std::cout<<GridLogMessage<<"HDCG::fPcg iteration "<<k<<" : orthogonalising to last "<<northog<<" vectors\n";
for(int back=0; back < northog; back++){
int peri_back = (k-back)%mmax;
RealD pbApk= real(innerProduct(mmp[peri_back],p[peri_kp]));
RealD beta = -pbApk/pAp[peri_back];
axpy(p[peri_kp],beta,p[peri_back],p[peri_kp]);
}
RealD rrn=sqrt(rn/ssq);
RealD rtn=sqrt(rtz/ssq);
RealD rtnp=sqrt(rtzp/ssq);
std::cout<<GridLogMessage<<"HDCG: fPcg k= "<<k<<" residual = "<<rrn<<"\n";
// Stopping condition
if ( rn <= rsq ) {
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: fPcg converged in "<<k<<" iterations and "<<HDCGTimer.Elapsed()<<std::endl;;
_FineLinop.HermOp(x,mmp[0]);
axpy(tmp,-1.0,src,mmp[0]);
RealD mmpnorm = sqrt(norm2(mmp[0]));
RealD xnorm = sqrt(norm2(x));
RealD srcnorm = sqrt(norm2(src));
RealD tmpnorm = sqrt(norm2(tmp));
RealD true_residual = tmpnorm/srcnorm;
std::cout<<GridLogMessage
<<"HDCG: true residual is "<<true_residual
<<" solution "<<xnorm
<<" source "<<srcnorm
<<" mmp "<<mmpnorm
<<std::endl;
return;
}
}
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: not converged "<<HDCGTimer.Elapsed()<<std::endl;
RealD xnorm = sqrt(norm2(x));
RealD srcnorm = sqrt(norm2(src));
std::cout<<GridLogMessage<<"HDCG: non-converged solution "<<xnorm<<" source "<<srcnorm<<std::endl;
}
virtual void operator() (std::vector<Field> &src, std::vector<Field> &x)
{
std::cout << GridLogMessage<<"HDCG: mrhs fPcg starting"<<std::endl;
src[0].Grid()->Barrier();
int nrhs = src.size();
std::vector<RealD> f(nrhs);
std::vector<RealD> rtzp(nrhs);
std::vector<RealD> rtz(nrhs);
std::vector<RealD> a(nrhs);
std::vector<RealD> d(nrhs);
std::vector<RealD> b(nrhs);
std::vector<RealD> rptzp(nrhs);
/////////////////////////////
// Set up history vectors
/////////////////////////////
int mmax = 3;
std::cout << GridLogMessage<<"HDCG: fPcg allocating"<<std::endl;
src[0].Grid()->Barrier();
std::vector<std::vector<Field> > p(nrhs); for(int r=0;r<nrhs;r++) p[r].resize(mmax,grid);
std::cout << GridLogMessage<<"HDCG: fPcg allocated p"<<std::endl;
src[0].Grid()->Barrier();
std::vector<std::vector<Field> > mmp(nrhs); for(int r=0;r<nrhs;r++) mmp[r].resize(mmax,grid);
std::cout << GridLogMessage<<"HDCG: fPcg allocated mmp"<<std::endl;
src[0].Grid()->Barrier();
std::vector<std::vector<RealD> > pAp(nrhs); for(int r=0;r<nrhs;r++) pAp[r].resize(mmax);
std::cout << GridLogMessage<<"HDCG: fPcg allocated pAp"<<std::endl;
src[0].Grid()->Barrier();
std::vector<Field> z(nrhs,grid);
std::vector<Field> mp (nrhs,grid);
std::vector<Field> r (nrhs,grid);
std::vector<Field> mu (nrhs,grid);
std::cout << GridLogMessage<<"HDCG: fPcg allocated z,mp,r,mu"<<std::endl;
src[0].Grid()->Barrier();
//Initial residual computation & set up
std::vector<RealD> src_nrm(nrhs);
for(int rhs=0;rhs<nrhs;rhs++) {
src_nrm[rhs]=norm2(src[rhs]);
assert(src_nrm[rhs]!=0.0);
}
std::vector<RealD> tn(nrhs);
GridStopWatch HDCGTimer;
HDCGTimer.Start();
//////////////////////////
// x0 = Vstart -- possibly modify guess
//////////////////////////
Vstart(x,src);
for(int rhs=0;rhs<nrhs;rhs++){
// r0 = b -A x0
_FineLinop.HermOp(x[rhs],mmp[rhs][0]);
axpy (r[rhs], -1.0,mmp[rhs][0], src[rhs]); // Recomputes r=src-Ax0
}
//////////////////////////////////
// Compute z = M1 x
//////////////////////////////////
// This needs a multiRHS version for acceleration
PcgM1(r,z);
std::vector<RealD> ssq(nrhs);
std::vector<RealD> rsq(nrhs);
std::vector<Field> pp(nrhs,grid);
for(int rhs=0;rhs<nrhs;rhs++){
rtzp[rhs] =real(innerProduct(r[rhs],z[rhs]));
p[rhs][0]=z[rhs];
ssq[rhs]=norm2(src[rhs]);
rsq[rhs]= ssq[rhs]*Tolerance*Tolerance;
std::cout << GridLogMessage<<"mrhs HDCG: "<<rhs<<" k=0 residual "<<rtzp[rhs]<<" rsq "<<rsq[rhs]<<"\n";
}
std::vector<RealD> rn(nrhs);
for (int k=0;k<=MaxIterations;k++){
int peri_k = k % mmax;
int peri_kp = (k+1) % mmax;
for(int rhs=0;rhs<nrhs;rhs++){
rtz[rhs]=rtzp[rhs];
d[rhs]= PcgM3(p[rhs][peri_k],mmp[rhs][peri_k]);
a[rhs] = rtz[rhs]/d[rhs];
// Memorise this
pAp[rhs][peri_k] = d[rhs];
axpy(x[rhs],a[rhs],p[rhs][peri_k],x[rhs]);
rn[rhs] = axpy_norm(r[rhs],-a[rhs],mmp[rhs][peri_k],r[rhs]);
}
// Compute z = M x (for *all* RHS)
PcgM1(r,z);
std::cout << GridLogMessage<<"HDCG::fPcg M1 complete"<<std::endl;
grid->Barrier();
RealD max_rn=0.0;
for(int rhs=0;rhs<nrhs;rhs++){
rtzp[rhs] =real(innerProduct(r[rhs],z[rhs]));
std::cout << GridLogMessage<<"HDCG::fPcg rhs"<<rhs<<" iteration "<<k<<" : inner rtzp "<<rtzp[rhs]<<"\n";
mu[rhs]=z[rhs];
p[rhs][peri_kp]=mu[rhs];
// Standard search direction p == z + b p
b[rhs] = (rtzp[rhs])/rtz[rhs];
int northog = (k>mmax-1)?(mmax-1):k; // This is the fCG-Tr(mmax-1) algorithm
std::cout<<GridLogMessage<<"HDCG::fPcg iteration "<<k<<" : orthogonalising to last "<<northog<<" vectors\n";
for(int back=0; back < northog; back++){
int peri_back = (k-back)%mmax;
RealD pbApk= real(innerProduct(mmp[rhs][peri_back],p[rhs][peri_kp]));
RealD beta = -pbApk/pAp[rhs][peri_back];
axpy(p[rhs][peri_kp],beta,p[rhs][peri_back],p[rhs][peri_kp]);
}
RealD rrn=sqrt(rn[rhs]/ssq[rhs]);
RealD rtn=sqrt(rtz[rhs]/ssq[rhs]);
RealD rtnp=sqrt(rtzp[rhs]/ssq[rhs]);
std::cout<<GridLogMessage<<"HDCG: rhs "<<rhs<<"fPcg k= "<<k<<" residual = "<<rrn<<"\n";
if ( rrn > max_rn ) max_rn = rrn;
}
// Stopping condition based on worst case
if ( max_rn <= Tolerance ) {
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg converged in "<<k<<" iterations and "<<HDCGTimer.Elapsed()<<std::endl;;
for(int rhs=0;rhs<nrhs;rhs++){
_FineLinop.HermOp(x[rhs],mmp[rhs][0]);
Field tmp(grid);
axpy(tmp,-1.0,src[rhs],mmp[rhs][0]);
RealD mmpnorm = sqrt(norm2(mmp[rhs][0]));
RealD xnorm = sqrt(norm2(x[rhs]));
RealD srcnorm = sqrt(norm2(src[rhs]));
RealD tmpnorm = sqrt(norm2(tmp));
RealD true_residual = tmpnorm/srcnorm;
std::cout<<GridLogMessage
<<"HDCG: true residual ["<<rhs<<"] is "<<true_residual
<<" solution "<<xnorm
<<" source "<<srcnorm
<<" mmp "<<mmpnorm
<<std::endl;
}
return;
}
}
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: not converged "<<HDCGTimer.Elapsed()<<std::endl;
for(int rhs=0;rhs<nrhs;rhs++){
RealD xnorm = sqrt(norm2(x[rhs]));
RealD srcnorm = sqrt(norm2(src[rhs]));
std::cout<<GridLogMessage<<"HDCG: non-converged solution "<<xnorm<<" source "<<srcnorm<<std::endl;
}
}
public:
virtual void PcgM1(std::vector<Field> & in,std::vector<Field> & out)
{
std::cout << "PcgM1 default (cheat) mrhs version"<<std::endl;
for(int rhs=0;rhs<in.size();rhs++){
this->PcgM1(in[rhs],out[rhs]);
}
}
virtual void PcgM1(Field & in, Field & out) =0;
virtual void Vstart(std::vector<Field> & x,std::vector<Field> & src)
{
std::cout << "Vstart default (cheat) mrhs version"<<std::endl;
for(int rhs=0;rhs<x.size();rhs++){
this->Vstart(x[rhs],src[rhs]);
}
}
virtual void Vstart(Field & x,const Field & src)=0;
virtual void PcgM2(const Field & in, Field & out) {
out=in;
}
virtual RealD PcgM3(const Field & p, Field & mmp){
RealD dd;
_FineLinop.HermOp(p,mmp);
ComplexD dot = innerProduct(p,mmp);
dd=real(dot);
return dd;
}
/////////////////////////////////////////////////////////////////////
// Only Def1 has non-trivial Vout.
/////////////////////////////////////////////////////////////////////
};
template<class Field, class CoarseField, class Aggregation>
class TwoLevelADEF2 : public TwoLevelCG<Field>
{
public:
///////////////////////////////////////////////////////////////////////////////////
// Need something that knows how to get from Coarse to fine and back again
// void ProjectToSubspace(CoarseVector &CoarseVec,const FineField &FineVec){
// void PromoteFromSubspace(const CoarseVector &CoarseVec,FineField &FineVec){
///////////////////////////////////////////////////////////////////////////////////
GridBase *coarsegrid;
Aggregation &_Aggregates;
LinearFunction<CoarseField> &_CoarseSolver;
LinearFunction<CoarseField> &_CoarseSolverPrecise;
///////////////////////////////////////////////////////////////////////////////////
// more most opertor functions
TwoLevelADEF2(RealD tol,
Integer maxit,
LinearOperatorBase<Field> &FineLinop,
LinearFunction<Field> &Smoother,
LinearFunction<CoarseField> &CoarseSolver,
LinearFunction<CoarseField> &CoarseSolverPrecise,
Aggregation &Aggregates
) :
TwoLevelCG<Field>(tol,maxit,FineLinop,Smoother,Aggregates.FineGrid),
_CoarseSolver(CoarseSolver),
_CoarseSolverPrecise(CoarseSolverPrecise),
_Aggregates(Aggregates)
{
coarsegrid = Aggregates.CoarseGrid;
};
virtual void PcgM1(Field & in, Field & out)
{
GRID_TRACE("MultiGridPreconditioner ");
// [PTM+Q] in = [1 - Q A] M in + Q in = Min + Q [ in -A Min]
Field tmp(this->grid);
Field Min(this->grid);
CoarseField PleftProj(this->coarsegrid);
CoarseField PleftMss_proj(this->coarsegrid);
GridStopWatch SmootherTimer;
GridStopWatch MatrixTimer;
SmootherTimer.Start();
this->_Smoother(in,Min);
SmootherTimer.Stop();
MatrixTimer.Start();
this->_FineLinop.HermOp(Min,out);
MatrixTimer.Stop();
axpy(tmp,-1.0,out,in); // tmp = in - A Min
GridStopWatch ProjTimer;
GridStopWatch CoarseTimer;
GridStopWatch PromTimer;
ProjTimer.Start();
this->_Aggregates.ProjectToSubspace(PleftProj,tmp);
ProjTimer.Stop();
CoarseTimer.Start();
this->_CoarseSolver(PleftProj,PleftMss_proj); // Ass^{-1} [in - A Min]_s
CoarseTimer.Stop();
PromTimer.Start();
this->_Aggregates.PromoteFromSubspace(PleftMss_proj,tmp);// tmp = Q[in - A Min]
PromTimer.Stop();
std::cout << GridLogPerformance << "PcgM1 breakdown "<<std::endl;
std::cout << GridLogPerformance << "\tSmoother " << SmootherTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "\tProj " << ProjTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "\tCoarse " << CoarseTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "\tProm " << PromTimer.Elapsed() <<std::endl;
axpy(out,1.0,Min,tmp); // Min+tmp
}
virtual void Vstart(Field & x,const Field & src)
{
std::cout << GridLogMessage<<"HDCG: fPcg Vstart "<<std::endl;
///////////////////////////////////
// Choose x_0 such that
// x_0 = guess + (A_ss^inv) r_s = guess + Ass_inv [src -Aguess]
// = [1 - Ass_inv A] Guess + Assinv src
// = P^T guess + Assinv src
// = Vstart [Tang notation]
// This gives:
// W^T (src - A x_0) = src_s - A guess_s - r_s
// = src_s - (A guess)_s - src_s + (A guess)_s
// = 0
///////////////////////////////////
Field r(this->grid);
Field mmp(this->grid);
CoarseField PleftProj(this->coarsegrid);
CoarseField PleftMss_proj(this->coarsegrid);
std::cout << GridLogMessage<<"HDCG: fPcg Vstart projecting "<<std::endl;
this->_Aggregates.ProjectToSubspace(PleftProj,src);
std::cout << GridLogMessage<<"HDCG: fPcg Vstart coarse solve "<<std::endl;
this->_CoarseSolverPrecise(PleftProj,PleftMss_proj); // Ass^{-1} r_s
std::cout << GridLogMessage<<"HDCG: fPcg Vstart promote "<<std::endl;
this->_Aggregates.PromoteFromSubspace(PleftMss_proj,x);
}
};
template<class Field>
class TwoLevelADEF1defl : public TwoLevelCG<Field>
{
public:
const std::vector<Field> &evec;
const std::vector<RealD> &eval;
TwoLevelADEF1defl(RealD tol,
Integer maxit,
LinearOperatorBase<Field> &FineLinop,
LinearFunction<Field> &Smoother,
std::vector<Field> &_evec,
std::vector<RealD> &_eval) :
TwoLevelCG<Field>(tol,maxit,FineLinop,Smoother,_evec[0].Grid()),
evec(_evec),
eval(_eval)
{};
// Can just inherit existing M2
// Can just inherit existing M3
// Simple vstart - do nothing
virtual void Vstart(Field & x,const Field & src){
x=src; // Could apply Q
};
// Override PcgM1
virtual void PcgM1(Field & in, Field & out)
{
GRID_TRACE("EvecPreconditioner ");
int N=evec.size();
Field Pin(this->grid);
Field Qin(this->grid);
//MP + Q = M(1-AQ) + Q = M
// // If we are eigenvector deflating in coarse space
// // Q = Sum_i |phi_i> 1/lambda_i <phi_i|
// // A Q = Sum_i |phi_i> <phi_i|
// // M(1-AQ) = M(1-proj) + Q
Qin.Checkerboard()=in.Checkerboard();
Qin = Zero();
Pin = in;
for (int i=0;i<N;i++) {
const Field& tmp = evec[i];
auto ip = TensorRemove(innerProduct(tmp,in));
axpy(Qin, ip / eval[i],tmp,Qin);
axpy(Pin, -ip ,tmp,Pin);
}
this->_Smoother(Pin,out);
out = out + Qin;
}
};
NAMESPACE_END(Grid);
#endif
-734
View File
@@ -1,734 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/AdefGeneric.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
/*
* Compared to Tang-2009: P=Pleft. P^T = PRight Q=MssInv.
* Script A = SolverMatrix
* Script P = Preconditioner
*
* Implement ADEF-2
*
* Vstart = P^Tx + Qb
* M1 = P^TM + Q
* M2=M3=1
*/
NAMESPACE_BEGIN(Grid);
template<class Field>
class TwoLevelCGmrhs
{
public:
RealD Tolerance;
Integer MaxIterations;
GridBase *grid;
// Fine operator, Smoother, CoarseSolver
LinearOperatorBase<Field> &_FineLinop;
LinearFunction<Field> &_Smoother;
MultiRHSBlockCGLinalg<Field> _BlockCGLinalg;
GridStopWatch ProjectTimer;
GridStopWatch PromoteTimer;
GridStopWatch DeflateTimer;
GridStopWatch CoarseTimer;
GridStopWatch FineTimer;
GridStopWatch SmoothTimer;
GridStopWatch InsertTimer;
/*
Field rrr;
Field sss;
Field qqq;
Field zzz;
*/
// more most opertor functions
TwoLevelCGmrhs(RealD tol,
Integer maxit,
LinearOperatorBase<Field> &FineLinop,
LinearFunction<Field> &Smoother,
GridBase *fine) :
Tolerance(tol),
MaxIterations(maxit),
_FineLinop(FineLinop),
_Smoother(Smoother)
/*
rrr(fine),
sss(fine),
qqq(fine),
zzz(fine)
*/
{
grid = fine;
};
// Vector case
virtual void operator() (std::vector<Field> &src, std::vector<Field> &x)
{
// SolveSingleSystem(src,x);
SolvePrecBlockCG(src,x);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
// Thin QR factorisation (google it)
////////////////////////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
//Dimensions
// R_{ferm x Nblock} = Q_{ferm x Nblock} x C_{Nblock x Nblock} -> ferm x Nblock
//
// Rdag R = m_rr = Herm = L L^dag <-- Cholesky decomposition (LLT routine in Eigen)
//
// Q C = R => Q = R C^{-1}
//
// Want Ident = Q^dag Q = C^{-dag} R^dag R C^{-1} = C^{-dag} L L^dag C^{-1} = 1_{Nblock x Nblock}
//
// Set C = L^{dag}, and then Q^dag Q = ident
//
// Checks:
// Cdag C = Rdag R ; passes.
// QdagQ = 1 ; passes
////////////////////////////////////////////////////////////////////////////////////////////////////
void ThinQRfact (Eigen::MatrixXcd &m_zz,
Eigen::MatrixXcd &C,
Eigen::MatrixXcd &Cinv,
std::vector<Field> & Q,
std::vector<Field> & MQ,
const std::vector<Field> & Z,
const std::vector<Field> & MZ)
{
RealD t0=usecond();
_BlockCGLinalg.InnerProductMatrix(m_zz,MZ,Z);
RealD t1=usecond();
m_zz = 0.5*(m_zz+m_zz.adjoint());
Eigen::MatrixXcd L = m_zz.llt().matrixL();
C = L.adjoint();
Cinv = C.inverse();
RealD t3=usecond();
_BlockCGLinalg.MulMatrix( Q,Cinv,Z);
_BlockCGLinalg.MulMatrix(MQ,Cinv,MZ);
RealD t4=usecond();
std::cout << " ThinQRfact IP :"<< t1-t0<<" us"<<std::endl;
std::cout << " ThinQRfact Eigen :"<< t3-t1<<" us"<<std::endl;
std::cout << " ThinQRfact MulMat:"<< t4-t3<<" us"<<std::endl;
}
virtual void SolvePrecBlockCG (std::vector<Field> &src, std::vector<Field> &X)
{
std::cout << GridLogMessage<<"HDCG: mrhs fPrecBlockcg starting"<<std::endl;
src[0].Grid()->Barrier();
int nrhs = src.size();
// std::vector<RealD> f(nrhs);
// std::vector<RealD> rtzp(nrhs);
// std::vector<RealD> rtz(nrhs);
// std::vector<RealD> a(nrhs);
// std::vector<RealD> d(nrhs);
// std::vector<RealD> b(nrhs);
// std::vector<RealD> rptzp(nrhs);
////////////////////////////////////////////
//Initial residual computation & set up
////////////////////////////////////////////
std::vector<RealD> ssq(nrhs);
for(int rhs=0;rhs<nrhs;rhs++){
ssq[rhs]=norm2(src[rhs]); assert(ssq[rhs]!=0.0);
}
///////////////////////////
// Fields -- eliminate duplicates between fPcg and block cg
///////////////////////////
std::vector<Field> Mtmp(nrhs,grid);
std::vector<Field> tmp(nrhs,grid);
std::vector<Field> Z(nrhs,grid); // Rename Z to R
std::vector<Field> MZ(nrhs,grid); // Rename MZ to Z
std::vector<Field> Q(nrhs,grid); //
std::vector<Field> MQ(nrhs,grid); // Rename to P
std::vector<Field> D(nrhs,grid);
std::vector<Field> AD(nrhs,grid);
/************************************************************************
* Preconditioned Block conjugate gradient rQ
* Generalise Sebastien Birk Thesis, after Dubrulle 2001.
* Introduce preconditioning following Saad Ch9
************************************************************************
* Dimensions:
*
* X,B etc... ==(Nferm x nrhs)
* Matrix A==(Nferm x Nferm)
*
* Nferm = Nspin x Ncolour x Ncomplex x Nlattice_site
* QC => Thin QR factorisation (google it)
*
* R = B-AX
* Z = Mi R
* QC = Z
* D = Q
* for k:
* R = AD
* Z = Mi R
* M = [D^dag R]^{-1}
* X = X + D M C
* QS = Q - Z.M
* D = Q + D S^dag
* C = S C
*/
Eigen::MatrixXcd m_DZ = Eigen::MatrixXcd::Identity(nrhs,nrhs);
Eigen::MatrixXcd m_M = Eigen::MatrixXcd::Identity(nrhs,nrhs);
Eigen::MatrixXcd m_zz = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_rr = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_C = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_Cinv = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_S = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_Sinv = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_tmp = Eigen::MatrixXcd::Identity(nrhs,nrhs);
Eigen::MatrixXcd m_tmp1 = Eigen::MatrixXcd::Identity(nrhs,nrhs);
GridStopWatch HDCGTimer;
//////////////////////////
// x0 = Vstart -- possibly modify guess
//////////////////////////
Vstart(X,src);
//////////////////////////
// R = B-AX
//////////////////////////
for(int rhs=0;rhs<nrhs;rhs++){
// r0 = b -A x0
_FineLinop.HermOp(X[rhs],tmp[rhs]);
axpy (Z[rhs], -1.0,tmp[rhs], src[rhs]); // Computes R=Z=src - A X0
}
//////////////////////////////////
// Compute MZ = M1 Z = M1 B - M1 A x0
//////////////////////////////////
PcgM1(Z,MZ);
//////////////////////////////////
// QC = Z
//////////////////////////////////
ThinQRfact (m_zz, m_C, m_Cinv, Q, MQ, Z, MZ);
//////////////////////////////////
// D=MQ
//////////////////////////////////
for(int b=0;b<nrhs;b++) D[b]=MQ[b]; // LLT rotation of the MZ basis of search dirs
std::cout << GridLogMessage<<"PrecBlockCGrQ vec computed initial residual and QR fact " <<std::endl;
ProjectTimer.Reset();
PromoteTimer.Reset();
DeflateTimer.Reset();
CoarseTimer.Reset();
SmoothTimer.Reset();
FineTimer.Reset();
InsertTimer.Reset();
GridStopWatch M1Timer;
GridStopWatch M2Timer;
GridStopWatch M3Timer;
GridStopWatch LinalgTimer;
GridStopWatch InnerProdTimer;
HDCGTimer.Start();
std::vector<RealD> rn(nrhs);
for (int k=0;k<=MaxIterations;k++){
////////////////////
// Z = AD
////////////////////
M3Timer.Start();
for(int b=0;b<nrhs;b++) _FineLinop.HermOp(D[b], Z[b]);
M3Timer.Stop();
////////////////////
// MZ = M1 Z <==== the Multigrid preconditioner
////////////////////
M1Timer.Start();
PcgM1(Z,MZ);
M1Timer.Stop();
FineTimer.Start();
////////////////////
// M = [D^dag Z]^{-1} = (<Ddag MZ>_M)^{-1} inner prod, generalising Saad derivation of Precon CG
////////////////////
InnerProdTimer.Start();
_BlockCGLinalg.InnerProductMatrix(m_DZ,D,Z);
InnerProdTimer.Stop();
m_M = m_DZ.inverse();
///////////////////////////
// X = X + D MC
///////////////////////////
m_tmp = m_M * m_C;
LinalgTimer.Start();
_BlockCGLinalg.MaddMatrix(X,m_tmp, D,X); // D are the search directions and X takes the updates
LinalgTimer.Stop();
///////////////////////////
// QS = Q - M Z
// (MQ) S = MQ - M (M1Z)
///////////////////////////
LinalgTimer.Start();
_BlockCGLinalg.MaddMatrix(tmp ,m_M, Z, Q,-1.0);
_BlockCGLinalg.MaddMatrix(Mtmp,m_M,MZ,MQ,-1.0);
ThinQRfact (m_zz, m_S, m_Sinv, Q, MQ, tmp, Mtmp);
LinalgTimer.Stop();
////////////////////////////
// D = MQ + D S^dag
////////////////////////////
m_tmp = m_S.adjoint();
LinalgTimer.Start();
_BlockCGLinalg.MaddMatrix(D,m_tmp,D,MQ);
LinalgTimer.Stop();
////////////////////////////
// C = S C
////////////////////////////
m_C = m_S*m_C;
////////////////////////////
// convergence monitor
////////////////////////////
m_rr = m_C.adjoint() * m_C;
FineTimer.Stop();
RealD max_resid=0;
RealD rrsum=0;
RealD sssum=0;
RealD rr;
for(int b=0;b<nrhs;b++) {
rrsum+=real(m_rr(b,b));
sssum+=ssq[b];
rr = real(m_rr(b,b))/ssq[b];
if ( rr > max_resid ) max_resid = rr;
}
std::cout << GridLogMessage <<
"\t Prec BlockCGrQ Iteration "<<k<<" ave resid "<< std::sqrt(rrsum/sssum) << " max "<< std::sqrt(max_resid) <<std::endl;
if ( max_resid < Tolerance*Tolerance ) {
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ converged in "<<k<<" iterations and "<<HDCGTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Linalg "<<LinalgTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : fine H "<<M3Timer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : prec M1 "<<M1Timer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"**** M1 breakdown:"<<std::endl;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Project "<<ProjectTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Promote "<<PromoteTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Deflate "<<DeflateTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Coarse "<<CoarseTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Fine "<<FineTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Smooth "<<SmoothTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Insert "<<InsertTimer.Elapsed()<<std::endl;;
for(int rhs=0;rhs<nrhs;rhs++){
_FineLinop.HermOp(X[rhs],tmp[rhs]);
Field mytmp(grid);
axpy(mytmp,-1.0,src[rhs],tmp[rhs]);
RealD xnorm = sqrt(norm2(X[rhs]));
RealD srcnorm = sqrt(norm2(src[rhs]));
RealD tmpnorm = sqrt(norm2(mytmp));
RealD true_residual = tmpnorm/srcnorm;
std::cout<<GridLogMessage
<<"HDCG: true residual ["<<rhs<<"] is "<<true_residual
<<" solution "<<xnorm
<<" source "<<srcnorm
<<std::endl;
}
return;
}
}
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: PrecBlockCGrQ not converged "<<HDCGTimer.Elapsed()<<std::endl;
assert(0);
}
virtual void SolveSingleSystem (std::vector<Field> &src, std::vector<Field> &x)
{
std::cout << GridLogMessage<<"HDCG: mrhs fPcg starting"<<std::endl;
src[0].Grid()->Barrier();
int nrhs = src.size();
std::vector<RealD> f(nrhs);
std::vector<RealD> rtzp(nrhs);
std::vector<RealD> rtz(nrhs);
std::vector<RealD> a(nrhs);
std::vector<RealD> d(nrhs);
std::vector<RealD> b(nrhs);
std::vector<RealD> rptzp(nrhs);
/////////////////////////////
// Set up history vectors
/////////////////////////////
int mmax = 3;
std::vector<std::vector<Field> > p(nrhs); for(int r=0;r<nrhs;r++) p[r].resize(mmax,grid);
std::vector<std::vector<Field> > mmp(nrhs); for(int r=0;r<nrhs;r++) mmp[r].resize(mmax,grid);
std::vector<std::vector<RealD> > pAp(nrhs); for(int r=0;r<nrhs;r++) pAp[r].resize(mmax);
std::vector<Field> z(nrhs,grid);
std::vector<Field> mp (nrhs,grid);
std::vector<Field> r (nrhs,grid);
std::vector<Field> mu (nrhs,grid);
//Initial residual computation & set up
std::vector<RealD> src_nrm(nrhs);
for(int rhs=0;rhs<nrhs;rhs++) {
src_nrm[rhs]=norm2(src[rhs]);
assert(src_nrm[rhs]!=0.0);
}
std::vector<RealD> tn(nrhs);
GridStopWatch HDCGTimer;
//////////////////////////
// x0 = Vstart -- possibly modify guess
//////////////////////////
Vstart(x,src);
for(int rhs=0;rhs<nrhs;rhs++){
// r0 = b -A x0
_FineLinop.HermOp(x[rhs],mmp[rhs][0]);
axpy (r[rhs], -1.0,mmp[rhs][0], src[rhs]); // Recomputes r=src-Ax0
}
//////////////////////////////////
// Compute z = M1 x
//////////////////////////////////
// This needs a multiRHS version for acceleration
PcgM1(r,z);
std::vector<RealD> ssq(nrhs);
std::vector<RealD> rsq(nrhs);
std::vector<Field> pp(nrhs,grid);
for(int rhs=0;rhs<nrhs;rhs++){
rtzp[rhs] =real(innerProduct(r[rhs],z[rhs]));
p[rhs][0]=z[rhs];
ssq[rhs]=norm2(src[rhs]);
rsq[rhs]= ssq[rhs]*Tolerance*Tolerance;
// std::cout << GridLogMessage<<"mrhs HDCG: "<<rhs<<" k=0 residual "<<rtzp[rhs]<<" rsq "<<rsq[rhs]<<"\n";
}
ProjectTimer.Reset();
PromoteTimer.Reset();
DeflateTimer.Reset();
CoarseTimer.Reset();
SmoothTimer.Reset();
FineTimer.Reset();
InsertTimer.Reset();
GridStopWatch M1Timer;
GridStopWatch M2Timer;
GridStopWatch M3Timer;
GridStopWatch LinalgTimer;
HDCGTimer.Start();
std::vector<RealD> rn(nrhs);
for (int k=0;k<=MaxIterations;k++){
int peri_k = k % mmax;
int peri_kp = (k+1) % mmax;
for(int rhs=0;rhs<nrhs;rhs++){
rtz[rhs]=rtzp[rhs];
M3Timer.Start();
d[rhs]= PcgM3(p[rhs][peri_k],mmp[rhs][peri_k]);
M3Timer.Stop();
a[rhs] = rtz[rhs]/d[rhs];
LinalgTimer.Start();
// Memorise this
pAp[rhs][peri_k] = d[rhs];
axpy(x[rhs],a[rhs],p[rhs][peri_k],x[rhs]);
rn[rhs] = axpy_norm(r[rhs],-a[rhs],mmp[rhs][peri_k],r[rhs]);
LinalgTimer.Stop();
}
// Compute z = M x (for *all* RHS)
M1Timer.Start();
PcgM1(r,z);
M1Timer.Stop();
RealD max_rn=0.0;
LinalgTimer.Start();
for(int rhs=0;rhs<nrhs;rhs++){
rtzp[rhs] =real(innerProduct(r[rhs],z[rhs]));
// std::cout << GridLogMessage<<"HDCG::fPcg rhs"<<rhs<<" iteration "<<k<<" : inner rtzp "<<rtzp[rhs]<<"\n";
mu[rhs]=z[rhs];
p[rhs][peri_kp]=mu[rhs];
// Standard search direction p == z + b p
b[rhs] = (rtzp[rhs])/rtz[rhs];
int northog = (k>mmax-1)?(mmax-1):k; // This is the fCG-Tr(mmax-1) algorithm
for(int back=0; back < northog; back++){
int peri_back = (k-back)%mmax;
RealD pbApk= real(innerProduct(mmp[rhs][peri_back],p[rhs][peri_kp]));
RealD beta = -pbApk/pAp[rhs][peri_back];
axpy(p[rhs][peri_kp],beta,p[rhs][peri_back],p[rhs][peri_kp]);
}
RealD rrn=sqrt(rn[rhs]/ssq[rhs]);
RealD rtn=sqrt(rtz[rhs]/ssq[rhs]);
RealD rtnp=sqrt(rtzp[rhs]/ssq[rhs]);
std::cout<<GridLogMessage<<"HDCG:fPcg rhs "<<rhs<<" k= "<<k<<" residual = "<<rrn<<"\n";
if ( rrn > max_rn ) max_rn = rrn;
}
LinalgTimer.Stop();
// Stopping condition based on worst case
if ( max_rn <= Tolerance ) {
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg converged in "<<k<<" iterations and "<<HDCGTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : Linalg "<<LinalgTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : fine M3 "<<M3Timer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : prec M1 "<<M1Timer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"**** M1 breakdown:"<<std::endl;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : Project "<<ProjectTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : Promote "<<PromoteTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : Deflate "<<DeflateTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : Coarse "<<CoarseTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : Fine "<<FineTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : Smooth "<<SmoothTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : Insert "<<InsertTimer.Elapsed()<<std::endl;;
for(int rhs=0;rhs<nrhs;rhs++){
_FineLinop.HermOp(x[rhs],mmp[rhs][0]);
Field tmp(grid);
axpy(tmp,-1.0,src[rhs],mmp[rhs][0]);
RealD mmpnorm = sqrt(norm2(mmp[rhs][0]));
RealD xnorm = sqrt(norm2(x[rhs]));
RealD srcnorm = sqrt(norm2(src[rhs]));
RealD tmpnorm = sqrt(norm2(tmp));
RealD true_residual = tmpnorm/srcnorm;
std::cout<<GridLogMessage
<<"HDCG: true residual ["<<rhs<<"] is "<<true_residual
<<" solution "<<xnorm
<<" source "<<srcnorm
<<" mmp "<<mmpnorm
<<std::endl;
}
return;
}
}
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: not converged "<<HDCGTimer.Elapsed()<<std::endl;
for(int rhs=0;rhs<nrhs;rhs++){
RealD xnorm = sqrt(norm2(x[rhs]));
RealD srcnorm = sqrt(norm2(src[rhs]));
std::cout<<GridLogMessage<<"HDCG: non-converged solution "<<xnorm<<" source "<<srcnorm<<std::endl;
}
}
public:
virtual void PcgM1(std::vector<Field> & in,std::vector<Field> & out) = 0;
virtual void Vstart(std::vector<Field> & x,std::vector<Field> & src) = 0;
virtual void PcgM2(const Field & in, Field & out) {
out=in;
}
virtual RealD PcgM3(const Field & p, Field & mmp){
RealD dd;
_FineLinop.HermOp(p,mmp);
ComplexD dot = innerProduct(p,mmp);
dd=real(dot);
return dd;
}
};
template<class Field, class CoarseField>
class TwoLevelADEF2mrhs : public TwoLevelCGmrhs<Field>
{
public:
GridBase *coarsegrid;
GridBase *coarsegridmrhs;
LinearFunction<CoarseField> &_CoarseSolverMrhs;
LinearFunction<CoarseField> &_CoarseSolverPreciseMrhs;
MultiRHSBlockProject<Field> &_Projector;
MultiRHSDeflation<CoarseField> &_Deflator;
TwoLevelADEF2mrhs(RealD tol,
Integer maxit,
LinearOperatorBase<Field> &FineLinop,
LinearFunction<Field> &Smoother,
LinearFunction<CoarseField> &CoarseSolverMrhs,
LinearFunction<CoarseField> &CoarseSolverPreciseMrhs,
MultiRHSBlockProject<Field> &Projector,
MultiRHSDeflation<CoarseField> &Deflator,
GridBase *_coarsemrhsgrid) :
TwoLevelCGmrhs<Field>(tol, maxit,FineLinop,Smoother,Projector.fine_grid),
_CoarseSolverMrhs(CoarseSolverMrhs),
_CoarseSolverPreciseMrhs(CoarseSolverPreciseMrhs),
_Projector(Projector),
_Deflator(Deflator)
{
coarsegrid = Projector.coarse_grid;
coarsegridmrhs = _coarsemrhsgrid;// Thi could be in projector
};
// Override Vstart
virtual void Vstart(std::vector<Field> & x,std::vector<Field> & src)
{
int nrhs=x.size();
///////////////////////////////////
// Choose x_0 such that
// x_0 = guess + (A_ss^inv) r_s = guess + Ass_inv [src -Aguess]
// = [1 - Ass_inv A] Guess + Assinv src
// = P^T guess + Assinv src
// = Vstart [Tang notation]
// This gives:
// W^T (src - A x_0) = src_s - A guess_s - r_s
// = src_s - (A guess)_s - src_s + (A guess)_s
// = 0
///////////////////////////////////
std::vector<CoarseField> PleftProj(nrhs,this->coarsegrid);
std::vector<CoarseField> PleftMss_proj(nrhs,this->coarsegrid);
CoarseField PleftProjMrhs(this->coarsegridmrhs);
CoarseField PleftMss_projMrhs(this->coarsegridmrhs);
this->_Projector.blockProject(src,PleftProj);
this->_Deflator.DeflateSources(PleftProj,PleftMss_proj);
for(int rhs=0;rhs<nrhs;rhs++) {
InsertSliceFast(PleftProj[rhs],PleftProjMrhs,rhs,0);
InsertSliceFast(PleftMss_proj[rhs],PleftMss_projMrhs,rhs,0); // the guess
}
this->_CoarseSolverPreciseMrhs(PleftProjMrhs,PleftMss_projMrhs); // Ass^{-1} r_s
for(int rhs=0;rhs<nrhs;rhs++) {
ExtractSliceFast(PleftMss_proj[rhs],PleftMss_projMrhs,rhs,0);
}
this->_Projector.blockPromote(x,PleftMss_proj);
}
virtual void PcgM1(std::vector<Field> & in,std::vector<Field> & out){
int nrhs=in.size();
// [PTM+Q] in = [1 - Q A] M in + Q in = Min + Q [ in -A Min]
std::vector<Field> tmp(nrhs,this->grid);
std::vector<Field> Min(nrhs,this->grid);
std::vector<CoarseField> PleftProj(nrhs,this->coarsegrid);
std::vector<CoarseField> PleftMss_proj(nrhs,this->coarsegrid);
CoarseField PleftProjMrhs(this->coarsegridmrhs);
CoarseField PleftMss_projMrhs(this->coarsegridmrhs);
// this->rrr=in[0];
#undef SMOOTHER_BLOCK_SOLVE
#if SMOOTHER_BLOCK_SOLVE
this->SmoothTimer.Start();
this->_Smoother(in,Min);
this->SmoothTimer.Stop();
#else
for(int rhs=0;rhs<nrhs;rhs++) {
this->SmoothTimer.Start();
this->_Smoother(in[rhs],Min[rhs]);
this->SmoothTimer.Stop();
}
#endif
// this->sss=Min[0];
for(int rhs=0;rhs<nrhs;rhs++) {
this->FineTimer.Start();
this->_FineLinop.HermOp(Min[rhs],out[rhs]);
axpy(tmp[rhs],-1.0,out[rhs],in[rhs]); // resid = in - A Min
this->FineTimer.Stop();
}
this->ProjectTimer.Start();
this->_Projector.blockProject(tmp,PleftProj);
this->ProjectTimer.Stop();
this->DeflateTimer.Start();
this->_Deflator.DeflateSources(PleftProj,PleftMss_proj);
this->DeflateTimer.Stop();
this->InsertTimer.Start();
for(int rhs=0;rhs<nrhs;rhs++) {
InsertSliceFast(PleftProj[rhs],PleftProjMrhs,rhs,0);
InsertSliceFast(PleftMss_proj[rhs],PleftMss_projMrhs,rhs,0); // the guess
}
this->InsertTimer.Stop();
this->CoarseTimer.Start();
this->_CoarseSolverMrhs(PleftProjMrhs,PleftMss_projMrhs); // Ass^{-1} [in - A Min]_s
this->CoarseTimer.Stop();
this->InsertTimer.Start();
for(int rhs=0;rhs<nrhs;rhs++) {
ExtractSliceFast(PleftMss_proj[rhs],PleftMss_projMrhs,rhs,0);
}
this->InsertTimer.Stop();
this->PromoteTimer.Start();
this->_Projector.blockPromote(tmp,PleftMss_proj);// tmp= Q[in - A Min]
this->PromoteTimer.Stop();
this->FineTimer.Start();
// this->qqq=tmp[0];
for(int rhs=0;rhs<nrhs;rhs++) {
axpy(out[rhs],1.0,Min[rhs],tmp[rhs]); // Min+tmp
}
// this->zzz=out[0];
this->FineTimer.Stop();
}
};
NAMESPACE_END(Grid);
-234
View File
@@ -1,234 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/BiCGSTAB.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: paboyle <paboyle@ph.ed.ac.uk>
Author: juettner <juettner@soton.ac.uk>
Author: David Murphy <djmurphy@mit.edu>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_BICGSTAB_H
#define GRID_BICGSTAB_H
NAMESPACE_BEGIN(Grid);
/////////////////////////////////////////////////////////////
// Base classes for iterative processes based on operators
// single input vec, single output vec.
/////////////////////////////////////////////////////////////
template <class Field>
class BiCGSTAB : public OperatorFunction<Field>
{
public:
using OperatorFunction<Field>::operator();
bool ErrorOnNoConverge; // throw an assert when the CG fails to converge.
// Defaults true.
RealD Tolerance;
Integer MaxIterations;
Integer IterationsToComplete; //Number of iterations the CG took to finish. Filled in upon completion
BiCGSTAB(RealD tol, Integer maxit, bool err_on_no_conv = true) :
Tolerance(tol), MaxIterations(maxit), ErrorOnNoConverge(err_on_no_conv){};
void operator()(LinearOperatorBase<Field>& Linop, const Field& src, Field& psi)
{
psi.Checkerboard() = src.Checkerboard();
conformable(psi, src);
RealD cp(0), rho(1), rho_prev(0), alpha(1), beta(0), omega(1);
RealD a(0), bo(0), b(0), ssq(0);
Field p(src);
Field r(src);
Field rhat(src);
Field v(src);
Field s(src);
Field t(src);
Field h(src);
v = Zero();
p = Zero();
// Initial residual computation & set up
RealD guess = norm2(psi);
assert(std::isnan(guess) == 0);
Linop.Op(psi, v);
b = norm2(v);
r = src - v;
rhat = r;
a = norm2(r);
ssq = norm2(src);
std::cout << GridLogIterative << std::setprecision(8) << "BiCGSTAB: guess " << guess << std::endl;
std::cout << GridLogIterative << std::setprecision(8) << "BiCGSTAB: src " << ssq << std::endl;
std::cout << GridLogIterative << std::setprecision(8) << "BiCGSTAB: mp " << b << std::endl;
std::cout << GridLogIterative << std::setprecision(8) << "BiCGSTAB: r " << a << std::endl;
RealD rsq = Tolerance * Tolerance * ssq;
// Check if guess is really REALLY good :)
if(a <= rsq){ return; }
std::cout << GridLogIterative << std::setprecision(8) << "BiCGSTAB: k=0 residual " << a << " target " << rsq << std::endl;
GridStopWatch LinalgTimer;
GridStopWatch InnerTimer;
GridStopWatch AxpyNormTimer;
GridStopWatch LinearCombTimer;
GridStopWatch MatrixTimer;
GridStopWatch SolverTimer;
SolverTimer.Start();
int k;
for (k = 1; k <= MaxIterations; k++)
{
rho_prev = rho;
LinalgTimer.Start();
InnerTimer.Start();
ComplexD Crho = innerProduct(rhat,r);
InnerTimer.Stop();
rho = Crho.real();
beta = (rho / rho_prev) * (alpha / omega);
LinearCombTimer.Start();
bo = beta * omega;
{
autoView( p_v , p, AcceleratorWrite);
autoView( r_v , r, AcceleratorRead);
autoView( v_v , v, AcceleratorRead);
accelerator_for(ss, p_v.size(), Field::vector_object::Nsimd(),{
coalescedWrite(p_v[ss], beta*p_v(ss) - bo*v_v(ss) + r_v(ss));
});
}
LinearCombTimer.Stop();
LinalgTimer.Stop();
MatrixTimer.Start();
Linop.Op(p,v);
MatrixTimer.Stop();
LinalgTimer.Start();
InnerTimer.Start();
ComplexD Calpha = innerProduct(rhat,v);
InnerTimer.Stop();
alpha = rho / Calpha.real();
LinearCombTimer.Start();
{
autoView( p_v , p, AcceleratorRead);
autoView( r_v , r, AcceleratorRead);
autoView( v_v , v, AcceleratorRead);
autoView( psi_v,psi, AcceleratorRead);
autoView( h_v , h, AcceleratorWrite);
autoView( s_v , s, AcceleratorWrite);
accelerator_for(ss, h_v.size(), Field::vector_object::Nsimd(),{
coalescedWrite(h_v[ss], alpha*p_v(ss) + psi_v(ss));
});
accelerator_for(ss, s_v.size(), Field::vector_object::Nsimd(),{
coalescedWrite(s_v[ss], -alpha*v_v(ss) + r_v(ss));
});
}
LinearCombTimer.Stop();
LinalgTimer.Stop();
MatrixTimer.Start();
Linop.Op(s,t);
MatrixTimer.Stop();
LinalgTimer.Start();
InnerTimer.Start();
ComplexD Comega = innerProduct(t,s);
InnerTimer.Stop();
omega = Comega.real() / norm2(t);
LinearCombTimer.Start();
{
autoView( psi_v,psi, AcceleratorWrite);
autoView( r_v , r, AcceleratorWrite);
autoView( h_v , h, AcceleratorRead);
autoView( s_v , s, AcceleratorRead);
autoView( t_v , t, AcceleratorRead);
accelerator_for(ss, psi_v.size(), Field::vector_object::Nsimd(),{
coalescedWrite(psi_v[ss], h_v(ss) + omega * s_v(ss));
coalescedWrite(r_v[ss], -omega * t_v(ss) + s_v(ss));
});
}
LinearCombTimer.Stop();
cp = norm2(r);
LinalgTimer.Stop();
std::cout << GridLogIterative << "BiCGSTAB: Iteration " << k << " residual " << sqrt(cp/ssq) << " target " << Tolerance << std::endl;
// Stopping condition
if(cp <= rsq)
{
SolverTimer.Stop();
Linop.Op(psi, v);
p = v - src;
RealD srcnorm = sqrt(norm2(src));
RealD resnorm = sqrt(norm2(p));
RealD true_residual = resnorm / srcnorm;
std::cout << GridLogMessage << "BiCGSTAB Converged on iteration " << k << std::endl;
std::cout << GridLogMessage << "\tComputed residual " << sqrt(cp/ssq) << std::endl;
std::cout << GridLogMessage << "\tTrue residual " << true_residual << std::endl;
std::cout << GridLogMessage << "\tTarget " << Tolerance << std::endl;
std::cout << GridLogMessage << "Time breakdown " << std::endl;
std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "\tLinalg " << LinalgTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "\tInner " << InnerTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "\tAxpyNorm " << AxpyNormTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "\tLinearComb " << LinearCombTimer.Elapsed() << std::endl;
if(ErrorOnNoConverge){ assert(true_residual / Tolerance < 10000.0); }
IterationsToComplete = k;
return;
}
}
std::cout << GridLogMessage << "BiCGSTAB did NOT converge" << std::endl;
if(ErrorOnNoConverge){ assert(0); }
IterationsToComplete = k;
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,159 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/BiCGSTABMixedPrec.h
Copyright (C) 2015
Author: Christopher Kelly <ckelly@phys.columbia.edu>
Author: David Murphy <djmurphy@mit.edu>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_BICGSTAB_MIXED_PREC_H
#define GRID_BICGSTAB_MIXED_PREC_H
NAMESPACE_BEGIN(Grid);
// Mixed precision restarted defect correction BiCGSTAB
template<class FieldD, class FieldF, typename std::enable_if< getPrecision<FieldD>::value == 2, int>::type = 0, typename std::enable_if< getPrecision<FieldF>::value == 1, int>::type = 0>
class MixedPrecisionBiCGSTAB : public LinearFunction<FieldD>
{
public:
using LinearFunction<FieldD>::operator();
RealD Tolerance;
RealD InnerTolerance; // Initial tolerance for inner CG. Defaults to Tolerance but can be changed
Integer MaxInnerIterations;
Integer MaxOuterIterations;
GridBase* SinglePrecGrid; // Grid for single-precision fields
RealD OuterLoopNormMult; // Stop the outer loop and move to a final double prec solve when the residual is OuterLoopNormMult * Tolerance
LinearOperatorBase<FieldF> &Linop_f;
LinearOperatorBase<FieldD> &Linop_d;
Integer TotalInnerIterations; //Number of inner CG iterations
Integer TotalOuterIterations; //Number of restarts
Integer TotalFinalStepIterations; //Number of CG iterations in final patch-up step
//Option to speed up *inner single precision* solves using a LinearFunction that produces a guess
LinearFunction<FieldF> *guesser;
MixedPrecisionBiCGSTAB(RealD tol, Integer maxinnerit, Integer maxouterit, GridBase* _sp_grid,
LinearOperatorBase<FieldF>& _Linop_f, LinearOperatorBase<FieldD>& _Linop_d) :
Linop_f(_Linop_f), Linop_d(_Linop_d), Tolerance(tol), InnerTolerance(tol), MaxInnerIterations(maxinnerit),
MaxOuterIterations(maxouterit), SinglePrecGrid(_sp_grid), OuterLoopNormMult(100.), guesser(NULL) {};
void useGuesser(LinearFunction<FieldF>& g){
guesser = &g;
}
void operator() (const FieldD& src_d_in, FieldD& sol_d)
{
TotalInnerIterations = 0;
GridStopWatch TotalTimer;
TotalTimer.Start();
int cb = src_d_in.Checkerboard();
sol_d.Checkerboard() = cb;
RealD src_norm = norm2(src_d_in);
RealD stop = src_norm * Tolerance*Tolerance;
GridBase* DoublePrecGrid = src_d_in.Grid();
FieldD tmp_d(DoublePrecGrid);
tmp_d.Checkerboard() = cb;
FieldD tmp2_d(DoublePrecGrid);
tmp2_d.Checkerboard() = cb;
FieldD src_d(DoublePrecGrid);
src_d = src_d_in; //source for next inner iteration, computed from residual during operation
RealD inner_tol = InnerTolerance;
FieldF src_f(SinglePrecGrid);
src_f.Checkerboard() = cb;
FieldF sol_f(SinglePrecGrid);
sol_f.Checkerboard() = cb;
BiCGSTAB<FieldF> CG_f(inner_tol, MaxInnerIterations);
CG_f.ErrorOnNoConverge = false;
GridStopWatch InnerCGtimer;
GridStopWatch PrecChangeTimer;
Integer &outer_iter = TotalOuterIterations; //so it will be equal to the final iteration count
for(outer_iter = 0; outer_iter < MaxOuterIterations; outer_iter++)
{
// Compute double precision rsd and also new RHS vector.
Linop_d.Op(sol_d, tmp_d);
RealD norm = axpy_norm(src_d, -1., tmp_d, src_d_in); //src_d is residual vector
std::cout << GridLogMessage << "MixedPrecisionBiCGSTAB: Outer iteration " << outer_iter << " residual " << norm << " target " << stop << std::endl;
if(norm < OuterLoopNormMult * stop){
std::cout << GridLogMessage << "MixedPrecisionBiCGSTAB: Outer iteration converged on iteration " << outer_iter << std::endl;
break;
}
while(norm * inner_tol * inner_tol < stop){ inner_tol *= 2; } // inner_tol = sqrt(stop/norm) ??
PrecChangeTimer.Start();
precisionChange(src_f, src_d);
PrecChangeTimer.Stop();
sol_f = Zero();
//Optionally improve inner solver guess (eg using known eigenvectors)
if(guesser != NULL){ (*guesser)(src_f, sol_f); }
//Inner CG
CG_f.Tolerance = inner_tol;
InnerCGtimer.Start();
CG_f(Linop_f, src_f, sol_f);
InnerCGtimer.Stop();
TotalInnerIterations += CG_f.IterationsToComplete;
//Convert sol back to double and add to double prec solution
PrecChangeTimer.Start();
precisionChange(tmp_d, sol_f);
PrecChangeTimer.Stop();
axpy(sol_d, 1.0, tmp_d, sol_d);
}
//Final trial CG
std::cout << GridLogMessage << "MixedPrecisionBiCGSTAB: Starting final patch-up double-precision solve" << std::endl;
BiCGSTAB<FieldD> CG_d(Tolerance, MaxInnerIterations);
CG_d(Linop_d, src_d_in, sol_d);
TotalFinalStepIterations = CG_d.IterationsToComplete;
TotalTimer.Stop();
std::cout << GridLogMessage << "MixedPrecisionBiCGSTAB: Inner CG iterations " << TotalInnerIterations << " Restarts " << TotalOuterIterations << " Final CG iterations " << TotalFinalStepIterations << std::endl;
std::cout << GridLogMessage << "MixedPrecisionBiCGSTAB: Total time " << TotalTimer.Elapsed() << " Precision change " << PrecChangeTimer.Elapsed() << " Inner CG total " << InnerCGtimer.Elapsed() << std::endl;
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,741 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/BlockConjugateGradient.h
Copyright (C) 2017
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
template<class Field>
void InnerProductMatrix(Eigen::MatrixXcd &m , const std::vector<Field> &X, const std::vector<Field> &Y){
typedef typename Field::scalar_type scomplex;
int Nblock = X.size();
for(int b=0;b<Nblock;b++){
for(int bp=0;bp<Nblock;bp++) {
m(b,bp) = innerProduct(X[b],Y[bp]);
}}
}
template<class Field>
void MaddMatrix(std::vector<Field> &AP, Eigen::MatrixXcd &m , const std::vector<Field> &X,const std::vector<Field> &Y,RealD scale=1.0){
// Should make this cache friendly with site outermost, parallel_for
// Deal with case AP aliases with either Y or X
//
//Could pack "X" and "AP" into a Nblock x Volume dense array.
// AP(Nrhs x vol) = Y(Nrhs x vol) + scale * m(nrhs x nrhs) * X(nrhs*vol)
typedef typename Field::scalar_type scomplex;
int Nblock = AP.size();
std::vector<Field> tmp(Nblock,X[0]);
for(int b=0;b<Nblock;b++){
tmp[b] = Y[b];
for(int bp=0;bp<Nblock;bp++) {
tmp[b] = tmp[b] +scomplex(scale*m(bp,b))*X[bp];
}
}
for(int b=0;b<Nblock;b++){
AP[b] = tmp[b];
}
}
template<class Field>
void MulMatrix(std::vector<Field> &AP, Eigen::MatrixXcd &m , const std::vector<Field> &X){
// Should make this cache friendly with site outermost, parallel_for
typedef typename Field::scalar_type scomplex;
int Nblock = AP.size();
for(int b=0;b<Nblock;b++){
AP[b] = Zero();
for(int bp=0;bp<Nblock;bp++) {
AP[b] += scomplex(m(bp,b))*X[bp];
}
}
}
template<class Field>
double normv(const std::vector<Field> &P){
int Nblock = P.size();
double nn = 0.0;
for(int b=0;b<Nblock;b++) {
nn+=norm2(P[b]);
}
return nn;
}
enum BlockCGtype { BlockCG, BlockCGrQ, CGmultiRHS, BlockCGVec, BlockCGrQVec };
//////////////////////////////////////////////////////////////////////////
// Block conjugate gradient. Dimension zero should be the block direction
//////////////////////////////////////////////////////////////////////////
template <class Field>
class BlockConjugateGradient : public OperatorFunction<Field> {
public:
typedef typename Field::scalar_type scomplex;
int blockDim ;
int Nblock;
BlockCGtype CGtype;
bool ErrorOnNoConverge; // throw an assert when the CG fails to converge.
// Defaults true.
RealD Tolerance;
Integer MaxIterations;
Integer IterationsToComplete; //Number of iterations the CG took to finish. Filled in upon completion
Integer PrintInterval; //GridLogMessages or Iterative
RealD TrueResidual;
BlockConjugateGradient(BlockCGtype cgtype,int _Orthog,RealD tol, Integer maxit, bool err_on_no_conv = true)
: Tolerance(tol), CGtype(cgtype), blockDim(_Orthog), MaxIterations(maxit), ErrorOnNoConverge(err_on_no_conv),PrintInterval(100)
{};
////////////////////////////////////////////////////////////////////////////////////////////////////
// Thin QR factorisation (google it)
////////////////////////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
//Dimensions
// R_{ferm x Nblock} = Q_{ferm x Nblock} x C_{Nblock x Nblock} -> ferm x Nblock
//
// Rdag R = m_rr = Herm = L L^dag <-- Cholesky decomposition (LLT routine in Eigen)
//
// Q C = R => Q = R C^{-1}
//
// Want Ident = Q^dag Q = C^{-dag} R^dag R C^{-1} = C^{-dag} L L^dag C^{-1} = 1_{Nblock x Nblock}
//
// Set C = L^{dag}, and then Q^dag Q = ident
//
// Checks:
// Cdag C = Rdag R ; passes.
// QdagQ = 1 ; passes
////////////////////////////////////////////////////////////////////////////////////////////////////
void ThinQRfact (Eigen::MatrixXcd &m_rr,
Eigen::MatrixXcd &C,
Eigen::MatrixXcd &Cinv,
Field & Q,
const Field & R)
{
int Orthog = blockDim; // First dimension is block dim; this is an assumption
sliceInnerProductMatrix(m_rr,R,R,Orthog);
// Force manifest hermitian to avoid rounding related
/*
int rank=m_rr.rows();
for(int r=0;r<rank;r++){
for(int s=0;s<rank;s++){
std::cout << "QR m_rr["<<r<<","<<s<<"] "<<m_rr(r,s)<<std::endl;
}}
*/
m_rr = 0.5*(m_rr+m_rr.adjoint());
Eigen::MatrixXcd L = m_rr.llt().matrixL();
// ComplexD det = L.determinant();
// std::cout << " Det m_rr "<<det<<std::endl;
C = L.adjoint();
Cinv = C.inverse();
////////////////////////////////////////////////////////////////////////////////////////////////////
// Q = R C^{-1}
//
// Q_j = R_i Cinv(i,j)
//
// NB maddMatrix conventions are Right multiplication X[j] a[j,i] already
////////////////////////////////////////////////////////////////////////////////////////////////////
sliceMulMatrix(Q,Cinv,R,Orthog);
}
// see comments above
void ThinQRfact (Eigen::MatrixXcd &m_rr,
Eigen::MatrixXcd &C,
Eigen::MatrixXcd &Cinv,
std::vector<Field> & Q,
const std::vector<Field> & R)
{
InnerProductMatrix(m_rr,R,R);
/*
int rank=m_rr.rows();
for(int r=0;r<rank;r++){
for(int s=0;s<rank;s++){
std::cout << "QRvec m_rr["<<r<<","<<s<<"] "<<m_rr(r,s)<<std::endl;
}}
*/
m_rr = 0.5*(m_rr+m_rr.adjoint());
Eigen::MatrixXcd L = m_rr.llt().matrixL();
// ComplexD det = L.determinant();
// std::cout << " Det m_rr "<<det<<std::endl;
C = L.adjoint();
Cinv = C.inverse();
MulMatrix(Q,Cinv,R);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
// Call one of several implementations
////////////////////////////////////////////////////////////////////////////////////////////////////
void operator()(LinearOperatorBase<Field> &Linop, const Field &Src, Field &Psi)
{
if ( CGtype == BlockCGrQ ) {
BlockCGrQsolve(Linop,Src,Psi);
} else if (CGtype == CGmultiRHS ) {
CGmultiRHSsolve(Linop,Src,Psi);
} else {
assert(0);
}
}
virtual void operator()(LinearOperatorBase<Field> &Linop, const std::vector<Field> &Src, std::vector<Field> &Psi)
{
if ( CGtype == BlockCGrQVec ) {
BlockCGrQsolveVec(Linop,Src,Psi);
} else {
assert(0);
}
}
////////////////////////////////////////////////////////////////////////////
// BlockCGrQ implementation:
//--------------------------
// X is guess/Solution
// B is RHS
// Solve A X_i = B_i ; i refers to Nblock index
////////////////////////////////////////////////////////////////////////////
void BlockCGrQsolve(LinearOperatorBase<Field> &Linop, const Field &B, Field &X)
{
int Orthog = blockDim; // First dimension is block dim; this is an assumption
Nblock = B.Grid()->_fdimensions[Orthog];
/* FAKE */
Nblock=8;
std::cout<<GridLogMessage<<" Block Conjugate Gradient : Orthog "<<Orthog<<" Nblock "<<Nblock<<std::endl;
X.Checkerboard() = B.Checkerboard();
conformable(X, B);
Field tmp(B);
Field Q(B);
Field D(B);
Field Z(B);
Field AD(B);
Eigen::MatrixXcd m_DZ = Eigen::MatrixXcd::Identity(Nblock,Nblock);
Eigen::MatrixXcd m_M = Eigen::MatrixXcd::Identity(Nblock,Nblock);
Eigen::MatrixXcd m_rr = Eigen::MatrixXcd::Zero(Nblock,Nblock);
Eigen::MatrixXcd m_C = Eigen::MatrixXcd::Zero(Nblock,Nblock);
Eigen::MatrixXcd m_Cinv = Eigen::MatrixXcd::Zero(Nblock,Nblock);
Eigen::MatrixXcd m_S = Eigen::MatrixXcd::Zero(Nblock,Nblock);
Eigen::MatrixXcd m_Sinv = Eigen::MatrixXcd::Zero(Nblock,Nblock);
Eigen::MatrixXcd m_tmp = Eigen::MatrixXcd::Identity(Nblock,Nblock);
Eigen::MatrixXcd m_tmp1 = Eigen::MatrixXcd::Identity(Nblock,Nblock);
// Initial residual computation & set up
std::vector<RealD> residuals(Nblock);
std::vector<RealD> ssq(Nblock);
sliceNorm(ssq,B,Orthog);
RealD sssum=0;
for(int b=0;b<Nblock;b++) sssum+=ssq[b];
for(int b=0;b<Nblock;b++) std::cout << "src["<<b<<"]" << ssq[b] <<std::endl;
sliceNorm(residuals,B,Orthog);
for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
sliceNorm(residuals,X,Orthog);
for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
/************************************************************************
* Block conjugate gradient rQ (Sebastien Birk Thesis, after Dubrulle 2001)
************************************************************************
* Dimensions:
*
* X,B==(Nferm x Nblock)
* A==(Nferm x Nferm)
*
* Nferm = Nspin x Ncolour x Ncomplex x Nlattice_site
*
* QC = R = B-AX, D = Q ; QC => Thin QR factorisation (google it)
* for k:
* Z = AD
* M = [D^dag Z]^{-1}
* X = X + D MC
* QS = Q - ZM
* D = Q + D S^dag
* C = S C
*/
///////////////////////////////////////
// Initial block: initial search dir is guess
///////////////////////////////////////
std::cout << GridLogMessage<<"BlockCGrQ algorithm initialisation " <<std::endl;
//1. QC = R = B-AX, D = Q ; QC => Thin QR factorisation (google it)
Linop.HermOp(X, AD);
tmp = B - AD;
sliceNorm(residuals,tmp,Orthog);
for(int b=0;b<Nblock;b++) std::cout << "res["<<b<<"]" << residuals[b] <<std::endl;
ThinQRfact (m_rr, m_C, m_Cinv, Q, tmp);
D=Q;
std::cout << GridLogMessage<<"BlockCGrQ computed initial residual and QR fact " <<std::endl;
///////////////////////////////////////
// Timers
///////////////////////////////////////
GridStopWatch sliceInnerTimer;
GridStopWatch sliceMaddTimer;
GridStopWatch QRTimer;
GridStopWatch MatrixTimer;
GridStopWatch SolverTimer;
SolverTimer.Start();
RealD max_resid=0;
int k;
for (k = 1; k <= MaxIterations; k++) {
//3. Z = AD
MatrixTimer.Start();
Linop.HermOp(D, Z);
MatrixTimer.Stop();
//4. M = [D^dag Z]^{-1}
sliceInnerTimer.Start();
sliceInnerProductMatrix(m_DZ,D,Z,Orthog);
sliceInnerTimer.Stop();
m_M = m_DZ.inverse();
//5. X = X + D MC
m_tmp = m_M * m_C;
sliceMaddTimer.Start();
sliceMaddMatrix(X,m_tmp, D,X,Orthog);
sliceMaddTimer.Stop();
//6. QS = Q - ZM
sliceMaddTimer.Start();
sliceMaddMatrix(tmp,m_M,Z,Q,Orthog,-1.0);
sliceMaddTimer.Stop();
QRTimer.Start();
ThinQRfact (m_rr, m_S, m_Sinv, Q, tmp);
QRTimer.Stop();
//7. D = Q + D S^dag
m_tmp = m_S.adjoint();
sliceMaddTimer.Start();
sliceMaddMatrix(D,m_tmp,D,Q,Orthog);
sliceMaddTimer.Stop();
//8. C = S C
m_C = m_S*m_C;
/*********************
* convergence monitor
*********************
*/
m_rr = m_C.adjoint() * m_C;
max_resid=0;
RealD rrsum=0;
RealD rr;
for(int b=0;b<Nblock;b++) {
rrsum+=real(m_rr(b,b));
rr = real(m_rr(b,b))/ssq[b];
if ( rr > max_resid ) max_resid = rr;
}
std::cout << GridLogIterative << "\titeration "<<k<<" rr_sum "<<rrsum<<" ssq_sum "<< sssum
<<" ave "<<std::sqrt(rrsum/sssum) << " max "<< max_resid <<std::endl;
if ( max_resid < Tolerance*Tolerance ) {
SolverTimer.Stop();
std::cout << GridLogMessage<<"BlockCGrQ converged in "<<k<<" iterations"<<std::endl;
for(int b=0;b<Nblock;b++){
std::cout << GridLogMessage<< "\t\tblock "<<b<<" computed resid "
<< std::sqrt(real(m_rr(b,b))/ssq[b])<<std::endl;
}
std::cout << GridLogMessage<<"\tMax residual is "<<std::sqrt(max_resid)<<std::endl;
Linop.HermOp(X, AD);
AD = AD-B;
TrueResidual = std::sqrt(norm2(AD)/norm2(B));
std::cout << GridLogMessage <<"\tTrue residual is " << TrueResidual <<std::endl;
std::cout << GridLogMessage << "Time Breakdown "<<std::endl;
std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tInnerProd " << sliceInnerTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tMaddMatrix " << sliceMaddTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tThinQRfact " << QRTimer.Elapsed() <<std::endl;
IterationsToComplete = k;
return;
}
}
std::cout << GridLogMessage << "BlockConjugateGradient(rQ) did NOT converge "<<k<<" / "<<MaxIterations
<<" residual "<< std::sqrt(max_resid)<< std::endl;
if (ErrorOnNoConverge) assert(0);
IterationsToComplete = k;
}
//////////////////////////////////////////////////////////////////////////
// multiRHS conjugate gradient. Dimension zero should be the block direction
// Use this for spread out across nodes
//////////////////////////////////////////////////////////////////////////
void CGmultiRHSsolve(LinearOperatorBase<Field> &Linop, const Field &Src, Field &Psi)
{
int Orthog = blockDim; // First dimension is block dim
Nblock = Src.Grid()->_fdimensions[Orthog];
std::cout<<GridLogMessage<<"MultiRHS Conjugate Gradient : Orthog "<<Orthog<<" Nblock "<<Nblock<<std::endl;
Psi.Checkerboard() = Src.Checkerboard();
conformable(Psi, Src);
Field P(Src);
Field AP(Src);
Field R(Src);
std::vector<ComplexD> v_pAp(Nblock);
std::vector<RealD> v_rr (Nblock);
std::vector<RealD> v_rr_inv(Nblock);
std::vector<RealD> v_alpha(Nblock);
std::vector<RealD> v_beta(Nblock);
// Initial residual computation & set up
std::vector<RealD> residuals(Nblock);
std::vector<RealD> ssq(Nblock);
sliceNorm(ssq,Src,Orthog);
RealD sssum=0;
for(int b=0;b<Nblock;b++) sssum+=ssq[b];
sliceNorm(residuals,Src,Orthog);
for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
sliceNorm(residuals,Psi,Orthog);
for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
// Initial search dir is guess
Linop.HermOp(Psi, AP);
R = Src - AP;
P = R;
sliceNorm(v_rr,R,Orthog);
GridStopWatch sliceInnerTimer;
GridStopWatch sliceMaddTimer;
GridStopWatch sliceNormTimer;
GridStopWatch MatrixTimer;
GridStopWatch SolverTimer;
SolverTimer.Start();
int k;
for (k = 1; k <= MaxIterations; k++) {
RealD rrsum=0;
for(int b=0;b<Nblock;b++) rrsum+=real(v_rr[b]);
std::cout << GridLogIterative << "\titeration "<<k<<" rr_sum "<<rrsum<<" ssq_sum "<< sssum
<<" / "<<std::sqrt(rrsum/sssum) <<std::endl;
MatrixTimer.Start();
Linop.HermOp(P, AP);
MatrixTimer.Stop();
// Alpha
sliceInnerTimer.Start();
sliceInnerProductVector(v_pAp,P,AP,Orthog);
sliceInnerTimer.Stop();
for(int b=0;b<Nblock;b++){
v_alpha[b] = v_rr[b]/real(v_pAp[b]);
}
// Psi, R update
sliceMaddTimer.Start();
sliceMaddVector(Psi,v_alpha, P,Psi,Orthog); // add alpha * P to psi
sliceMaddVector(R ,v_alpha,AP, R,Orthog,-1.0);// sub alpha * AP to resid
sliceMaddTimer.Stop();
// Beta
for(int b=0;b<Nblock;b++){
v_rr_inv[b] = 1.0/v_rr[b];
}
sliceNormTimer.Start();
sliceNorm(v_rr,R,Orthog);
sliceNormTimer.Stop();
for(int b=0;b<Nblock;b++){
v_beta[b] = v_rr_inv[b] *v_rr[b];
}
// Search update
sliceMaddTimer.Start();
sliceMaddVector(P,v_beta,P,R,Orthog);
sliceMaddTimer.Stop();
/*********************
* convergence monitor
*********************
*/
RealD max_resid=0;
for(int b=0;b<Nblock;b++){
RealD rr = v_rr[b]/ssq[b];
if ( rr > max_resid ) max_resid = rr;
}
if ( max_resid < Tolerance*Tolerance ) {
SolverTimer.Stop();
std::cout << GridLogMessage<<"MultiRHS solver converged in " <<k<<" iterations"<<std::endl;
for(int b=0;b<Nblock;b++){
std::cout << GridLogMessage<< "\t\tBlock "<<b<<" computed resid "<< std::sqrt(v_rr[b]/ssq[b])<<std::endl;
}
std::cout << GridLogMessage<<"\tMax residual is "<<std::sqrt(max_resid)<<std::endl;
Linop.HermOp(Psi, AP);
AP = AP-Src;
TrueResidual = std::sqrt(norm2(AP)/norm2(Src));
std::cout <<GridLogMessage << "\tTrue residual is " << TrueResidual <<std::endl;
std::cout << GridLogMessage << "Time Breakdown "<<std::endl;
std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tInnerProd " << sliceInnerTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tNorm " << sliceNormTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tMaddMatrix " << sliceMaddTimer.Elapsed() <<std::endl;
IterationsToComplete = k;
return;
}
}
std::cout << GridLogMessage << "MultiRHSConjugateGradient did NOT converge" << std::endl;
if (ErrorOnNoConverge) assert(0);
IterationsToComplete = k;
}
////////////////////////////////////////////////////////////////////////////
// BlockCGrQvec implementation:
//--------------------------
// X is guess/Solution
// B is RHS
// Solve A X_i = B_i ; i refers to Nblock index
////////////////////////////////////////////////////////////////////////////
void BlockCGrQsolveVec(LinearOperatorBase<Field> &Linop, const std::vector<Field> &B, std::vector<Field> &X)
{
Nblock = B.size();
assert(Nblock == X.size());
std::cout<<GridLogMessage<<" Block Conjugate Gradient Vec rQ : Nblock "<<Nblock<<std::endl;
for(int b=0;b<Nblock;b++){
X[b].Checkerboard() = B[b].Checkerboard();
conformable(X[b], B[b]);
conformable(X[b], X[0]);
}
Field Fake(B[0]);
std::vector<Field> tmp(Nblock,Fake);
std::vector<Field> Q(Nblock,Fake);
std::vector<Field> D(Nblock,Fake);
std::vector<Field> Z(Nblock,Fake);
std::vector<Field> AD(Nblock,Fake);
Eigen::MatrixXcd m_DZ = Eigen::MatrixXcd::Identity(Nblock,Nblock);
Eigen::MatrixXcd m_M = Eigen::MatrixXcd::Identity(Nblock,Nblock);
Eigen::MatrixXcd m_rr = Eigen::MatrixXcd::Zero(Nblock,Nblock);
Eigen::MatrixXcd m_C = Eigen::MatrixXcd::Zero(Nblock,Nblock);
Eigen::MatrixXcd m_Cinv = Eigen::MatrixXcd::Zero(Nblock,Nblock);
Eigen::MatrixXcd m_S = Eigen::MatrixXcd::Zero(Nblock,Nblock);
Eigen::MatrixXcd m_Sinv = Eigen::MatrixXcd::Zero(Nblock,Nblock);
Eigen::MatrixXcd m_tmp = Eigen::MatrixXcd::Identity(Nblock,Nblock);
Eigen::MatrixXcd m_tmp1 = Eigen::MatrixXcd::Identity(Nblock,Nblock);
// Initial residual computation & set up
std::vector<RealD> residuals(Nblock);
std::vector<RealD> ssq(Nblock);
RealD sssum=0;
for(int b=0;b<Nblock;b++){ ssq[b] = norm2(B[b]);}
for(int b=0;b<Nblock;b++){ std::cout << "ssq["<<b<<"] "<<ssq[b]<<std::endl;}
for(int b=0;b<Nblock;b++) sssum+=ssq[b];
for(int b=0;b<Nblock;b++){ residuals[b] = norm2(B[b]);}
for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
for(int b=0;b<Nblock;b++){ residuals[b] = norm2(X[b]);}
for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
/************************************************************************
* Block conjugate gradient rQ (Sebastien Birk Thesis, after Dubrulle 2001)
************************************************************************
* Dimensions:
*
* X,B==(Nferm x Nblock)
* A==(Nferm x Nferm)
*
* Nferm = Nspin x Ncolour x Ncomplex x Nlattice_site
*
* QC = R = B-AX, D = Q ; QC => Thin QR factorisation (google it)
* for k:
* Z = AD
* M = [D^dag Z]^{-1}
* X = X + D MC
* QS = Q - ZM
* D = Q + D S^dag
* C = S C
*/
///////////////////////////////////////
// Initial block: initial search dir is guess
///////////////////////////////////////
std::cout << GridLogMessage<<"BlockCGrQvec algorithm initialisation " <<std::endl;
//1. QC = R = B-AX, D = Q ; QC => Thin QR factorisation (google it)
for(int b=0;b<Nblock;b++) {
Linop.HermOp(X[b], AD[b]);
tmp[b] = B[b] - AD[b];
std::cout << "r0["<<b<<"] "<<norm2(tmp[b])<<std::endl;
}
ThinQRfact (m_rr, m_C, m_Cinv, Q, tmp);
for(int b=0;b<Nblock;b++) D[b]=Q[b];
std::cout << GridLogMessage<<"BlockCGrQ vec computed initial residual and QR fact " <<std::endl;
///////////////////////////////////////
// Timers
///////////////////////////////////////
GridStopWatch sliceInnerTimer;
GridStopWatch sliceMaddTimer;
GridStopWatch QRTimer;
GridStopWatch MatrixTimer;
GridStopWatch SolverTimer;
SolverTimer.Start();
int k;
for (k = 1; k <= MaxIterations; k++) {
//3. Z = AD
MatrixTimer.Start();
for(int b=0;b<Nblock;b++) Linop.HermOp(D[b], Z[b]);
MatrixTimer.Stop();
//4. M = [D^dag Z]^{-1}
sliceInnerTimer.Start();
InnerProductMatrix(m_DZ,D,Z);
sliceInnerTimer.Stop();
m_M = m_DZ.inverse();
//5. X = X + D MC
m_tmp = m_M * m_C;
sliceMaddTimer.Start();
MaddMatrix(X,m_tmp, D,X);
sliceMaddTimer.Stop();
//6. QS = Q - ZM
sliceMaddTimer.Start();
MaddMatrix(tmp,m_M,Z,Q,-1.0);
sliceMaddTimer.Stop();
QRTimer.Start();
ThinQRfact (m_rr, m_S, m_Sinv, Q, tmp);
QRTimer.Stop();
//7. D = Q + D S^dag
m_tmp = m_S.adjoint();
sliceMaddTimer.Start();
MaddMatrix(D,m_tmp,D,Q);
sliceMaddTimer.Stop();
//8. C = S C
m_C = m_S*m_C;
/*********************
* convergence monitor
*********************
*/
m_rr = m_C.adjoint() * m_C;
RealD max_resid=0;
RealD rrsum=0;
RealD rr;
for(int b=0;b<Nblock;b++) {
rrsum+=real(m_rr(b,b));
rr = real(m_rr(b,b))/ssq[b];
if ( rr > max_resid ) max_resid = rr;
}
std::cout << GridLogIterative << "\t Block Iteration "<<k<<" ave resid "<< std::sqrt(rrsum/sssum) << " max "<< std::sqrt(max_resid) <<std::endl;
if ( max_resid < Tolerance*Tolerance ) {
SolverTimer.Stop();
std::cout << GridLogMessage<<"BlockCGrQ converged in "<<k<<" iterations"<<std::endl;
for(int b=0;b<Nblock;b++){
std::cout << GridLogMessage<< "\t\tblock "<<b<<" computed resid "<< std::sqrt(real(m_rr(b,b))/ssq[b])<<std::endl;
}
std::cout << GridLogMessage<<"\tMax residual is "<<std::sqrt(max_resid)<<std::endl;
for(int b=0;b<Nblock;b++) Linop.HermOp(X[b], AD[b]);
for(int b=0;b<Nblock;b++) AD[b] = AD[b]-B[b];
TrueResidual = std::sqrt(normv(AD)/normv(B));
std::cout << GridLogMessage << "\tTrue residual is " << TrueResidual <<std::endl;
std::cout << GridLogMessage << "Time Breakdown "<<std::endl;
std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tInnerProd " << sliceInnerTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tMaddMatrix " << sliceMaddTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tThinQRfact " << QRTimer.Elapsed() <<std::endl;
IterationsToComplete = k;
return;
}
}
std::cout << GridLogMessage << "BlockConjugateGradient(rQ) did NOT converge" << std::endl;
if (ErrorOnNoConverge) assert(0);
IterationsToComplete = k;
}
};
NAMESPACE_END(Grid);
@@ -1,248 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/CommunicationAvoidingGeneralisedMinimalResidual.h
Copyright (C) 2015
Author: Daniel Richtmann <daniel.richtmann@ur.de>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_COMMUNICATION_AVOIDING_GENERALISED_MINIMAL_RESIDUAL_H
#define GRID_COMMUNICATION_AVOIDING_GENERALISED_MINIMAL_RESIDUAL_H
namespace Grid {
template<class Field>
class CommunicationAvoidingGeneralisedMinimalResidual : public OperatorFunction<Field> {
public:
using OperatorFunction<Field>::operator();
bool ErrorOnNoConverge; // Throw an assert when CAGMRES fails to converge,
// defaults to true
RealD Tolerance;
Integer MaxIterations;
Integer RestartLength;
Integer MaxNumberOfRestarts;
Integer IterationCount; // Number of iterations the CAGMRES took to finish,
// filled in upon completion
GridStopWatch MatrixTimer;
GridStopWatch LinalgTimer;
GridStopWatch QrTimer;
GridStopWatch CompSolutionTimer;
Eigen::MatrixXcd H;
std::vector<ComplexD> y;
std::vector<ComplexD> gamma;
std::vector<ComplexD> c;
std::vector<ComplexD> s;
CommunicationAvoidingGeneralisedMinimalResidual(RealD tol,
Integer maxit,
Integer restart_length,
bool err_on_no_conv = true)
: Tolerance(tol)
, MaxIterations(maxit)
, RestartLength(restart_length)
, MaxNumberOfRestarts(MaxIterations/RestartLength + ((MaxIterations%RestartLength == 0) ? 0 : 1))
, ErrorOnNoConverge(err_on_no_conv)
, H(Eigen::MatrixXcd::Zero(RestartLength, RestartLength + 1)) // sizes taken from DD-αAMG code base
, y(RestartLength + 1, 0.)
, gamma(RestartLength + 1, 0.)
, c(RestartLength + 1, 0.)
, s(RestartLength + 1, 0.) {};
void operator()(LinearOperatorBase<Field> &LinOp, const Field &src, Field &psi) {
std::cout << GridLogWarning << "This algorithm currently doesn't differ from regular GMRES" << std::endl;
psi.Checkerboard() = src.Checkerboard();
conformable(psi, src);
RealD guess = norm2(psi);
assert(std::isnan(guess) == 0);
RealD cp;
RealD ssq = norm2(src);
RealD rsq = Tolerance * Tolerance * ssq;
Field r(src.Grid());
std::cout << std::setprecision(4) << std::scientific;
std::cout << GridLogIterative << "CommunicationAvoidingGeneralisedMinimalResidual: guess " << guess << std::endl;
std::cout << GridLogIterative << "CommunicationAvoidingGeneralisedMinimalResidual: src " << ssq << std::endl;
MatrixTimer.Reset();
LinalgTimer.Reset();
QrTimer.Reset();
CompSolutionTimer.Reset();
GridStopWatch SolverTimer;
SolverTimer.Start();
IterationCount = 0;
for (int k=0; k<MaxNumberOfRestarts; k++) {
cp = outerLoopBody(LinOp, src, psi, rsq);
// Stopping condition
if (cp <= rsq) {
SolverTimer.Stop();
LinOp.Op(psi,r);
axpy(r,-1.0,src,r);
RealD srcnorm = sqrt(ssq);
RealD resnorm = sqrt(norm2(r));
RealD true_residual = resnorm / srcnorm;
std::cout << GridLogMessage << "CommunicationAvoidingGeneralisedMinimalResidual: Converged on iteration " << IterationCount
<< " computed residual " << sqrt(cp / ssq)
<< " true residual " << true_residual
<< " target " << Tolerance << std::endl;
std::cout << GridLogMessage << "CAGMRES Time elapsed: Total " << SolverTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "CAGMRES Time elapsed: Matrix " << MatrixTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "CAGMRES Time elapsed: Linalg " << LinalgTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "CAGMRES Time elapsed: QR " << QrTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "CAGMRES Time elapsed: CompSol " << CompSolutionTimer.Elapsed() << std::endl;
return;
}
}
std::cout << GridLogMessage << "CommunicationAvoidingGeneralisedMinimalResidual did NOT converge" << std::endl;
if (ErrorOnNoConverge)
assert(0);
}
RealD outerLoopBody(LinearOperatorBase<Field> &LinOp, const Field &src, Field &psi, RealD rsq) {
RealD cp = 0;
Field w(src.Grid());
Field r(src.Grid());
// this should probably be made a class member so that it is only allocated once, not in every restart
std::vector<Field> v(RestartLength + 1, src.Grid()); for (auto &elem : v) elem = Zero();
MatrixTimer.Start();
LinOp.Op(psi, w);
MatrixTimer.Stop();
LinalgTimer.Start();
r = src - w;
gamma[0] = sqrt(norm2(r));
ComplexD scale = 1.0/gamma[0];
v[0] = scale * r;
LinalgTimer.Stop();
for (int i=0; i<RestartLength; i++) {
IterationCount++;
arnoldiStep(LinOp, v, w, i);
qrUpdate(i);
cp = norm(gamma[i+1]);
std::cout << GridLogIterative << "CommunicationAvoidingGeneralisedMinimalResidual: Iteration " << IterationCount
<< " residual " << cp << " target " << rsq << std::endl;
if ((i == RestartLength - 1) || (IterationCount == MaxIterations) || (cp <= rsq)) {
computeSolution(v, psi, i);
return cp;
}
}
assert(0); // Never reached
return cp;
}
void arnoldiStep(LinearOperatorBase<Field> &LinOp, std::vector<Field> &v, Field &w, int iter) {
MatrixTimer.Start();
LinOp.Op(v[iter], w);
MatrixTimer.Stop();
LinalgTimer.Start();
for (int i = 0; i <= iter; ++i) {
H(iter, i) = innerProduct(v[i], w);
w = w - ComplexD(H(iter, i)) * v[i];
}
H(iter, iter + 1) = sqrt(norm2(w));
v[iter + 1] = ComplexD(1. / H(iter, iter + 1)) * w;
LinalgTimer.Stop();
}
void qrUpdate(int iter) {
QrTimer.Start();
for (int i = 0; i < iter ; ++i) {
auto tmp = -s[i] * ComplexD(H(iter, i)) + c[i] * ComplexD(H(iter, i + 1));
H(iter, i) = conjugate(c[i]) * ComplexD(H(iter, i)) + conjugate(s[i]) * ComplexD(H(iter, i + 1));
H(iter, i + 1) = tmp;
}
// Compute new Givens Rotation
auto nu = sqrt(std::norm(H(iter, iter)) + std::norm(H(iter, iter + 1)));
c[iter] = H(iter, iter) / nu;
s[iter] = H(iter, iter + 1) / nu;
// Apply new Givens rotation
H(iter, iter) = nu;
H(iter, iter + 1) = 0.;
gamma[iter + 1] = -s[iter] * gamma[iter];
gamma[iter] = conjugate(c[iter]) * gamma[iter];
QrTimer.Stop();
}
void computeSolution(std::vector<Field> const &v, Field &psi, int iter) {
CompSolutionTimer.Start();
for (int i = iter; i >= 0; i--) {
y[i] = gamma[i];
for (int k = i + 1; k <= iter; k++)
y[i] = y[i] - ComplexD(H(k, i)) * y[k];
y[i] = y[i] / ComplexD(H(i, i));
}
for (int i = 0; i <= iter; i++)
psi = psi + v[i] * y[i];
CompSolutionTimer.Stop();
}
};
}
#endif
@@ -1,373 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ConjugateGradient.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: paboyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CONJUGATE_GRADIENT_H
#define GRID_CONJUGATE_GRADIENT_H
NAMESPACE_BEGIN(Grid);
/////////////////////////////////////////////////////////////
// Base classes for iterative processes based on operators
// single input vec, single output vec.
/////////////////////////////////////////////////////////////
template <class Field>
class ConjugateGradient : public OperatorFunction<Field> {
public:
using OperatorFunction<Field>::operator();
bool ErrorOnNoConverge; // throw an assert when the CG fails to converge.
// Defaults true.
RealD Tolerance;
Integer MaxIterations;
Integer IterationsToComplete; //Number of iterations the CG took to finish. Filled in upon completion
RealD TrueResidual;
ConjugateGradient(RealD tol, Integer maxit, bool err_on_no_conv = true)
: Tolerance(tol),
MaxIterations(maxit),
ErrorOnNoConverge(err_on_no_conv)
{};
virtual void LogIteration(int k,RealD a,RealD b){
// std::cout << "ConjugageGradient::LogIteration() "<<std::endl;
};
virtual void LogBegin(void){
std::cout << "ConjugageGradient::LogBegin() "<<std::endl;
};
void operator()(LinearOperatorBase<Field> &Linop, const Field &src, Field &psi) {
this->LogBegin();
GRID_TRACE("ConjugateGradient");
GridStopWatch PreambleTimer;
GridStopWatch ConstructTimer;
GridStopWatch NormTimer;
GridStopWatch AssignTimer;
PreambleTimer.Start();
psi.Checkerboard() = src.Checkerboard();
conformable(psi, src);
RealD cp, c, a, d, b, ssq, qq;
//RealD b_pred;
// Was doing copies
ConstructTimer.Start();
Field p (src.Grid());
Field mmp(src.Grid());
Field r (src.Grid());
ConstructTimer.Stop();
// Initial residual computation & set up
NormTimer.Start();
ssq = norm2(src);
RealD guess = norm2(psi);
NormTimer.Stop();
assert(std::isnan(guess) == 0);
AssignTimer.Start();
if ( guess == 0.0 ) {
r = src;
p = r;
a = ssq;
} else {
Linop.HermOpAndNorm(psi, mmp, d, b);
r = src - mmp;
p = r;
a = norm2(p);
}
cp = a;
AssignTimer.Stop();
// Handle trivial case of zero src
if (ssq == 0.){
psi = Zero();
IterationsToComplete = 1;
TrueResidual = 0.;
return;
}
std::cout << GridLogIterative << std::setprecision(8) << "ConjugateGradient: guess " << guess << std::endl;
std::cout << GridLogIterative << std::setprecision(8) << "ConjugateGradient: src " << ssq << std::endl;
std::cout << GridLogIterative << std::setprecision(8) << "ConjugateGradient: mp " << d << std::endl;
std::cout << GridLogIterative << std::setprecision(8) << "ConjugateGradient: mmp " << b << std::endl;
std::cout << GridLogIterative << std::setprecision(8) << "ConjugateGradient: cp,r " << cp << std::endl;
std::cout << GridLogIterative << std::setprecision(8) << "ConjugateGradient: p " << a << std::endl;
RealD rsq = Tolerance * Tolerance * ssq;
// Check if guess is really REALLY good :)
if (cp <= rsq) {
TrueResidual = std::sqrt(a/ssq);
std::cout << GridLogMessage << "ConjugateGradient guess is converged already " << std::endl;
IterationsToComplete = 0;
return;
}
std::cout << GridLogIterative << std::setprecision(8)
<< "ConjugateGradient: k=0 residual " << cp << " target " << rsq << std::endl;
PreambleTimer.Stop();
GridStopWatch LinalgTimer;
GridStopWatch InnerTimer;
GridStopWatch AxpyNormTimer;
GridStopWatch LinearCombTimer;
GridStopWatch MatrixTimer;
GridStopWatch SolverTimer;
RealD usecs = -usecond();
SolverTimer.Start();
int k;
for (k = 1; k <= MaxIterations; k++) {
GridStopWatch IterationTimer;
IterationTimer.Start();
c = cp;
MatrixTimer.Start();
Linop.HermOp(p, mmp);
MatrixTimer.Stop();
LinalgTimer.Start();
InnerTimer.Start();
ComplexD dc = innerProduct(p,mmp);
InnerTimer.Stop();
d = dc.real();
a = c / d;
AxpyNormTimer.Start();
cp = axpy_norm(r, -a, mmp, r);
AxpyNormTimer.Stop();
b = cp / c;
LinearCombTimer.Start();
{
autoView( psi_v , psi, AcceleratorWrite);
autoView( p_v , p, AcceleratorWrite);
autoView( r_v , r, AcceleratorWrite);
accelerator_for(ss,p_v.size(), Field::vector_object::Nsimd(),{
coalescedWrite(psi_v[ss], a * p_v(ss) + psi_v(ss));
coalescedWrite(p_v[ss] , b * p_v(ss) + r_v (ss));
});
}
LinearCombTimer.Stop();
LinalgTimer.Stop();
LogIteration(k,a,b);
IterationTimer.Stop();
if ( (k % 500) == 0 ) {
std::cout << GridLogMessage << "ConjugateGradient: Iteration " << k
<< " residual " << sqrt(cp/ssq) << " target " << Tolerance << std::endl;
} else {
std::cout << GridLogIterative << "ConjugateGradient: Iteration " << k
<< " residual " << sqrt(cp/ssq) << " target " << Tolerance << " took " << IterationTimer.Elapsed() << std::endl;
}
// Stopping condition
if (cp <= rsq) {
usecs +=usecond();
SolverTimer.Stop();
Linop.HermOpAndNorm(psi, mmp, d, qq);
p = mmp - src;
GridBase *grid = src.Grid();
RealD DwfFlops = (1452. )*grid->gSites()*4*k
+ (8+4+8+4+4)*12*grid->gSites()*k; // CG linear algebra
RealD srcnorm = std::sqrt(norm2(src));
RealD resnorm = std::sqrt(norm2(p));
RealD true_residual = resnorm / srcnorm;
std::cout << GridLogMessage << "ConjugateGradient Converged on iteration " << k
<< "\tComputed residual " << std::sqrt(cp / ssq)
<< "\tTrue residual " << true_residual
<< "\tTarget " << Tolerance << std::endl;
// std::cout << GridLogMessage << "\tPreamble " << PreambleTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tSolver Elapsed " << SolverTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "Time breakdown "<<std::endl;
std::cout << GridLogPerformance << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "\tLinalg " << LinalgTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "\t\tInner " << InnerTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "\t\tAxpyNorm " << AxpyNormTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "\t\tLinearComb " << LinearCombTimer.Elapsed() <<std::endl;
std::cout << GridLogDebug << "\tMobius flop rate " << DwfFlops/ usecs<< " Gflops " <<std::endl;
if (ErrorOnNoConverge) assert(true_residual / Tolerance < 10000.0);
IterationsToComplete = k;
TrueResidual = true_residual;
return;
}
}
// Failed. Calculate true residual before giving up
// Linop.HermOpAndNorm(psi, mmp, d, qq);
// p = mmp - src;
//TrueResidual = sqrt(norm2(p)/ssq);
// TrueResidual = 1;
std::cout << GridLogMessage << "ConjugateGradient did NOT converge "<<k<<" / "<< MaxIterations
<<" residual "<< std::sqrt(cp / ssq)<< std::endl;
SolverTimer.Stop();
std::cout << GridLogMessage << "\tPreamble " << PreambleTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tConstruct " << ConstructTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tNorm " << NormTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tAssign " << AssignTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tSolver " << SolverTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "Solver breakdown "<<std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage<< "\tLinalg " << LinalgTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "\t\tInner " << InnerTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "\t\tAxpyNorm " << AxpyNormTimer.Elapsed() <<std::endl;
std::cout << GridLogPerformance << "\t\tLinearComb " << LinearCombTimer.Elapsed() <<std::endl;
if (ErrorOnNoConverge) assert(0);
IterationsToComplete = k;
}
};
template <class Field>
class ConjugateGradientPolynomial : public ConjugateGradient<Field> {
public:
// Optionally record the CG polynomial
std::vector<double> ak;
std::vector<double> bk;
std::vector<double> poly_p;
std::vector<double> poly_r;
std::vector<double> poly_Ap;
std::vector<double> polynomial;
public:
ConjugateGradientPolynomial(RealD tol, Integer maxit, bool err_on_no_conv = true)
: ConjugateGradient<Field>(tol,maxit,err_on_no_conv)
{ };
void PolyHermOp(LinearOperatorBase<Field> &Linop, const Field &src, Field &psi)
{
Field tmp(src.Grid());
Field AtoN(src.Grid());
AtoN = src;
psi=AtoN*polynomial[0];
for(int n=1;n<polynomial.size();n++){
tmp = AtoN;
Linop.HermOp(tmp,AtoN);
psi = psi + polynomial[n]*AtoN;
}
}
void CGsequenceHermOp(LinearOperatorBase<Field> &Linop, const Field &src, Field &x)
{
Field Ap(src.Grid());
Field r(src.Grid());
Field p(src.Grid());
p=src;
r=src;
x=Zero();
x.Checkerboard()=src.Checkerboard();
for(int k=0;k<ak.size();k++){
x = x + ak[k]*p;
Linop.HermOp(p,Ap);
r = r - ak[k] * Ap;
p = r + bk[k] * p;
}
}
void Solve(LinearOperatorBase<Field> &Linop, const Field &src, Field &psi)
{
psi=Zero();
this->operator ()(Linop,src,psi);
}
virtual void LogBegin(void)
{
std::cout << "ConjugageGradientPolynomial::LogBegin() "<<std::endl;
ak.resize(0);
bk.resize(0);
polynomial.resize(0);
poly_Ap.resize(0);
poly_Ap.resize(0);
poly_p.resize(1);
poly_r.resize(1);
poly_p[0]=1.0;
poly_r[0]=1.0;
};
virtual void LogIteration(int k,RealD a,RealD b)
{
// With zero guess,
// p = r = src
//
// iterate:
// x = x + a p
// r = r - a A p
// p = r + b p
//
// [0]
// r = x
// p = x
// Ap=0
//
// [1]
// Ap = A x + 0 ==> shift poly P right by 1 and add 0.
// x = x + a p ==> add polynomials term by term
// r = r - a A p ==> add polynomials term by term
// p = r + b p ==> add polynomials term by term
//
std::cout << "ConjugageGradientPolynomial::LogIteration() "<<k<<std::endl;
ak.push_back(a);
bk.push_back(b);
// Ap= right_shift(p)
poly_Ap.resize(k+1);
poly_Ap[0]=0.0;
for(int i=0;i<k;i++){
poly_Ap[i+1]=poly_p[i];
}
// x = x + a p
polynomial.resize(k);
polynomial[k-1]=0.0;
for(int i=0;i<k;i++){
polynomial[i] = polynomial[i] + a * poly_p[i];
}
// r = r - a Ap
// p = r + b p
poly_r.resize(k+1);
poly_p.resize(k+1);
poly_r[k] = poly_p[k] = 0.0;
for(int i=0;i<k+1;i++){
poly_r[i] = poly_r[i] - a * poly_Ap[i];
poly_p[i] = poly_r[i] + b * poly_p[i];
}
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,170 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ConjugateGradientMixedPrec.h
Copyright (C) 2015
Author: Christopher Kelly <ckelly@phys.columbia.edu>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CONJUGATE_GRADIENT_MIXED_PREC_H
#define GRID_CONJUGATE_GRADIENT_MIXED_PREC_H
NAMESPACE_BEGIN(Grid);
//Mixed precision restarted defect correction CG
template<class FieldD,class FieldF,
typename std::enable_if< getPrecision<FieldD>::value == 2, int>::type = 0,
typename std::enable_if< getPrecision<FieldF>::value == 1, int>::type = 0>
class MixedPrecisionConjugateGradient : public LinearFunction<FieldD> {
public:
using LinearFunction<FieldD>::operator();
RealD Tolerance;
RealD InnerTolerance; //Initial tolerance for inner CG. Defaults to Tolerance but can be changed
Integer MaxInnerIterations;
Integer MaxOuterIterations;
GridBase* SinglePrecGrid; //Grid for single-precision fields
RealD OuterLoopNormMult; //Stop the outer loop and move to a final double prec solve when the residual is OuterLoopNormMult * Tolerance
LinearOperatorBase<FieldF> &Linop_f;
LinearOperatorBase<FieldD> &Linop_d;
Integer TotalInnerIterations; //Number of inner CG iterations
Integer TotalOuterIterations; //Number of restarts
Integer TotalFinalStepIterations; //Number of CG iterations in final patch-up step
RealD TrueResidual;
//Option to speed up *inner single precision* solves using a LinearFunction that produces a guess
LinearFunction<FieldF> *guesser;
MixedPrecisionConjugateGradient(RealD tol,
Integer maxinnerit,
Integer maxouterit,
GridBase* _sp_grid,
LinearOperatorBase<FieldF> &_Linop_f,
LinearOperatorBase<FieldD> &_Linop_d) :
Linop_f(_Linop_f), Linop_d(_Linop_d),
Tolerance(tol), InnerTolerance(tol), MaxInnerIterations(maxinnerit), MaxOuterIterations(maxouterit), SinglePrecGrid(_sp_grid),
OuterLoopNormMult(100.), guesser(NULL){ };
void useGuesser(LinearFunction<FieldF> &g){
guesser = &g;
}
void operator() (const FieldD &src_d_in, FieldD &sol_d){
std::cout << GridLogMessage << "MixedPrecisionConjugateGradient: Starting mixed precision CG with outer tolerance " << Tolerance << " and inner tolerance " << InnerTolerance << std::endl;
TotalInnerIterations = 0;
GridStopWatch TotalTimer;
TotalTimer.Start();
int cb = src_d_in.Checkerboard();
sol_d.Checkerboard() = cb;
RealD src_norm = norm2(src_d_in);
RealD stop = src_norm * Tolerance*Tolerance;
GridBase* DoublePrecGrid = src_d_in.Grid();
FieldD tmp_d(DoublePrecGrid);
tmp_d.Checkerboard() = cb;
FieldD tmp2_d(DoublePrecGrid);
tmp2_d.Checkerboard() = cb;
FieldD src_d(DoublePrecGrid);
src_d = src_d_in; //source for next inner iteration, computed from residual during operation
RealD inner_tol = InnerTolerance;
FieldF src_f(SinglePrecGrid);
src_f.Checkerboard() = cb;
FieldF sol_f(SinglePrecGrid);
sol_f.Checkerboard() = cb;
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradient: Starting initial inner CG with tolerance " << inner_tol << std::endl;
ConjugateGradient<FieldF> CG_f(inner_tol, MaxInnerIterations);
CG_f.ErrorOnNoConverge = false;
GridStopWatch InnerCGtimer;
GridStopWatch PrecChangeTimer;
Integer &outer_iter = TotalOuterIterations; //so it will be equal to the final iteration count
precisionChangeWorkspace pc_wk_sp_to_dp(DoublePrecGrid, SinglePrecGrid);
precisionChangeWorkspace pc_wk_dp_to_sp(SinglePrecGrid, DoublePrecGrid);
for(outer_iter = 0; outer_iter < MaxOuterIterations; outer_iter++){
//Compute double precision rsd and also new RHS vector.
Linop_d.HermOp(sol_d, tmp_d);
RealD norm = axpy_norm(src_d, -1., tmp_d, src_d_in); //src_d is residual vector
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradient: Outer iteration " <<outer_iter<<" residual "<< norm<< " target "<< stop<<std::endl;
if(norm < OuterLoopNormMult * stop){
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradient: Outer iteration converged on iteration " <<outer_iter <<std::endl;
break;
}
while(norm * inner_tol * inner_tol < stop) inner_tol *= 2; // inner_tol = sqrt(stop/norm) ??
PrecChangeTimer.Start();
precisionChange(src_f, src_d, pc_wk_dp_to_sp);
PrecChangeTimer.Stop();
sol_f = Zero();
//Optionally improve inner solver guess (eg using known eigenvectors)
if(guesser != NULL)
(*guesser)(src_f, sol_f);
//Inner CG
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradient: Outer iteration " << outer_iter << " starting inner CG with tolerance " << inner_tol << std::endl;
CG_f.Tolerance = inner_tol;
InnerCGtimer.Start();
CG_f(Linop_f, src_f, sol_f);
InnerCGtimer.Stop();
TotalInnerIterations += CG_f.IterationsToComplete;
//Convert sol back to double and add to double prec solution
PrecChangeTimer.Start();
precisionChange(tmp_d, sol_f, pc_wk_sp_to_dp);
PrecChangeTimer.Stop();
axpy(sol_d, 1.0, tmp_d, sol_d);
}
//Final trial CG
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradient: Starting final patch-up double-precision solve"<<std::endl;
ConjugateGradient<FieldD> CG_d(Tolerance, MaxInnerIterations);
CG_d(Linop_d, src_d_in, sol_d);
TotalFinalStepIterations = CG_d.IterationsToComplete;
TrueResidual = CG_d.TrueResidual;
TotalTimer.Stop();
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradient: Inner CG iterations " << TotalInnerIterations << " Restarts " << TotalOuterIterations << " Final CG iterations " << TotalFinalStepIterations << std::endl;
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradient: Total time " << TotalTimer.Elapsed() << " Precision change " << PrecChangeTimer.Elapsed() << " Inner CG total " << InnerCGtimer.Elapsed() << std::endl;
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,213 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ConjugateGradientMixedPrecBatched.h
Copyright (C) 2015
Author: Raoul Hodgson <raoul.hodgson@ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CONJUGATE_GRADIENT_MIXED_PREC_BATCHED_H
#define GRID_CONJUGATE_GRADIENT_MIXED_PREC_BATCHED_H
NAMESPACE_BEGIN(Grid);
//Mixed precision restarted defect correction CG
template<class FieldD,class FieldF,
typename std::enable_if< getPrecision<FieldD>::value == 2, int>::type = 0,
typename std::enable_if< getPrecision<FieldF>::value == 1, int>::type = 0>
class MixedPrecisionConjugateGradientBatched : public LinearFunction<FieldD> {
public:
using LinearFunction<FieldD>::operator();
RealD Tolerance;
RealD InnerTolerance; //Initial tolerance for inner CG. Defaults to Tolerance but can be changed
Integer MaxInnerIterations;
Integer MaxOuterIterations;
Integer MaxPatchupIterations;
GridBase* SinglePrecGrid; //Grid for single-precision fields
RealD OuterLoopNormMult; //Stop the outer loop and move to a final double prec solve when the residual is OuterLoopNormMult * Tolerance
LinearOperatorBase<FieldF> &Linop_f;
LinearOperatorBase<FieldD> &Linop_d;
//Option to speed up *inner single precision* solves using a LinearFunction that produces a guess
LinearFunction<FieldF> *guesser;
bool updateResidual;
MixedPrecisionConjugateGradientBatched(RealD tol,
Integer maxinnerit,
Integer maxouterit,
Integer maxpatchit,
GridBase* _sp_grid,
LinearOperatorBase<FieldF> &_Linop_f,
LinearOperatorBase<FieldD> &_Linop_d,
bool _updateResidual=true) :
Linop_f(_Linop_f), Linop_d(_Linop_d),
Tolerance(tol), InnerTolerance(tol), MaxInnerIterations(maxinnerit), MaxOuterIterations(maxouterit), MaxPatchupIterations(maxpatchit), SinglePrecGrid(_sp_grid),
OuterLoopNormMult(100.), guesser(NULL), updateResidual(_updateResidual) { };
void useGuesser(LinearFunction<FieldF> &g){
guesser = &g;
}
void operator() (const FieldD &src_d_in, FieldD &sol_d){
std::vector<FieldD> srcs_d_in{src_d_in};
std::vector<FieldD> sols_d{sol_d};
(*this)(srcs_d_in,sols_d);
sol_d = sols_d[0];
}
void operator() (const std::vector<FieldD> &src_d_in, std::vector<FieldD> &sol_d){
assert(src_d_in.size() == sol_d.size());
int NBatch = src_d_in.size();
std::cout << GridLogMessage << "NBatch = " << NBatch << std::endl;
Integer TotalOuterIterations = 0; //Number of restarts
std::vector<Integer> TotalInnerIterations(NBatch,0); //Number of inner CG iterations
std::vector<Integer> TotalFinalStepIterations(NBatch,0); //Number of CG iterations in final patch-up step
GridStopWatch TotalTimer;
TotalTimer.Start();
GridStopWatch InnerCGtimer;
GridStopWatch PrecChangeTimer;
int cb = src_d_in[0].Checkerboard();
std::vector<RealD> src_norm;
std::vector<RealD> norm;
std::vector<RealD> stop;
GridBase* DoublePrecGrid = src_d_in[0].Grid();
FieldD tmp_d(DoublePrecGrid);
tmp_d.Checkerboard() = cb;
FieldD tmp2_d(DoublePrecGrid);
tmp2_d.Checkerboard() = cb;
std::vector<FieldD> src_d;
std::vector<FieldF> src_f;
std::vector<FieldF> sol_f;
for (int i=0; i<NBatch; i++) {
sol_d[i].Checkerboard() = cb;
src_norm.push_back(norm2(src_d_in[i]));
norm.push_back(0.);
stop.push_back(src_norm[i] * Tolerance*Tolerance);
src_d.push_back(src_d_in[i]); //source for next inner iteration, computed from residual during operation
src_f.push_back(SinglePrecGrid);
src_f[i].Checkerboard() = cb;
sol_f.push_back(SinglePrecGrid);
sol_f[i].Checkerboard() = cb;
}
RealD inner_tol = InnerTolerance;
ConjugateGradient<FieldF> CG_f(inner_tol, MaxInnerIterations);
CG_f.ErrorOnNoConverge = false;
Integer &outer_iter = TotalOuterIterations; //so it will be equal to the final iteration count
for(outer_iter = 0; outer_iter < MaxOuterIterations; outer_iter++){
std::cout << GridLogMessage << std::endl;
std::cout << GridLogMessage << "Outer iteration " << outer_iter << std::endl;
bool allConverged = true;
for (int i=0; i<NBatch; i++) {
//Compute double precision rsd and also new RHS vector.
Linop_d.HermOp(sol_d[i], tmp_d);
norm[i] = axpy_norm(src_d[i], -1., tmp_d, src_d_in[i]); //src_d is residual vector
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradientBatched: Outer iteration " << outer_iter <<" solve " << i << " residual "<< norm[i] << " target "<< stop[i] <<std::endl;
PrecChangeTimer.Start();
precisionChange(src_f[i], src_d[i]);
PrecChangeTimer.Stop();
sol_f[i] = Zero();
if(norm[i] > OuterLoopNormMult * stop[i]) {
allConverged = false;
}
}
if (allConverged) break;
if (updateResidual) {
RealD normMax = *std::max_element(std::begin(norm), std::end(norm));
RealD stopMax = *std::max_element(std::begin(stop), std::end(stop));
while( normMax * inner_tol * inner_tol < stopMax) inner_tol *= 2; // inner_tol = sqrt(stop/norm) ??
CG_f.Tolerance = inner_tol;
}
//Optionally improve inner solver guess (eg using known eigenvectors)
if(guesser != NULL) {
(*guesser)(src_f, sol_f);
}
for (int i=0; i<NBatch; i++) {
//Inner CG
InnerCGtimer.Start();
CG_f(Linop_f, src_f[i], sol_f[i]);
InnerCGtimer.Stop();
TotalInnerIterations[i] += CG_f.IterationsToComplete;
//Convert sol back to double and add to double prec solution
PrecChangeTimer.Start();
precisionChange(tmp_d, sol_f[i]);
PrecChangeTimer.Stop();
axpy(sol_d[i], 1.0, tmp_d, sol_d[i]);
}
}
//Final trial CG
std::cout << GridLogMessage << std::endl;
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradientBatched: Starting final patch-up double-precision solve"<<std::endl;
for (int i=0; i<NBatch; i++) {
ConjugateGradient<FieldD> CG_d(Tolerance, MaxPatchupIterations);
CG_d(Linop_d, src_d_in[i], sol_d[i]);
TotalFinalStepIterations[i] += CG_d.IterationsToComplete;
}
TotalTimer.Stop();
std::cout << GridLogMessage << std::endl;
for (int i=0; i<NBatch; i++) {
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradientBatched: solve " << i << " Inner CG iterations " << TotalInnerIterations[i] << " Restarts " << TotalOuterIterations << " Final CG iterations " << TotalFinalStepIterations[i] << std::endl;
}
std::cout << GridLogMessage << std::endl;
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradientBatched: Total time " << TotalTimer.Elapsed() << " Precision change " << PrecChangeTimer.Elapsed() << " Inner CG total " << InnerCGtimer.Elapsed() << std::endl;
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,346 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ConjugateGradientMultiShift.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CONJUGATE_MULTI_SHIFT_GRADIENT_H
#define GRID_CONJUGATE_MULTI_SHIFT_GRADIENT_H
NAMESPACE_BEGIN(Grid);
/////////////////////////////////////////////////////////////
// Base classes for iterative processes based on operators
// single input vec, single output vec.
/////////////////////////////////////////////////////////////
template<class Field>
class ConjugateGradientMultiShift : public OperatorMultiFunction<Field>,
public OperatorFunction<Field>
{
public:
using OperatorFunction<Field>::operator();
// RealD Tolerance;
Integer MaxIterations;
Integer IterationsToComplete; //Number of iterations the CG took to finish. Filled in upon completion
std::vector<int> IterationsToCompleteShift; // Iterations for this shift
int verbose;
MultiShiftFunction shifts;
std::vector<RealD> TrueResidualShift;
ConjugateGradientMultiShift(Integer maxit, const MultiShiftFunction &_shifts) :
MaxIterations(maxit),
shifts(_shifts)
{
verbose=1;
IterationsToCompleteShift.resize(_shifts.order);
TrueResidualShift.resize(_shifts.order);
}
void operator() (LinearOperatorBase<Field> &Linop, const Field &src, Field &psi)
{
GridBase *grid = src.Grid();
int nshift = shifts.order;
std::vector<Field> results(nshift,grid);
(*this)(Linop,src,results,psi);
}
void operator() (LinearOperatorBase<Field> &Linop, const Field &src, std::vector<Field> &results, Field &psi)
{
int nshift = shifts.order;
(*this)(Linop,src,results);
psi = shifts.norm*src;
for(int i=0;i<nshift;i++){
psi = psi + shifts.residues[i]*results[i];
}
return;
}
void operator() (LinearOperatorBase<Field> &Linop, const Field &src, std::vector<Field> &psi)
{
GRID_TRACE("ConjugateGradientMultiShift");
GridBase *grid = src.Grid();
////////////////////////////////////////////////////////////////////////
// Convenience references to the info stored in "MultiShiftFunction"
////////////////////////////////////////////////////////////////////////
int nshift = shifts.order;
std::vector<RealD> &mass(shifts.poles); // Make references to array in "shifts"
std::vector<RealD> &mresidual(shifts.tolerances);
std::vector<RealD> alpha(nshift,1.0);
std::vector<Field> ps(nshift,grid);// Search directions
assert(psi.size()==nshift);
assert(mass.size()==nshift);
assert(mresidual.size()==nshift);
// dynamic sized arrays on stack; 2d is a pain with vector
RealD bs[nshift];
RealD rsq[nshift];
RealD z[nshift][2];
int converged[nshift];
const int primary =0;
//Primary shift fields CG iteration
RealD a,b,c,d;
RealD cp,bp,qq; //prev
// Matrix mult fields
Field r(grid);
Field p(grid);
Field tmp(grid);
Field mmp(grid);
// Check lightest mass
for(int s=0;s<nshift;s++){
assert( mass[s]>= mass[primary] );
converged[s]=0;
}
// Wire guess to zero
// Residuals "r" are src
// First search direction "p" is also src
cp = norm2(src);
// Handle trivial case of zero src.
if( cp == 0. ){
for(int s=0;s<nshift;s++){
psi[s] = Zero();
IterationsToCompleteShift[s] = 1;
TrueResidualShift[s] = 0.;
}
return;
}
for(int s=0;s<nshift;s++){
rsq[s] = cp * mresidual[s] * mresidual[s];
std::cout<<GridLogMessage<<"ConjugateGradientMultiShift: shift "<<s
<<" target resid^2 "<<rsq[s]<<std::endl;
ps[s] = src;
}
// r and p for primary
r=src;
p=src;
//MdagM+m[0]
Linop.HermOpAndNorm(p,mmp,d,qq);
axpy(mmp,mass[0],p,mmp);
RealD rn = norm2(p);
d += rn*mass[0];
// have verified that inner product of
// p and mmp is equal to d after this since
// the d computation is tricky
// qq = real(innerProduct(p,mmp));
// std::cout<<GridLogMessage << "debug equal ? qq "<<qq<<" d "<< d<<std::endl;
b = -cp /d;
// Set up the various shift variables
int iz=0;
z[0][1-iz] = 1.0;
z[0][iz] = 1.0;
bs[0] = b;
for(int s=1;s<nshift;s++){
z[s][1-iz] = 1.0;
z[s][iz] = 1.0/( 1.0 - b*(mass[s]-mass[0]));
bs[s] = b*z[s][iz];
}
// r += b[0] A.p[0]
// c= norm(r)
c=axpy_norm(r,b,mmp,r);
for(int s=0;s<nshift;s++) {
axpby(psi[s],0.,-bs[s]*alpha[s],src,src);
}
std::cout << GridLogIterative << "ConjugateGradientMultiShift: initial rn (|src|^2) =" << rn << " qq (|MdagM src|^2) =" << qq << " d ( dot(src, [MdagM + m_0]src) ) =" << d << " c=" << c << std::endl;
///////////////////////////////////////
// Timers
///////////////////////////////////////
GridStopWatch AXPYTimer;
GridStopWatch ShiftTimer;
GridStopWatch QRTimer;
GridStopWatch MatrixTimer;
GridStopWatch SolverTimer;
SolverTimer.Start();
// Iteration loop
int k;
for (k=1;k<=MaxIterations;k++){
a = c /cp;
AXPYTimer.Start();
axpy(p,a,p,r);
AXPYTimer.Stop();
// Note to self - direction ps is iterated seperately
// for each shift. Does not appear to have any scope
// for avoiding linear algebra in "single" case.
//
// However SAME r is used. Could load "r" and update
// ALL ps[s]. 2/3 Bandwidth saving
// New Kernel: Load r, vector of coeffs, vector of pointers ps
AXPYTimer.Start();
for(int s=0;s<nshift;s++){
if ( ! converged[s] ) {
if (s==0){
axpy(ps[s],a,ps[s],r);
} else{
RealD as =a *z[s][iz]*bs[s] /(z[s][1-iz]*b);
axpby(ps[s],z[s][iz],as,r,ps[s]);
}
}
}
AXPYTimer.Stop();
cp=c;
MatrixTimer.Start();
//Linop.HermOpAndNorm(p,mmp,d,qq); // d is used
// The below is faster on KNL
Linop.HermOp(p,mmp);
d=real(innerProduct(p,mmp));
MatrixTimer.Stop();
AXPYTimer.Start();
axpy(mmp,mass[0],p,mmp);
AXPYTimer.Stop();
RealD rn = norm2(p);
d += rn*mass[0];
bp=b;
b=-cp/d;
AXPYTimer.Start();
c=axpy_norm(r,b,mmp,r);
AXPYTimer.Stop();
// Toggle the recurrence history
bs[0] = b;
iz = 1-iz;
ShiftTimer.Start();
for(int s=1;s<nshift;s++){
if((!converged[s])){
RealD z0 = z[s][1-iz];
RealD z1 = z[s][iz];
z[s][iz] = z0*z1*bp
/ (b*a*(z1-z0) + z1*bp*(1- (mass[s]-mass[0])*b));
bs[s] = b*z[s][iz]/z0; // NB sign rel to Mike
}
}
ShiftTimer.Stop();
for(int s=0;s<nshift;s++){
int ss = s;
// Scope for optimisation here in case of "single".
// Could load psi[0] and pull all ps[s] in.
// if ( single ) ss=primary;
// Bandwith saving in single case is Ls * 3 -> 2+Ls, so ~ 3x saving
// Pipelined CG gain:
//
// New Kernel: Load r, vector of coeffs, vector of pointers ps
// New Kernel: Load psi[0], vector of coeffs, vector of pointers ps
// If can predict the coefficient bs then we can fuse these and avoid write reread cyce
// on ps[s].
// Before: 3 x npole + 3 x npole
// After : 2 x npole (ps[s]) => 3x speed up of multishift CG.
if( (!converged[s]) ) {
axpy(psi[ss],-bs[s]*alpha[s],ps[s],psi[ss]);
}
}
// Convergence checks
int all_converged = 1;
for(int s=0;s<nshift;s++){
if ( (!converged[s]) ){
IterationsToCompleteShift[s] = k;
RealD css = c * z[s][iz]* z[s][iz];
if(css<rsq[s]){
if ( ! converged[s] )
std::cout<<GridLogMessage<<"ConjugateGradientMultiShift k="<<k<<" Shift "<<s<<" has converged"<<std::endl;
converged[s]=1;
} else {
all_converged=0;
}
}
}
if ( all_converged ){
SolverTimer.Stop();
std::cout<<GridLogMessage<< "CGMultiShift: All shifts have converged iteration "<<k<<std::endl;
std::cout<<GridLogMessage<< "CGMultiShift: Checking solutions"<<std::endl;
// Check answers
for(int s=0; s < nshift; s++) {
Linop.HermOpAndNorm(psi[s],mmp,d,qq);
axpy(tmp,mass[s],psi[s],mmp);
axpy(r,-alpha[s],src,tmp);
RealD rn = norm2(r);
RealD cn = norm2(src);
TrueResidualShift[s] = std::sqrt(rn/cn);
std::cout<<GridLogMessage<<"CGMultiShift: shift["<<s<<"] true residual "<< TrueResidualShift[s] <<std::endl;
}
std::cout << GridLogMessage << "Time Breakdown "<<std::endl;
std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tAXPY " << AXPYTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tShift " << ShiftTimer.Elapsed() <<std::endl;
IterationsToComplete = k;
return;
}
}
// ugly hack
std::cout<<GridLogMessage<<"CG multi shift did not converge"<<std::endl;
// assert(0);
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,373 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ConjugateGradientMultiShift.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: Christopher Kelly <ckelly@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
//CK 2020: A variant of the multi-shift conjugate gradient with the matrix multiplication in single precision.
//The residual is stored in single precision, but the search directions and solution are stored in double precision.
//Every update_freq iterations the residual is corrected in double precision.
//For safety the a final regular CG is applied to clean up if necessary
//PB Pure single, then double fixup
template<class FieldD, class FieldF,
typename std::enable_if< getPrecision<FieldD>::value == 2, int>::type = 0,
typename std::enable_if< getPrecision<FieldF>::value == 1, int>::type = 0>
class ConjugateGradientMultiShiftMixedPrecCleanup : public OperatorMultiFunction<FieldD>,
public OperatorFunction<FieldD>
{
public:
using OperatorFunction<FieldD>::operator();
RealD Tolerance;
Integer MaxIterationsMshift;
Integer MaxIterations;
Integer IterationsToComplete; //Number of iterations the CG took to finish. Filled in upon completion
std::vector<int> IterationsToCompleteShift; // Iterations for this shift
int verbose;
MultiShiftFunction shifts;
std::vector<RealD> TrueResidualShift;
int ReliableUpdateFreq; //number of iterations between reliable updates
GridBase* SinglePrecGrid; //Grid for single-precision fields
LinearOperatorBase<FieldF> &Linop_f; //single precision
ConjugateGradientMultiShiftMixedPrecCleanup(Integer maxit, const MultiShiftFunction &_shifts,
GridBase* _SinglePrecGrid, LinearOperatorBase<FieldF> &_Linop_f,
int _ReliableUpdateFreq) :
MaxIterationsMshift(maxit), shifts(_shifts), SinglePrecGrid(_SinglePrecGrid), Linop_f(_Linop_f), ReliableUpdateFreq(_ReliableUpdateFreq),
MaxIterations(20000)
{
verbose=1;
IterationsToCompleteShift.resize(_shifts.order);
TrueResidualShift.resize(_shifts.order);
}
void operator() (LinearOperatorBase<FieldD> &Linop, const FieldD &src, FieldD &psi)
{
GridBase *grid = src.Grid();
int nshift = shifts.order;
std::vector<FieldD> results(nshift,grid);
(*this)(Linop,src,results,psi);
}
void operator() (LinearOperatorBase<FieldD> &Linop, const FieldD &src, std::vector<FieldD> &results, FieldD &psi)
{
int nshift = shifts.order;
(*this)(Linop,src,results);
psi = shifts.norm*src;
for(int i=0;i<nshift;i++){
psi = psi + shifts.residues[i]*results[i];
}
return;
}
void operator() (LinearOperatorBase<FieldD> &Linop_d, const FieldD &src_d, std::vector<FieldD> &psi_d)
{
GRID_TRACE("ConjugateGradientMultiShiftMixedPrecCleanup");
GridBase *DoublePrecGrid = src_d.Grid();
////////////////////////////////////////////////////////////////////////
// Convenience references to the info stored in "MultiShiftFunction"
////////////////////////////////////////////////////////////////////////
int nshift = shifts.order;
std::vector<RealD> &mass(shifts.poles); // Make references to array in "shifts"
std::vector<RealD> &mresidual(shifts.tolerances);
std::vector<RealD> alpha(nshift,1.0);
//Double precision search directions
FieldD p_d(DoublePrecGrid);
std::vector<FieldF> ps_f (nshift, SinglePrecGrid);// Search directions (single precision)
std::vector<FieldF> psi_f(nshift, SinglePrecGrid);// solutions (single precision)
FieldD tmp_d(DoublePrecGrid);
FieldD r_d(DoublePrecGrid);
FieldF r_f(SinglePrecGrid);
FieldD mmp_d(DoublePrecGrid);
assert(psi_d.size()==nshift);
assert(mass.size()==nshift);
assert(mresidual.size()==nshift);
// dynamic sized arrays on stack; 2d is a pain with vector
RealD bs[nshift];
RealD rsq[nshift];
RealD rsqf[nshift];
RealD z[nshift][2];
int converged[nshift];
const int primary =0;
//Primary shift fields CG iteration
RealD a,b,c,d;
RealD cp,bp,qq; //prev
// Matrix mult fields
FieldF p_f(SinglePrecGrid);
FieldF mmp_f(SinglePrecGrid);
// Check lightest mass
for(int s=0;s<nshift;s++){
assert( mass[s]>= mass[primary] );
converged[s]=0;
}
// Wire guess to zero
// Residuals "r" are src
// First search direction "p" is also src
cp = norm2(src_d);
// Handle trivial case of zero src.
if( cp == 0. ){
for(int s=0;s<nshift;s++){
psi_d[s] = Zero();
psi_f[s] = Zero();
IterationsToCompleteShift[s] = 1;
TrueResidualShift[s] = 0.;
}
return;
}
for(int s=0;s<nshift;s++){
rsq[s] = cp * mresidual[s] * mresidual[s];
rsqf[s] =rsq[s];
std::cout<<GridLogMessage<<"ConjugateGradientMultiShiftMixedPrecCleanup: shift "<< s <<" target resid "<<rsq[s]<<std::endl;
// ps_d[s] = src_d;
precisionChange(ps_f[s],src_d);
}
// r and p for primary
p_d = src_d; //primary copy --- make this a reference to ps_d to save axpys
r_d = p_d;
//MdagM+m[0]
precisionChange(p_f,p_d);
Linop_f.HermOpAndNorm(p_f,mmp_f,d,qq); // mmp = MdagM p d=real(dot(p, mmp)), qq=norm2(mmp)
precisionChange(tmp_d,mmp_f);
Linop_d.HermOpAndNorm(p_d,mmp_d,d,qq); // mmp = MdagM p d=real(dot(p, mmp)), qq=norm2(mmp)
tmp_d = tmp_d - mmp_d;
std::cout << " Testing operators match "<<norm2(mmp_d)<<" f "<<norm2(mmp_f)<<" diff "<< norm2(tmp_d)<<std::endl;
// assert(norm2(tmp_d)< 1.0e-4);
axpy(mmp_d,mass[0],p_d,mmp_d);
RealD rn = norm2(p_d);
d += rn*mass[0];
b = -cp /d;
// Set up the various shift variables
int iz=0;
z[0][1-iz] = 1.0;
z[0][iz] = 1.0;
bs[0] = b;
for(int s=1;s<nshift;s++){
z[s][1-iz] = 1.0;
z[s][iz] = 1.0/( 1.0 - b*(mass[s]-mass[0]));
bs[s] = b*z[s][iz];
}
// r += b[0] A.p[0]
// c= norm(r)
c=axpy_norm(r_d,b,mmp_d,r_d);
for(int s=0;s<nshift;s++) {
axpby(psi_d[s],0.,-bs[s]*alpha[s],src_d,src_d);
precisionChange(psi_f[s],psi_d[s]);
}
///////////////////////////////////////
// Timers
///////////////////////////////////////
GridStopWatch AXPYTimer, ShiftTimer, QRTimer, MatrixTimer, SolverTimer, PrecChangeTimer, CleanupTimer;
SolverTimer.Start();
// Iteration loop
int k;
for (k=1;k<=MaxIterationsMshift;k++){
a = c /cp;
AXPYTimer.Start();
axpy(p_d,a,p_d,r_d);
AXPYTimer.Stop();
PrecChangeTimer.Start();
precisionChange(r_f, r_d);
PrecChangeTimer.Stop();
AXPYTimer.Start();
for(int s=0;s<nshift;s++){
if ( ! converged[s] ) {
if (s==0){
axpy(ps_f[s],a,ps_f[s],r_f);
} else{
RealD as =a *z[s][iz]*bs[s] /(z[s][1-iz]*b);
axpby(ps_f[s],z[s][iz],as,r_f,ps_f[s]);
}
}
}
AXPYTimer.Stop();
cp=c;
PrecChangeTimer.Start();
precisionChange(p_f, p_d); //get back single prec search direction for linop
PrecChangeTimer.Stop();
MatrixTimer.Start();
Linop_f.HermOp(p_f,mmp_f);
MatrixTimer.Stop();
PrecChangeTimer.Start();
precisionChange(mmp_d, mmp_f); // From Float to Double
PrecChangeTimer.Stop();
d=real(innerProduct(p_d,mmp_d));
axpy(mmp_d,mass[0],p_d,mmp_d);
RealD rn = norm2(p_d);
d += rn*mass[0];
bp=b;
b=-cp/d;
// Toggle the recurrence history
bs[0] = b;
iz = 1-iz;
ShiftTimer.Start();
for(int s=1;s<nshift;s++){
if((!converged[s])){
RealD z0 = z[s][1-iz];
RealD z1 = z[s][iz];
z[s][iz] = z0*z1*bp
/ (b*a*(z1-z0) + z1*bp*(1- (mass[s]-mass[0])*b));
bs[s] = b*z[s][iz]/z0; // NB sign rel to Mike
}
}
ShiftTimer.Stop();
//Update single precision solutions
AXPYTimer.Start();
for(int s=0;s<nshift;s++){
int ss = s;
if( (!converged[s]) ) {
axpy(psi_f[ss],-bs[s]*alpha[s],ps_f[s],psi_f[ss]);
}
}
c = axpy_norm(r_d,b,mmp_d,r_d);
AXPYTimer.Stop();
// Convergence checks
int all_converged = 1;
for(int s=0;s<nshift;s++){
if ( (!converged[s]) ){
IterationsToCompleteShift[s] = k;
RealD css = c * z[s][iz]* z[s][iz];
if(css<rsqf[s]){
if ( ! converged[s] )
std::cout<<GridLogMessage<<"ConjugateGradientMultiShiftMixedPrecCleanup k="<<k<<" Shift "<<s<<" has converged"<<std::endl;
converged[s]=1;
} else {
all_converged=0;
}
}
}
if ( all_converged || k == MaxIterationsMshift-1){
SolverTimer.Stop();
for(int s=0;s<nshift;s++){
precisionChange(psi_d[s],psi_f[s]);
}
if ( all_converged ){
std::cout<<GridLogMessage<< "ConjugateGradientMultiShiftMixedPrecCleanup: All shifts have converged iteration "<<k<<std::endl;
std::cout<<GridLogMessage<< "ConjugateGradientMultiShiftMixedPrecCleanup: Checking solutions"<<std::endl;
} else {
std::cout<<GridLogMessage<< "ConjugateGradientMultiShiftMixedPrecCleanup: Not all shifts have converged iteration "<<k<<std::endl;
}
// Check answers
for(int s=0; s < nshift; s++) {
Linop_d.HermOpAndNorm(psi_d[s],mmp_d,d,qq);
axpy(tmp_d,mass[s],psi_d[s],mmp_d);
axpy(r_d,-alpha[s],src_d,tmp_d);
RealD rn = norm2(r_d);
RealD cn = norm2(src_d);
TrueResidualShift[s] = std::sqrt(rn/cn);
std::cout<<GridLogMessage<<"ConjugateGradientMultiShiftMixedPrecCleanup: shift["<<s<<"] true residual "<< TrueResidualShift[s] << " target " << mresidual[s] << std::endl;
//If we have not reached the desired tolerance, do a (mixed precision) CG cleanup
if(rn >= rsq[s]){
CleanupTimer.Start();
std::cout<<GridLogMessage<<"ConjugateGradientMultiShiftMixedPrecCleanup: performing cleanup step for shift " << s << std::endl;
//Setup linear operators for final cleanup
ConjugateGradientMultiShiftMixedPrecSupport::ShiftedLinop<FieldD> Linop_shift_d(Linop_d, mass[s]);
ConjugateGradientMultiShiftMixedPrecSupport::ShiftedLinop<FieldF> Linop_shift_f(Linop_f, mass[s]);
MixedPrecisionConjugateGradient<FieldD,FieldF> cg(mresidual[s], MaxIterations, MaxIterations, SinglePrecGrid, Linop_shift_f, Linop_shift_d);
cg(src_d, psi_d[s]);
TrueResidualShift[s] = cg.TrueResidual;
CleanupTimer.Stop();
}
}
std::cout << GridLogMessage << "ConjugateGradientMultiShiftMixedPrecCleanup: Time Breakdown for body"<<std::endl;
std::cout << GridLogMessage << "\tSolver " << SolverTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\t\tAXPY " << AXPYTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\t\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\t\tShift " << ShiftTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\t\tPrecision Change " << PrecChangeTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tFinal Cleanup " << CleanupTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tSolver+Cleanup " << SolverTimer.Elapsed() + CleanupTimer.Elapsed() << std::endl;
IterationsToComplete = k;
return;
}
}
std::cout<<GridLogMessage<<"CG multi shift did not converge"<<std::endl;
assert(0);
}
};
NAMESPACE_END(Grid);
@@ -1,416 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ConjugateGradientMultiShift.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: Christopher Kelly <ckelly@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CONJUGATE_GRADIENT_MULTI_SHIFT_MIXEDPREC_H
#define GRID_CONJUGATE_GRADIENT_MULTI_SHIFT_MIXEDPREC_H
NAMESPACE_BEGIN(Grid);
//CK 2020: A variant of the multi-shift conjugate gradient with the matrix multiplication in single precision.
//The residual is stored in single precision, but the search directions and solution are stored in double precision.
//Every update_freq iterations the residual is corrected in double precision.
//For safety the a final regular CG is applied to clean up if necessary
//Linop to add shift to input linop, used in cleanup CG
namespace ConjugateGradientMultiShiftMixedPrecSupport{
template<typename Field>
class ShiftedLinop: public LinearOperatorBase<Field>{
public:
LinearOperatorBase<Field> &linop_base;
RealD shift;
ShiftedLinop(LinearOperatorBase<Field> &_linop_base, RealD _shift): linop_base(_linop_base), shift(_shift){}
void OpDiag (const Field &in, Field &out){ assert(0); }
void OpDir (const Field &in, Field &out,int dir,int disp){ assert(0); }
void OpDirAll (const Field &in, std::vector<Field> &out){ assert(0); }
void Op (const Field &in, Field &out){ assert(0); }
void AdjOp (const Field &in, Field &out){ assert(0); }
void HermOp(const Field &in, Field &out){
linop_base.HermOp(in, out);
axpy(out, shift, in, out);
}
void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
HermOp(in,out);
ComplexD dot = innerProduct(in,out);
n1=real(dot);
n2=norm2(out);
}
};
};
template<class FieldD, class FieldF,
typename std::enable_if< getPrecision<FieldD>::value == 2, int>::type = 0,
typename std::enable_if< getPrecision<FieldF>::value == 1, int>::type = 0>
class ConjugateGradientMultiShiftMixedPrec : public OperatorMultiFunction<FieldD>,
public OperatorFunction<FieldD>
{
public:
using OperatorFunction<FieldD>::operator();
RealD Tolerance;
Integer MaxIterationsMshift;
Integer MaxIterations;
Integer IterationsToComplete; //Number of iterations the CG took to finish. Filled in upon completion
std::vector<int> IterationsToCompleteShift; // Iterations for this shift
int verbose;
MultiShiftFunction shifts;
std::vector<RealD> TrueResidualShift;
int ReliableUpdateFreq; //number of iterations between reliable updates
GridBase* SinglePrecGrid; //Grid for single-precision fields
LinearOperatorBase<FieldF> &Linop_f; //single precision
ConjugateGradientMultiShiftMixedPrec(Integer maxit, const MultiShiftFunction &_shifts,
GridBase* _SinglePrecGrid, LinearOperatorBase<FieldF> &_Linop_f,
int _ReliableUpdateFreq) :
MaxIterationsMshift(maxit), shifts(_shifts), SinglePrecGrid(_SinglePrecGrid), Linop_f(_Linop_f), ReliableUpdateFreq(_ReliableUpdateFreq),
MaxIterations(20000)
{
verbose=1;
IterationsToCompleteShift.resize(_shifts.order);
TrueResidualShift.resize(_shifts.order);
}
void operator() (LinearOperatorBase<FieldD> &Linop, const FieldD &src, FieldD &psi)
{
GridBase *grid = src.Grid();
int nshift = shifts.order;
std::vector<FieldD> results(nshift,grid);
(*this)(Linop,src,results,psi);
}
void operator() (LinearOperatorBase<FieldD> &Linop, const FieldD &src, std::vector<FieldD> &results, FieldD &psi)
{
int nshift = shifts.order;
(*this)(Linop,src,results);
psi = shifts.norm*src;
for(int i=0;i<nshift;i++){
psi = psi + shifts.residues[i]*results[i];
}
return;
}
void operator() (LinearOperatorBase<FieldD> &Linop_d, const FieldD &src_d, std::vector<FieldD> &psi_d)
{
GRID_TRACE("ConjugateGradientMultiShiftMixedPrec");
GridBase *DoublePrecGrid = src_d.Grid();
precisionChangeWorkspace pc_wk_s_to_d(DoublePrecGrid,SinglePrecGrid);
precisionChangeWorkspace pc_wk_d_to_s(SinglePrecGrid,DoublePrecGrid);
////////////////////////////////////////////////////////////////////////
// Convenience references to the info stored in "MultiShiftFunction"
////////////////////////////////////////////////////////////////////////
int nshift = shifts.order;
std::vector<RealD> &mass(shifts.poles); // Make references to array in "shifts"
std::vector<RealD> &mresidual(shifts.tolerances);
std::vector<RealD> alpha(nshift,1.0);
//Double precision search directions
FieldD p_d(DoublePrecGrid);
std::vector<FieldD> ps_d(nshift, DoublePrecGrid);// Search directions (double precision)
FieldD tmp_d(DoublePrecGrid);
FieldD r_d(DoublePrecGrid);
FieldD mmp_d(DoublePrecGrid);
assert(psi_d.size()==nshift);
assert(mass.size()==nshift);
assert(mresidual.size()==nshift);
// dynamic sized arrays on stack; 2d is a pain with vector
RealD bs[nshift];
RealD rsq[nshift];
RealD rsqf[nshift];
RealD z[nshift][2];
int converged[nshift];
const int primary =0;
//Primary shift fields CG iteration
RealD a,b,c,d;
RealD cp,bp,qq; //prev
// Matrix mult fields
FieldF p_f(SinglePrecGrid);
FieldF mmp_f(SinglePrecGrid);
// Check lightest mass
for(int s=0;s<nshift;s++){
assert( mass[s]>= mass[primary] );
converged[s]=0;
}
// Wire guess to zero
// Residuals "r" are src
// First search direction "p" is also src
cp = norm2(src_d);
// Handle trivial case of zero src.
if( cp == 0. ){
for(int s=0;s<nshift;s++){
psi_d[s] = Zero();
IterationsToCompleteShift[s] = 1;
TrueResidualShift[s] = 0.;
}
return;
}
for(int s=0;s<nshift;s++){
rsq[s] = cp * mresidual[s] * mresidual[s];
rsqf[s] =rsq[s];
std::cout<<GridLogMessage<<"ConjugateGradientMultiShiftMixedPrec: shift "<< s <<" target resid "<<rsq[s]<<std::endl;
ps_d[s] = src_d;
}
// r and p for primary
p_d = src_d; //primary copy --- make this a reference to ps_d to save axpys
r_d = p_d;
//MdagM+m[0]
precisionChange(p_f, p_d, pc_wk_d_to_s);
Linop_f.HermOpAndNorm(p_f,mmp_f,d,qq); // mmp = MdagM p d=real(dot(p, mmp)), qq=norm2(mmp)
precisionChange(tmp_d, mmp_f, pc_wk_s_to_d);
Linop_d.HermOpAndNorm(p_d,mmp_d,d,qq); // mmp = MdagM p d=real(dot(p, mmp)), qq=norm2(mmp)
tmp_d = tmp_d - mmp_d;
std::cout << " Testing operators match "<<norm2(mmp_d)<<" f "<<norm2(mmp_f)<<" diff "<< norm2(tmp_d)<<std::endl;
assert(norm2(tmp_d)< 1.0);
axpy(mmp_d,mass[0],p_d,mmp_d);
RealD rn = norm2(p_d);
d += rn*mass[0];
b = -cp /d;
// Set up the various shift variables
int iz=0;
z[0][1-iz] = 1.0;
z[0][iz] = 1.0;
bs[0] = b;
for(int s=1;s<nshift;s++){
z[s][1-iz] = 1.0;
z[s][iz] = 1.0/( 1.0 - b*(mass[s]-mass[0]));
bs[s] = b*z[s][iz];
}
// r += b[0] A.p[0]
// c= norm(r)
c=axpy_norm(r_d,b,mmp_d,r_d);
for(int s=0;s<nshift;s++) {
axpby(psi_d[s],0.,-bs[s]*alpha[s],src_d,src_d);
}
///////////////////////////////////////
// Timers
///////////////////////////////////////
GridStopWatch AXPYTimer, ShiftTimer, QRTimer, MatrixTimer, SolverTimer, PrecChangeTimer, CleanupTimer;
SolverTimer.Start();
// Iteration loop
int k;
for (k=1;k<=MaxIterationsMshift;k++){
a = c /cp;
AXPYTimer.Start();
axpy(p_d,a,p_d,r_d);
for(int s=0;s<nshift;s++){
if ( ! converged[s] ) {
if (s==0){
axpy(ps_d[s],a,ps_d[s],r_d);
} else{
RealD as =a *z[s][iz]*bs[s] /(z[s][1-iz]*b);
axpby(ps_d[s],z[s][iz],as,r_d,ps_d[s]);
}
}
}
AXPYTimer.Stop();
PrecChangeTimer.Start();
precisionChange(p_f, p_d, pc_wk_d_to_s); //get back single prec search direction for linop
PrecChangeTimer.Stop();
cp=c;
MatrixTimer.Start();
Linop_f.HermOp(p_f,mmp_f);
MatrixTimer.Stop();
PrecChangeTimer.Start();
precisionChange(mmp_d, mmp_f, pc_wk_s_to_d); // From Float to Double
PrecChangeTimer.Stop();
AXPYTimer.Start();
d=real(innerProduct(p_d,mmp_d));
axpy(mmp_d,mass[0],p_d,mmp_d);
AXPYTimer.Stop();
RealD rn = norm2(p_d);
d += rn*mass[0];
bp=b;
b=-cp/d;
// Toggle the recurrence history
bs[0] = b;
iz = 1-iz;
ShiftTimer.Start();
for(int s=1;s<nshift;s++){
if((!converged[s])){
RealD z0 = z[s][1-iz];
RealD z1 = z[s][iz];
z[s][iz] = z0*z1*bp
/ (b*a*(z1-z0) + z1*bp*(1- (mass[s]-mass[0])*b));
bs[s] = b*z[s][iz]/z0; // NB sign rel to Mike
}
}
ShiftTimer.Stop();
//Update double precision solutions
AXPYTimer.Start();
for(int s=0;s<nshift;s++){
int ss = s;
if( (!converged[s]) ) {
axpy(psi_d[ss],-bs[s]*alpha[s],ps_d[s],psi_d[ss]);
}
}
//Perform reliable update if necessary; otherwise update residual from single-prec mmp
c = axpy_norm(r_d,b,mmp_d,r_d);
AXPYTimer.Stop();
if(k % ReliableUpdateFreq == 0){
RealD c_old = c;
//Replace r with true residual
MatrixTimer.Start();
Linop_d.HermOp(psi_d[0],mmp_d);
MatrixTimer.Stop();
AXPYTimer.Start();
axpy(mmp_d,mass[0],psi_d[0],mmp_d);
c = axpy_norm(r_d, -1.0, mmp_d, src_d);
AXPYTimer.Stop();
std::cout<<GridLogMessage<<"ConjugateGradientMultiShiftMixedPrec k="<<k<< ", replaced |r|^2 = "<<c_old <<" with |r|^2 = "<<c<<std::endl;
}
// Convergence checks
int all_converged = 1;
for(int s=0;s<nshift;s++){
if ( (!converged[s]) ){
IterationsToCompleteShift[s] = k;
RealD css = c * z[s][iz]* z[s][iz];
if(css<rsqf[s]){
if ( ! converged[s] )
std::cout<<GridLogMessage<<"ConjugateGradientMultiShiftMixedPrec k="<<k<<" Shift "<<s<<" has converged"<<std::endl;
converged[s]=1;
} else {
all_converged=0;
}
}
}
if ( all_converged || k == MaxIterationsMshift-1){
SolverTimer.Stop();
if ( all_converged ){
std::cout<<GridLogMessage<< "ConjugateGradientMultiShiftMixedPrec: All shifts have converged iteration "<<k<<std::endl;
std::cout<<GridLogMessage<< "ConjugateGradientMultiShiftMixedPrec: Checking solutions"<<std::endl;
} else {
std::cout<<GridLogMessage<< "ConjugateGradientMultiShiftMixedPrec: Not all shifts have converged iteration "<<k<<std::endl;
}
// Check answers
for(int s=0; s < nshift; s++) {
Linop_d.HermOpAndNorm(psi_d[s],mmp_d,d,qq);
axpy(tmp_d,mass[s],psi_d[s],mmp_d);
axpy(r_d,-alpha[s],src_d,tmp_d);
RealD rn = norm2(r_d);
RealD cn = norm2(src_d);
TrueResidualShift[s] = std::sqrt(rn/cn);
std::cout<<GridLogMessage<<"ConjugateGradientMultiShiftMixedPrec: shift["<<s<<"] true residual "<< TrueResidualShift[s] << " target " << mresidual[s] << std::endl;
//If we have not reached the desired tolerance, do a (mixed precision) CG cleanup
if(rn >= rsq[s]){
CleanupTimer.Start();
std::cout<<GridLogMessage<<"ConjugateGradientMultiShiftMixedPrec: performing cleanup step for shift " << s << std::endl;
//Setup linear operators for final cleanup
ConjugateGradientMultiShiftMixedPrecSupport::ShiftedLinop<FieldD> Linop_shift_d(Linop_d, mass[s]);
ConjugateGradientMultiShiftMixedPrecSupport::ShiftedLinop<FieldF> Linop_shift_f(Linop_f, mass[s]);
MixedPrecisionConjugateGradient<FieldD,FieldF> cg(mresidual[s], MaxIterations, MaxIterations, SinglePrecGrid, Linop_shift_f, Linop_shift_d);
cg(src_d, psi_d[s]);
TrueResidualShift[s] = cg.TrueResidual;
CleanupTimer.Stop();
}
}
std::cout << GridLogMessage << "ConjugateGradientMultiShiftMixedPrec: Time Breakdown for body"<<std::endl;
std::cout << GridLogMessage << "\tSolver " << SolverTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\t\tAXPY " << AXPYTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\t\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\t\tShift " << ShiftTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\t\tPrecision Change " << PrecChangeTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tFinal Cleanup " << CleanupTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tSolver+Cleanup " << SolverTimer.Elapsed() + CleanupTimer.Elapsed() << std::endl;
IterationsToComplete = k;
return;
}
}
std::cout<<GridLogMessage<<"CG multi shift did not converge"<<std::endl;
assert(0);
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,277 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ConjugateGradientReliableUpdate.h
Copyright (C) 2015
Author: Christopher Kelly <ckelly@phys.columbia.edu>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CONJUGATE_GRADIENT_RELIABLE_UPDATE_H
#define GRID_CONJUGATE_GRADIENT_RELIABLE_UPDATE_H
NAMESPACE_BEGIN(Grid);
template<class FieldD,class FieldF,
typename std::enable_if< getPrecision<FieldD>::value == 2, int>::type = 0,
typename std::enable_if< getPrecision<FieldF>::value == 1, int>::type = 0>
class ConjugateGradientReliableUpdate : public LinearFunction<FieldD> {
public:
bool ErrorOnNoConverge; // throw an assert when the CG fails to converge.
// Defaults true.
RealD Tolerance;
Integer MaxIterations;
Integer IterationsToComplete; //Number of iterations the CG took to finish. Filled in upon completion
Integer ReliableUpdatesPerformed;
bool DoFinalCleanup; //Final DP cleanup, defaults to true
Integer IterationsToCleanup; //Final DP cleanup step iterations
LinearOperatorBase<FieldF> &Linop_f;
LinearOperatorBase<FieldD> &Linop_d;
GridBase* SinglePrecGrid;
RealD Delta; //reliable update parameter. A reliable update is performed when the residual drops by a factor of Delta relative to its value at the last update
//Optional ability to switch to a different linear operator once the tolerance reaches a certain point. Useful for single/half -> single/single
LinearOperatorBase<FieldF> *Linop_fallback;
RealD fallback_transition_tol;
ConjugateGradientReliableUpdate(RealD tol, Integer maxit, RealD _delta, GridBase* _sp_grid, LinearOperatorBase<FieldF> &_Linop_f, LinearOperatorBase<FieldD> &_Linop_d, bool err_on_no_conv = true)
: Tolerance(tol),
MaxIterations(maxit),
Delta(_delta),
Linop_f(_Linop_f),
Linop_d(_Linop_d),
SinglePrecGrid(_sp_grid),
ErrorOnNoConverge(err_on_no_conv),
DoFinalCleanup(true),
Linop_fallback(NULL)
{
assert(Delta > 0. && Delta < 1. && "Expect 0 < Delta < 1");
};
void setFallbackLinop(LinearOperatorBase<FieldF> &_Linop_fallback, const RealD _fallback_transition_tol){
Linop_fallback = &_Linop_fallback;
fallback_transition_tol = _fallback_transition_tol;
}
void operator()(const FieldD &src, FieldD &psi) {
GRID_TRACE("ConjugateGradientReliableUpdate");
LinearOperatorBase<FieldF> *Linop_f_use = &Linop_f;
bool using_fallback = false;
psi.Checkerboard() = src.Checkerboard();
conformable(psi, src);
RealD cp, c, a, d, b, ssq, qq, b_pred;
FieldD p(src);
FieldD mmp(src);
FieldD r(src);
// Initial residual computation & set up
RealD guess = norm2(psi);
assert(std::isnan(guess) == 0);
Linop_d.HermOpAndNorm(psi, mmp, d, b);
r = src - mmp;
p = r;
a = norm2(p);
cp = a;
ssq = norm2(src);
std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: guess " << guess << std::endl;
std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: src " << ssq << std::endl;
std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: mp " << d << std::endl;
std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: mmp " << b << std::endl;
std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: cp,r " << cp << std::endl;
std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: p " << a << std::endl;
RealD rsq = Tolerance * Tolerance * ssq;
// Check if guess is really REALLY good :)
if (cp <= rsq) {
std::cout << GridLogMessage << "ConjugateGradientReliableUpdate guess was REALLY good\n";
std::cout << GridLogMessage << "\tComputed residual " << std::sqrt(cp / ssq)<<std::endl;
return;
}
//Single prec initialization
precisionChangeWorkspace pc_wk_sp_to_dp(src.Grid(), SinglePrecGrid);
precisionChangeWorkspace pc_wk_dp_to_sp(SinglePrecGrid, src.Grid());
FieldF r_f(SinglePrecGrid);
r_f.Checkerboard() = r.Checkerboard();
precisionChange(r_f, r, pc_wk_dp_to_sp);
FieldF psi_f(r_f);
psi_f = Zero();
FieldF p_f(r_f);
FieldF mmp_f(r_f);
RealD MaxResidSinceLastRelUp = cp; //initial residual
std::cout << GridLogIterative << std::setprecision(4)
<< "ConjugateGradient: k=0 residual " << cp << " target " << rsq << std::endl;
GridStopWatch LinalgTimer;
GridStopWatch MatrixTimer;
GridStopWatch SolverTimer;
GridStopWatch PrecChangeTimer;
SolverTimer.Start();
int k = 0;
int l = 0;
for (k = 1; k <= MaxIterations; k++) {
c = cp;
MatrixTimer.Start();
Linop_f_use->HermOpAndNorm(p_f, mmp_f, d, qq);
MatrixTimer.Stop();
LinalgTimer.Start();
a = c / d;
b_pred = a * (a * qq - d) / c;
cp = axpy_norm(r_f, -a, mmp_f, r_f);
b = cp / c;
// Fuse these loops ; should be really easy
psi_f = a * p_f + psi_f;
//p_f = p_f * b + r_f;
LinalgTimer.Stop();
std::cout << GridLogIterative << "ConjugateGradientReliableUpdate: Iteration " << k
<< " residual " << cp << " target " << rsq << std::endl;
std::cout << GridLogDebug << "a = "<< a << " b_pred = "<< b_pred << " b = "<< b << std::endl;
std::cout << GridLogDebug << "qq = "<< qq << " d = "<< d << " c = "<< c << std::endl;
if(cp > MaxResidSinceLastRelUp){
std::cout << GridLogIterative << "ConjugateGradientReliableUpdate: updating MaxResidSinceLastRelUp : " << MaxResidSinceLastRelUp << " -> " << cp << std::endl;
MaxResidSinceLastRelUp = cp;
}
// Stopping condition
if (cp <= rsq) {
//Although not written in the paper, I assume that I have to add on the final solution
PrecChangeTimer.Start();
precisionChange(mmp, psi_f, pc_wk_sp_to_dp);
PrecChangeTimer.Stop();
psi = psi + mmp;
SolverTimer.Stop();
Linop_d.HermOpAndNorm(psi, mmp, d, qq);
p = mmp - src;
RealD srcnorm = std::sqrt(norm2(src));
RealD resnorm = std::sqrt(norm2(p));
RealD true_residual = resnorm / srcnorm;
std::cout << GridLogMessage << "ConjugateGradientReliableUpdate Converged on iteration " << k << " after " << l << " reliable updates" << std::endl;
std::cout << GridLogMessage << "\tComputed residual " << std::sqrt(cp / ssq)<<std::endl;
std::cout << GridLogMessage << "\tTrue residual " << true_residual<<std::endl;
std::cout << GridLogMessage << "\tTarget " << Tolerance << std::endl;
std::cout << GridLogMessage << "Time breakdown "<<std::endl;
std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tLinalg " << LinalgTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tPrecChange " << PrecChangeTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tPrecChange avg time " << PrecChangeTimer.Elapsed()/(2*l+1) <<std::endl;
IterationsToComplete = k;
ReliableUpdatesPerformed = l;
if(DoFinalCleanup){
//Do a final CG to cleanup
std::cout << GridLogMessage << "ConjugateGradientReliableUpdate performing final cleanup.\n";
ConjugateGradient<FieldD> CG(Tolerance,MaxIterations);
CG.ErrorOnNoConverge = ErrorOnNoConverge;
CG(Linop_d,src,psi);
IterationsToCleanup = CG.IterationsToComplete;
}
else if (ErrorOnNoConverge) assert(true_residual / Tolerance < 10000.0);
std::cout << GridLogMessage << "ConjugateGradientReliableUpdate complete.\n";
return;
}
else if(cp < Delta * MaxResidSinceLastRelUp) { //reliable update
std::cout << GridLogMessage << "ConjugateGradientReliableUpdate "
<< cp << "(residual) < " << Delta << "(Delta) * " << MaxResidSinceLastRelUp << "(MaxResidSinceLastRelUp) on iteration " << k << " : performing reliable update\n";
PrecChangeTimer.Start();
precisionChange(mmp, psi_f, pc_wk_sp_to_dp);
PrecChangeTimer.Stop();
psi = psi + mmp;
MatrixTimer.Start();
Linop_d.HermOpAndNorm(psi, mmp, d, qq);
MatrixTimer.Stop();
r = src - mmp;
psi_f = Zero();
PrecChangeTimer.Start();
precisionChange(r_f, r, pc_wk_dp_to_sp);
PrecChangeTimer.Stop();
cp = norm2(r);
MaxResidSinceLastRelUp = cp;
b = cp/c;
std::cout << GridLogMessage << "ConjugateGradientReliableUpdate new residual " << cp << std::endl;
l = l+1;
}
p_f = p_f * b + r_f; //update search vector after reliable update appears to help convergence
if(!using_fallback && Linop_fallback != NULL && cp < fallback_transition_tol){
std::cout << GridLogMessage << "ConjugateGradientReliableUpdate switching to fallback linear operator on iteration " << k << " at residual " << cp << std::endl;
Linop_f_use = Linop_fallback;
using_fallback = true;
}
}
std::cout << GridLogMessage << "ConjugateGradientReliableUpdate did NOT converge"
<< std::endl;
if (ErrorOnNoConverge) assert(0);
IterationsToComplete = k;
ReliableUpdatesPerformed = l;
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,113 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ConjugateResidual.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CONJUGATE_RESIDUAL_H
#define GRID_CONJUGATE_RESIDUAL_H
NAMESPACE_BEGIN(Grid);
/////////////////////////////////////////////////////////////
// Base classes for iterative processes based on operators
// single input vec, single output vec.
/////////////////////////////////////////////////////////////
template<class Field>
class ConjugateResidual : public OperatorFunction<Field> {
public:
using OperatorFunction<Field>::operator();
RealD Tolerance;
Integer MaxIterations;
int verbose;
ConjugateResidual(RealD tol,Integer maxit) : Tolerance(tol), MaxIterations(maxit) {
verbose=0;
};
void operator() (LinearOperatorBase<Field> &Linop,const Field &src, Field &psi){
RealD a, b; // c, d;
RealD cp, ssq,rsq;
RealD rAr, rAAr, rArp;
RealD pAp, pAAp;
GridBase *grid = src.Grid();
psi=Zero();
Field r(grid), p(grid), Ap(grid), Ar(grid);
r=src;
p=src;
Linop.HermOpAndNorm(p,Ap,pAp,pAAp);
Linop.HermOpAndNorm(r,Ar,rAr,rAAr);
cp =norm2(r);
ssq=norm2(src);
rsq=Tolerance*Tolerance*ssq;
if (verbose) std::cout<<GridLogMessage<<"ConjugateResidual: iteration " <<0<<" residual "<<cp<< " target"<< rsq<<std::endl;
for(int k=1;k<MaxIterations;k++){
a = rAr/pAAp;
axpy(psi,a,p,psi);
cp = axpy_norm(r,-a,Ap,r);
rArp=rAr;
Linop.HermOpAndNorm(r,Ar,rAr,rAAr);
b =rAr/rArp;
axpy(p,b,p,r);
pAAp=axpy_norm(Ap,b,Ap,Ar);
if(verbose) std::cout<<GridLogMessage<<"ConjugateResidual: iteration " <<k<<" residual "<<cp<< " target"<< rsq<<std::endl;
if(cp<rsq) {
Linop.HermOp(psi,Ap);
axpy(r,-1.0,src,Ap);
RealD true_resid = norm2(r)/ssq;
std::cout<<GridLogMessage<<"ConjugateResidual: Converged on iteration " <<k
<< " computed residual "<<std::sqrt(cp/ssq)
<< " true residual "<<std::sqrt(true_resid)
<< " target " <<Tolerance <<std::endl;
return;
}
}
std::cout<<GridLogMessage<<"ConjugateResidual did NOT converge"<<std::endl;
assert(0);
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,258 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/FlexibleCommunicationAvoidingGeneralisedMinimalResidual.h
Copyright (C) 2015
Author: Daniel Richtmann <daniel.richtmann@ur.de>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_FLEXIBLE_COMMUNICATION_AVOIDING_GENERALISED_MINIMAL_RESIDUAL_H
#define GRID_FLEXIBLE_COMMUNICATION_AVOIDING_GENERALISED_MINIMAL_RESIDUAL_H
namespace Grid {
template<class Field>
class FlexibleCommunicationAvoidingGeneralisedMinimalResidual : public OperatorFunction<Field> {
public:
using OperatorFunction<Field>::operator();
bool ErrorOnNoConverge; // Throw an assert when FCAGMRES fails to converge,
// defaults to true
RealD Tolerance;
Integer MaxIterations;
Integer RestartLength;
Integer MaxNumberOfRestarts;
Integer IterationCount; // Number of iterations the FCAGMRES took to finish,
// filled in upon completion
GridStopWatch MatrixTimer;
GridStopWatch PrecTimer;
GridStopWatch LinalgTimer;
GridStopWatch QrTimer;
GridStopWatch CompSolutionTimer;
Eigen::MatrixXcd H;
std::vector<ComplexD> y;
std::vector<ComplexD> gamma;
std::vector<ComplexD> c;
std::vector<ComplexD> s;
LinearFunction<Field> &Preconditioner;
FlexibleCommunicationAvoidingGeneralisedMinimalResidual(RealD tol,
Integer maxit,
LinearFunction<Field> &Prec,
Integer restart_length,
bool err_on_no_conv = true)
: Tolerance(tol)
, MaxIterations(maxit)
, RestartLength(restart_length)
, MaxNumberOfRestarts(MaxIterations/RestartLength + ((MaxIterations%RestartLength == 0) ? 0 : 1))
, ErrorOnNoConverge(err_on_no_conv)
, H(Eigen::MatrixXcd::Zero(RestartLength, RestartLength + 1)) // sizes taken from DD-αAMG code base
, y(RestartLength + 1, 0.)
, gamma(RestartLength + 1, 0.)
, c(RestartLength + 1, 0.)
, s(RestartLength + 1, 0.)
, Preconditioner(Prec) {};
void operator()(LinearOperatorBase<Field> &LinOp, const Field &src, Field &psi) {
std::cout << GridLogWarning << "This algorithm currently doesn't differ from regular FGMRES" << std::endl;
psi.Checkerboard() = src.Checkerboard();
conformable(psi, src);
RealD guess = norm2(psi);
assert(std::isnan(guess) == 0);
RealD cp;
RealD ssq = norm2(src);
RealD rsq = Tolerance * Tolerance * ssq;
Field r(src.Grid());
std::cout << std::setprecision(4) << std::scientific;
std::cout << GridLogIterative << "FlexibleCommunicationAvoidingGeneralisedMinimalResidual: guess " << guess << std::endl;
std::cout << GridLogIterative << "FlexibleCommunicationAvoidingGeneralisedMinimalResidual: src " << ssq << std::endl;
PrecTimer.Reset();
MatrixTimer.Reset();
LinalgTimer.Reset();
QrTimer.Reset();
CompSolutionTimer.Reset();
GridStopWatch SolverTimer;
SolverTimer.Start();
IterationCount = 0;
for (int k=0; k<MaxNumberOfRestarts; k++) {
cp = outerLoopBody(LinOp, src, psi, rsq);
// Stopping condition
if (cp <= rsq) {
SolverTimer.Stop();
LinOp.Op(psi,r);
axpy(r,-1.0,src,r);
RealD srcnorm = sqrt(ssq);
RealD resnorm = sqrt(norm2(r));
RealD true_residual = resnorm / srcnorm;
std::cout << GridLogMessage << "FlexibleCommunicationAvoidingGeneralisedMinimalResidual: Converged on iteration " << IterationCount
<< " computed residual " << sqrt(cp / ssq)
<< " true residual " << true_residual
<< " target " << Tolerance << std::endl;
std::cout << GridLogMessage << "FCAGMRES Time elapsed: Total " << SolverTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "FCAGMRES Time elapsed: Precon " << PrecTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "FCAGMRES Time elapsed: Matrix " << MatrixTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "FCAGMRES Time elapsed: Linalg " << LinalgTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "FCAGMRES Time elapsed: QR " << QrTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "FCAGMRES Time elapsed: CompSol " << CompSolutionTimer.Elapsed() << std::endl;
return;
}
}
std::cout << GridLogMessage << "FlexibleCommunicationAvoidingGeneralisedMinimalResidual did NOT converge" << std::endl;
if (ErrorOnNoConverge)
assert(0);
}
RealD outerLoopBody(LinearOperatorBase<Field> &LinOp, const Field &src, Field &psi, RealD rsq) {
RealD cp = 0;
Field w(src.Grid());
Field r(src.Grid());
// these should probably be made class members so that they are only allocated once, not in every restart
std::vector<Field> v(RestartLength + 1, src.Grid()); for (auto &elem : v) elem = Zero();
std::vector<Field> z(RestartLength + 1, src.Grid()); for (auto &elem : z) elem = Zero();
MatrixTimer.Start();
LinOp.Op(psi, w);
MatrixTimer.Stop();
LinalgTimer.Start();
r = src - w;
gamma[0] = sqrt(norm2(r));
v[0] = (1. / gamma[0]) * r;
LinalgTimer.Stop();
for (int i=0; i<RestartLength; i++) {
IterationCount++;
arnoldiStep(LinOp, v, z, w, i);
qrUpdate(i);
cp = norm(gamma[i+1]);
std::cout << GridLogIterative << "FlexibleCommunicationAvoidingGeneralisedMinimalResidual: Iteration " << IterationCount
<< " residual " << cp << " target " << rsq << std::endl;
if ((i == RestartLength - 1) || (IterationCount == MaxIterations) || (cp <= rsq)) {
computeSolution(z, psi, i);
return cp;
}
}
assert(0); // Never reached
return cp;
}
void arnoldiStep(LinearOperatorBase<Field> &LinOp, std::vector<Field> &v, std::vector<Field> &z, Field &w, int iter) {
PrecTimer.Start();
Preconditioner(v[iter], z[iter]);
PrecTimer.Stop();
MatrixTimer.Start();
LinOp.Op(z[iter], w);
MatrixTimer.Stop();
LinalgTimer.Start();
for (int i = 0; i <= iter; ++i) {
H(iter, i) = innerProduct(v[i], w);
w = w - ComplexD(H(iter, i)) * v[i];
}
H(iter, iter + 1) = sqrt(norm2(w));
v[iter + 1] = ComplexD(1. / H(iter, iter + 1)) * w;
LinalgTimer.Stop();
}
void qrUpdate(int iter) {
QrTimer.Start();
for (int i = 0; i < iter ; ++i) {
auto tmp = -s[i] * ComplexD(H(iter, i)) + c[i] * ComplexD(H(iter, i + 1));
H(iter, i) = conjugate(c[i]) * ComplexD(H(iter, i)) + conjugate(s[i]) * ComplexD(H(iter, i + 1));
H(iter, i + 1) = tmp;
}
// Compute new Givens Rotation
auto nu = sqrt(std::norm(H(iter, iter)) + std::norm(H(iter, iter + 1)));
c[iter] = H(iter, iter) / nu;
s[iter] = H(iter, iter + 1) / nu;
// Apply new Givens rotation
H(iter, iter) = nu;
H(iter, iter + 1) = 0.;
gamma[iter + 1] = -s[iter] * gamma[iter];
gamma[iter] = conjugate(c[iter]) * gamma[iter];
QrTimer.Stop();
}
void computeSolution(std::vector<Field> const &z, Field &psi, int iter) {
CompSolutionTimer.Start();
for (int i = iter; i >= 0; i--) {
y[i] = gamma[i];
for (int k = i + 1; k <= iter; k++)
y[i] = y[i] - ComplexD(H(k, i)) * y[k];
y[i] = y[i] / ComplexD(H(i, i));
}
for (int i = 0; i <= iter; i++)
psi = psi + z[i] * y[i];
CompSolutionTimer.Stop();
}
};
}
#endif
@@ -1,256 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/FlexibleGeneralisedMinimalResidual.h
Copyright (C) 2015
Author: Daniel Richtmann <daniel.richtmann@ur.de>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_FLEXIBLE_GENERALISED_MINIMAL_RESIDUAL_H
#define GRID_FLEXIBLE_GENERALISED_MINIMAL_RESIDUAL_H
namespace Grid {
template<class Field>
class FlexibleGeneralisedMinimalResidual : public OperatorFunction<Field> {
public:
using OperatorFunction<Field>::operator();
bool ErrorOnNoConverge; // Throw an assert when FGMRES fails to converge,
// defaults to true
RealD Tolerance;
Integer MaxIterations;
Integer RestartLength;
Integer MaxNumberOfRestarts;
Integer IterationCount; // Number of iterations the FGMRES took to finish,
// filled in upon completion
GridStopWatch MatrixTimer;
GridStopWatch PrecTimer;
GridStopWatch LinalgTimer;
GridStopWatch QrTimer;
GridStopWatch CompSolutionTimer;
Eigen::MatrixXcd H;
std::vector<ComplexD> y;
std::vector<ComplexD> gamma;
std::vector<ComplexD> c;
std::vector<ComplexD> s;
LinearFunction<Field> &Preconditioner;
FlexibleGeneralisedMinimalResidual(RealD tol,
Integer maxit,
LinearFunction<Field> &Prec,
Integer restart_length,
bool err_on_no_conv = true)
: Tolerance(tol)
, MaxIterations(maxit)
, RestartLength(restart_length)
, MaxNumberOfRestarts(MaxIterations/RestartLength + ((MaxIterations%RestartLength == 0) ? 0 : 1))
, ErrorOnNoConverge(err_on_no_conv)
, H(Eigen::MatrixXcd::Zero(RestartLength, RestartLength + 1)) // sizes taken from DD-αAMG code base
, y(RestartLength + 1, 0.)
, gamma(RestartLength + 1, 0.)
, c(RestartLength + 1, 0.)
, s(RestartLength + 1, 0.)
, Preconditioner(Prec) {};
void operator()(LinearOperatorBase<Field> &LinOp, const Field &src, Field &psi) {
psi.Checkerboard() = src.Checkerboard();
conformable(psi, src);
RealD guess = norm2(psi);
assert(std::isnan(guess) == 0);
RealD cp;
RealD ssq = norm2(src);
RealD rsq = Tolerance * Tolerance * ssq;
Field r(src.Grid());
std::cout << std::setprecision(4) << std::scientific;
std::cout << GridLogIterative << "FlexibleGeneralisedMinimalResidual: guess " << guess << std::endl;
std::cout << GridLogIterative << "FlexibleGeneralisedMinimalResidual: src " << ssq << std::endl;
PrecTimer.Reset();
MatrixTimer.Reset();
LinalgTimer.Reset();
QrTimer.Reset();
CompSolutionTimer.Reset();
GridStopWatch SolverTimer;
SolverTimer.Start();
IterationCount = 0;
for (int k=0; k<MaxNumberOfRestarts; k++) {
cp = outerLoopBody(LinOp, src, psi, rsq);
// Stopping condition
if (cp <= rsq) {
SolverTimer.Stop();
LinOp.Op(psi,r);
axpy(r,-1.0,src,r);
RealD srcnorm = sqrt(ssq);
RealD resnorm = sqrt(norm2(r));
RealD true_residual = resnorm / srcnorm;
std::cout << GridLogMessage << "FlexibleGeneralisedMinimalResidual: Converged on iteration " << IterationCount
<< " computed residual " << sqrt(cp / ssq)
<< " true residual " << true_residual
<< " target " << Tolerance << std::endl;
std::cout << GridLogMessage << "FGMRES Time elapsed: Total " << SolverTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "FGMRES Time elapsed: Precon " << PrecTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "FGMRES Time elapsed: Matrix " << MatrixTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "FGMRES Time elapsed: Linalg " << LinalgTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "FGMRES Time elapsed: QR " << QrTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "FGMRES Time elapsed: CompSol " << CompSolutionTimer.Elapsed() << std::endl;
return;
}
}
std::cout << GridLogMessage << "FlexibleGeneralisedMinimalResidual did NOT converge" << std::endl;
if (ErrorOnNoConverge)
assert(0);
}
RealD outerLoopBody(LinearOperatorBase<Field> &LinOp, const Field &src, Field &psi, RealD rsq) {
RealD cp = 0;
Field w(src.Grid());
Field r(src.Grid());
// these should probably be made class members so that they are only allocated once, not in every restart
std::vector<Field> v(RestartLength + 1, src.Grid()); for (auto &elem : v) elem = Zero();
std::vector<Field> z(RestartLength + 1, src.Grid()); for (auto &elem : z) elem = Zero();
MatrixTimer.Start();
LinOp.Op(psi, w);
MatrixTimer.Stop();
LinalgTimer.Start();
r = src - w;
gamma[0] = sqrt(norm2(r));
v[0] = (1. / gamma[0]) * r;
LinalgTimer.Stop();
for (int i=0; i<RestartLength; i++) {
IterationCount++;
arnoldiStep(LinOp, v, z, w, i);
qrUpdate(i);
cp = norm(gamma[i+1]);
std::cout << GridLogIterative << "FlexibleGeneralisedMinimalResidual: Iteration " << IterationCount
<< " residual " << cp << " target " << rsq << std::endl;
if ((i == RestartLength - 1) || (IterationCount == MaxIterations) || (cp <= rsq)) {
computeSolution(z, psi, i);
return cp;
}
}
assert(0); // Never reached
return cp;
}
void arnoldiStep(LinearOperatorBase<Field> &LinOp, std::vector<Field> &v, std::vector<Field> &z, Field &w, int iter) {
PrecTimer.Start();
Preconditioner(v[iter], z[iter]);
PrecTimer.Stop();
MatrixTimer.Start();
LinOp.Op(z[iter], w);
MatrixTimer.Stop();
LinalgTimer.Start();
for (int i = 0; i <= iter; ++i) {
H(iter, i) = innerProduct(v[i], w);
w = w - ComplexD(H(iter, i)) * v[i];
}
H(iter, iter + 1) = sqrt(norm2(w));
v[iter + 1] = ComplexD(1. / H(iter, iter + 1)) * w;
LinalgTimer.Stop();
}
void qrUpdate(int iter) {
QrTimer.Start();
for (int i = 0; i < iter ; ++i) {
auto tmp = -s[i] * ComplexD(H(iter, i)) + c[i] * ComplexD(H(iter, i + 1));
H(iter, i) = conjugate(c[i]) * ComplexD(H(iter, i)) + conjugate(s[i]) * ComplexD(H(iter, i + 1));
H(iter, i + 1) = tmp;
}
// Compute new Givens Rotation
auto nu = sqrt(std::norm(H(iter, iter)) + std::norm(H(iter, iter + 1)));
c[iter] = H(iter, iter) / nu;
s[iter] = H(iter, iter + 1) / nu;
// Apply new Givens rotation
H(iter, iter) = nu;
H(iter, iter + 1) = 0.;
gamma[iter + 1] = -s[iter] * gamma[iter];
gamma[iter] = conjugate(c[iter]) * gamma[iter];
QrTimer.Stop();
}
void computeSolution(std::vector<Field> const &z, Field &psi, int iter) {
CompSolutionTimer.Start();
for (int i = iter; i >= 0; i--) {
y[i] = gamma[i];
for (int k = i + 1; k <= iter; k++)
y[i] = y[i] - ComplexD(H(k, i)) * y[k];
y[i] = y[i] / ComplexD(H(i, i));
}
for (int i = 0; i <= iter; i++)
psi = psi + z[i] * y[i];
CompSolutionTimer.Stop();
}
};
}
#endif
@@ -1,244 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/GeneralisedMinimalResidual.h
Copyright (C) 2015
Author: Daniel Richtmann <daniel.richtmann@ur.de>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_GENERALISED_MINIMAL_RESIDUAL_H
#define GRID_GENERALISED_MINIMAL_RESIDUAL_H
namespace Grid {
template<class Field>
class GeneralisedMinimalResidual : public OperatorFunction<Field> {
public:
using OperatorFunction<Field>::operator();
bool ErrorOnNoConverge; // Throw an assert when GMRES fails to converge,
// defaults to true
RealD Tolerance;
Integer MaxIterations;
Integer RestartLength;
Integer MaxNumberOfRestarts;
Integer IterationCount; // Number of iterations the GMRES took to finish,
// filled in upon completion
GridStopWatch MatrixTimer;
GridStopWatch LinalgTimer;
GridStopWatch QrTimer;
GridStopWatch CompSolutionTimer;
Eigen::MatrixXcd H;
std::vector<ComplexD> y;
std::vector<ComplexD> gamma;
std::vector<ComplexD> c;
std::vector<ComplexD> s;
GeneralisedMinimalResidual(RealD tol,
Integer maxit,
Integer restart_length,
bool err_on_no_conv = true)
: Tolerance(tol)
, MaxIterations(maxit)
, RestartLength(restart_length)
, MaxNumberOfRestarts(MaxIterations/RestartLength + ((MaxIterations%RestartLength == 0) ? 0 : 1))
, ErrorOnNoConverge(err_on_no_conv)
, H(Eigen::MatrixXcd::Zero(RestartLength, RestartLength + 1)) // sizes taken from DD-αAMG code base
, y(RestartLength + 1, 0.)
, gamma(RestartLength + 1, 0.)
, c(RestartLength + 1, 0.)
, s(RestartLength + 1, 0.) {};
void operator()(LinearOperatorBase<Field> &LinOp, const Field &src, Field &psi) {
psi.Checkerboard() = src.Checkerboard();
conformable(psi, src);
RealD guess = norm2(psi);
assert(std::isnan(guess) == 0);
RealD cp;
RealD ssq = norm2(src);
RealD rsq = Tolerance * Tolerance * ssq;
Field r(src.Grid());
std::cout << std::setprecision(4) << std::scientific;
std::cout << GridLogIterative << "GeneralisedMinimalResidual: guess " << guess << std::endl;
std::cout << GridLogIterative << "GeneralisedMinimalResidual: src " << ssq << std::endl;
MatrixTimer.Reset();
LinalgTimer.Reset();
QrTimer.Reset();
CompSolutionTimer.Reset();
GridStopWatch SolverTimer;
SolverTimer.Start();
IterationCount = 0;
for (int k=0; k<MaxNumberOfRestarts; k++) {
cp = outerLoopBody(LinOp, src, psi, rsq);
// Stopping condition
if (cp <= rsq) {
SolverTimer.Stop();
LinOp.Op(psi,r);
axpy(r,-1.0,src,r);
RealD srcnorm = sqrt(ssq);
RealD resnorm = sqrt(norm2(r));
RealD true_residual = resnorm / srcnorm;
std::cout << GridLogMessage << "GeneralisedMinimalResidual: Converged on iteration " << IterationCount
<< " computed residual " << sqrt(cp / ssq)
<< " true residual " << true_residual
<< " target " << Tolerance << std::endl;
std::cout << GridLogMessage << "GMRES Time elapsed: Total " << SolverTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "GMRES Time elapsed: Matrix " << MatrixTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "GMRES Time elapsed: Linalg " << LinalgTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "GMRES Time elapsed: QR " << QrTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "GMRES Time elapsed: CompSol " << CompSolutionTimer.Elapsed() << std::endl;
return;
}
}
std::cout << GridLogMessage << "GeneralisedMinimalResidual did NOT converge" << std::endl;
if (ErrorOnNoConverge)
assert(0);
}
RealD outerLoopBody(LinearOperatorBase<Field> &LinOp, const Field &src, Field &psi, RealD rsq) {
RealD cp = 0;
Field w(src.Grid());
Field r(src.Grid());
// this should probably be made a class member so that it is only allocated once, not in every restart
std::vector<Field> v(RestartLength + 1, src.Grid()); for (auto &elem : v) elem = Zero();
MatrixTimer.Start();
LinOp.Op(psi, w);
MatrixTimer.Stop();
LinalgTimer.Start();
r = src - w;
gamma[0] = sqrt(norm2(r));
v[0] = (1. / gamma[0]) * r;
LinalgTimer.Stop();
for (int i=0; i<RestartLength; i++) {
IterationCount++;
arnoldiStep(LinOp, v, w, i);
qrUpdate(i);
cp = norm(gamma[i+1]);
std::cout << GridLogIterative << "GeneralisedMinimalResidual: Iteration " << IterationCount
<< " residual " << cp << " target " << rsq << std::endl;
if ((i == RestartLength - 1) || (IterationCount == MaxIterations) || (cp <= rsq)) {
computeSolution(v, psi, i);
return cp;
}
}
assert(0); // Never reached
return cp;
}
void arnoldiStep(LinearOperatorBase<Field> &LinOp, std::vector<Field> &v, Field &w, int iter) {
MatrixTimer.Start();
LinOp.Op(v[iter], w);
MatrixTimer.Stop();
LinalgTimer.Start();
for (int i = 0; i <= iter; ++i) {
H(iter, i) = innerProduct(v[i], w);
w = w - ComplexD(H(iter, i)) * v[i];
}
H(iter, iter + 1) = sqrt(norm2(w));
v[iter + 1] = ComplexD(1. / H(iter, iter + 1)) * w;
LinalgTimer.Stop();
}
void qrUpdate(int iter) {
QrTimer.Start();
for (int i = 0; i < iter ; ++i) {
auto tmp = -s[i] * ComplexD(H(iter, i)) + c[i] * ComplexD(H(iter, i + 1));
H(iter, i) = conjugate(c[i]) * ComplexD(H(iter, i)) + conjugate(s[i]) * ComplexD(H(iter, i + 1));
H(iter, i + 1) = tmp;
}
// Compute new Givens Rotation
auto nu = sqrt(std::norm(H(iter, iter)) + std::norm(H(iter, iter + 1)));
c[iter] = H(iter, iter) / nu;
s[iter] = H(iter, iter + 1) / nu;
// Apply new Givens rotation
H(iter, iter) = nu;
H(iter, iter + 1) = 0.;
gamma[iter + 1] = -s[iter] * gamma[iter];
gamma[iter] = conjugate(c[iter]) * gamma[iter];
QrTimer.Stop();
}
void computeSolution(std::vector<Field> const &v, Field &psi, int iter) {
CompSolutionTimer.Start();
for (int i = iter; i >= 0; i--) {
y[i] = gamma[i];
for (int k = i + 1; k <= iter; k++)
y[i] = y[i] - ComplexD(H(k, i)) * y[k];
y[i] = y[i] / ComplexD(H(i, i));
}
for (int i = 0; i <= iter; i++)
psi = psi + v[i] * y[i];
CompSolutionTimer.Stop();
}
};
}
#endif
File diff suppressed because it is too large Load Diff
File diff suppressed because it is too large Load Diff
@@ -1,741 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ImplicitlyRestartedLanczos.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: paboyle <paboyle@ph.ed.ac.uk>
Author: Chulwoo Jung <chulwoo@bnl.gov>
Author: Christoph Lehner <clehner@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_BIRL_H
#define GRID_BIRL_H
#include <string.h> //memset
//#include <zlib.h>
#include <sys/stat.h>
NAMESPACE_BEGIN(Grid);
/////////////////////////////////////////////////////////////
// Implicitly restarted lanczos
/////////////////////////////////////////////////////////////
template<class Field> class ImplicitlyRestartedLanczosTester
{
public:
virtual int TestConvergence(int j,RealD resid,Field &evec, RealD &eval,RealD evalMaxApprox)=0;
virtual int ReconstructEval(int j,RealD resid,Field &evec, RealD &eval,RealD evalMaxApprox)=0;
};
enum IRLdiagonalisation {
IRLdiagonaliseWithDSTEGR,
IRLdiagonaliseWithQR,
IRLdiagonaliseWithEigen
};
template<class Field> class ImplicitlyRestartedLanczosHermOpTester : public ImplicitlyRestartedLanczosTester<Field>
{
public:
LinearFunction<Field> &_HermOp;
ImplicitlyRestartedLanczosHermOpTester(LinearFunction<Field> &HermOp) : _HermOp(HermOp) { };
int ReconstructEval(int j,RealD resid,Field &B, RealD &eval,RealD evalMaxApprox)
{
return TestConvergence(j,resid,B,eval,evalMaxApprox);
}
int TestConvergence(int j,RealD eresid,Field &B, RealD &eval,RealD evalMaxApprox)
{
Field v(B);
RealD eval_poly = eval;
// Apply operator
_HermOp(B,v);
RealD vnum = real(innerProduct(B,v)); // HermOp.
RealD vden = norm2(B);
RealD vv0 = norm2(v);
eval = vnum/vden;
v -= eval*B;
RealD vv = norm2(v) / ::pow(evalMaxApprox,2.0);
std::cout.precision(13);
int conv=0;
if( (vv<eresid*eresid) ) conv = 1;
std::cout<<GridLogIRL << "[" << std::setw(3)<<j<<"] "
<<"eval = "<<std::setw(25)<< eval << " (" << eval_poly << ")"
<<" |H B[i] - eval[i]B[i]|^2 / evalMaxApprox^2 " << std::setw(25) << vv
<<" target " << eresid*eresid << " conv " <<conv
<<std::endl;
return conv;
}
};
template<class Field>
class ImplicitlyRestartedLanczos {
private:
const RealD small = 1.0e-8;
int MaxIter;
int MinRestart; // Minimum number of restarts; only check for convergence after
int Nstop; // Number of evecs checked for convergence
int Nk; // Number of converged sought
// int Np; // Np -- Number of spare vecs in krylov space // == Nm - Nk
int Nm; // Nm -- total number of vectors
IRLdiagonalisation diagonalisation;
int orth_period;
RealD OrthoTime;
RealD eresid, betastp;
////////////////////////////////
// Embedded objects
////////////////////////////////
LinearFunction<Field> &_PolyOp;
LinearFunction<Field> &_HermOp;
ImplicitlyRestartedLanczosTester<Field> &_Tester;
// Default tester provided (we need a ref to something in default case)
ImplicitlyRestartedLanczosHermOpTester<Field> SimpleTester;
/////////////////////////
// Constructor
/////////////////////////
public:
//////////////////////////////////////////////////////////////////
// PAB:
//////////////////////////////////////////////////////////////////
// Too many options & knobs.
// Eliminate:
// orth_period
// betastp
// MinRestart
//
// Do we really need orth_period
// What is the theoretical basis & guarantees of betastp ?
// Nstop=Nk viable?
// MinRestart avoidable with new convergence test?
// Could cut to PolyOp, HermOp, Tester, Nk, Nm, resid, maxiter (+diagonalisation)
// HermOp could be eliminated if we dropped the Power method for max eval.
// -- also: The eval, eval2, eval2_copy stuff is still unnecessarily unclear
//////////////////////////////////////////////////////////////////
ImplicitlyRestartedLanczos(LinearFunction<Field> & PolyOp,
LinearFunction<Field> & HermOp,
ImplicitlyRestartedLanczosTester<Field> & Tester,
int _Nstop, // sought vecs
int _Nk, // sought vecs
int _Nm, // spare vecs
RealD _eresid, // resid in lmdue deficit
int _MaxIter, // Max iterations
RealD _betastp=0.0, // if beta(k) < betastp: converged
int _MinRestart=0, int _orth_period = 1,
IRLdiagonalisation _diagonalisation= IRLdiagonaliseWithEigen) :
SimpleTester(HermOp), _PolyOp(PolyOp), _HermOp(HermOp), _Tester(Tester),
Nstop(_Nstop) , Nk(_Nk), Nm(_Nm),
eresid(_eresid), betastp(_betastp),
MaxIter(_MaxIter) , MinRestart(_MinRestart),
orth_period(_orth_period), diagonalisation(_diagonalisation) { };
ImplicitlyRestartedLanczos(LinearFunction<Field> & PolyOp,
LinearFunction<Field> & HermOp,
int _Nstop, // sought vecs
int _Nk, // sought vecs
int _Nm, // spare vecs
RealD _eresid, // resid in lmdue deficit
int _MaxIter, // Max iterations
RealD _betastp=0.0, // if beta(k) < betastp: converged
int _MinRestart=0, int _orth_period = 1,
IRLdiagonalisation _diagonalisation= IRLdiagonaliseWithEigen) :
SimpleTester(HermOp), _PolyOp(PolyOp), _HermOp(HermOp), _Tester(SimpleTester),
Nstop(_Nstop) , Nk(_Nk), Nm(_Nm),
eresid(_eresid), betastp(_betastp),
MaxIter(_MaxIter) , MinRestart(_MinRestart),
orth_period(_orth_period), diagonalisation(_diagonalisation) { };
////////////////////////////////
// Helpers
////////////////////////////////
template<typename T> static RealD normalise(T& v)
{
RealD nn = norm2(v);
nn = std::sqrt(nn);
v = v * (1.0/nn);
return nn;
}
void orthogonalize(Field& w, std::vector<Field>& evec,int k)
{
OrthoTime-=usecond()/1e6;
basisOrthogonalize(evec,w,k);
normalise(w);
OrthoTime+=usecond()/1e6;
}
/* Rudy Arthur's thesis pp.137
------------------------
Require: M > K P = M K †
Compute the factorization AVM = VM HM + fM eM
repeat
Q=I
for i = 1,...,P do
QiRi =HM −θiI Q = QQi
H M = Q †i H M Q i
end for
βK =HM(K+1,K) σK =Q(M,K)
r=vK+1βK +rσK
VK =VM(1:M)Q(1:M,1:K)
HK =HM(1:K,1:K)
→AVK =VKHK +fKe†K † Extend to an M = K + P step factorization AVM = VMHM + fMeM
until convergence
*/
void calc(std::vector<RealD>& eval, std::vector<Field>& evec, const Field& src, int& Nconv, bool reverse=false)
{
GridBase *grid = src.Grid();
assert(grid == evec[0].Grid());
// GridLogIRL.TimingMode(1);
std::cout << GridLogIRL <<"**************************************************************************"<< std::endl;
std::cout << GridLogIRL <<" ImplicitlyRestartedLanczos::calc() starting iteration 0 / "<< MaxIter<< std::endl;
std::cout << GridLogIRL <<"**************************************************************************"<< std::endl;
std::cout << GridLogIRL <<" -- seek Nk = " << Nk <<" vectors"<< std::endl;
std::cout << GridLogIRL <<" -- accept Nstop = " << Nstop <<" vectors"<< std::endl;
std::cout << GridLogIRL <<" -- total Nm = " << Nm <<" vectors"<< std::endl;
std::cout << GridLogIRL <<" -- size of eval = " << eval.size() << std::endl;
std::cout << GridLogIRL <<" -- size of evec = " << evec.size() << std::endl;
if ( diagonalisation == IRLdiagonaliseWithDSTEGR ) {
std::cout << GridLogIRL << "Diagonalisation is DSTEGR "<<std::endl;
} else if ( diagonalisation == IRLdiagonaliseWithQR ) {
std::cout << GridLogIRL << "Diagonalisation is QR "<<std::endl;
} else if ( diagonalisation == IRLdiagonaliseWithEigen ) {
std::cout << GridLogIRL << "Diagonalisation is Eigen "<<std::endl;
}
std::cout << GridLogIRL <<"**************************************************************************"<< std::endl;
assert(Nm <= evec.size() && Nm <= eval.size());
// quickly get an idea of the largest eigenvalue to more properly normalize the residuum
RealD evalMaxApprox = 0.0;
{
auto src_n = src;
auto tmp = src;
std::cout << GridLogIRL << " IRL source norm " << norm2(src) << std::endl;
const int _MAX_ITER_IRL_MEVAPP_ = 50;
for (int i=0;i<_MAX_ITER_IRL_MEVAPP_;i++) {
normalise(src_n);
_HermOp(src_n,tmp);
// std::cout << GridLogMessage<< tmp<<std::endl; exit(0);
// std::cout << GridLogIRL << " _HermOp " << norm2(tmp) << std::endl;
// RealD vnum = real(innerProduct(src_n,tmp)); // HermOp.
RealD vnum = real(innerProduct(tmp,tmp)); // HermOp^2.
RealD vden = norm2(src_n);
RealD na = std::sqrt(vnum/vden);
if (fabs(evalMaxApprox/na - 1.0) < 0.0001)
i=_MAX_ITER_IRL_MEVAPP_;
evalMaxApprox = na;
std::cout << GridLogIRL << " Approximation of largest eigenvalue: " << evalMaxApprox << std::endl;
src_n = tmp;
}
}
std::cout << GridLogIRL << " Final evalMaxApprox " << evalMaxApprox << std::endl;
std::vector<RealD> lme(Nm);
std::vector<RealD> lme2(Nm);
std::vector<RealD> eval2(Nm);
std::vector<RealD> eval2_copy(Nm);
Eigen::MatrixXd Qt = Eigen::MatrixXd::Zero(Nm,Nm);
Field f(grid);
Field v(grid);
int k1 = 1;
int k2 = Nk;
RealD beta_k;
Nconv = 0;
// Set initial vector
evec[0] = src;
normalise(evec[0]);
// Initial Nk steps
OrthoTime=0.;
for(int k=0; k<Nk; ++k) step(eval,lme,evec,f,Nm,k);
std::cout<<GridLogIRL <<"Initial "<< Nk <<"steps done "<<std::endl;
std::cout<<GridLogIRL <<"Initial steps:OrthoTime "<<OrthoTime<< "seconds"<<std::endl;
//////////////////////////////////
// Restarting loop begins
//////////////////////////////////
int iter;
for(iter = 0; iter<MaxIter; ++iter){
OrthoTime=0.;
std::cout<< GridLogMessage <<" **********************"<< std::endl;
std::cout<< GridLogMessage <<" Restart iteration = "<< iter << std::endl;
std::cout<< GridLogMessage <<" **********************"<< std::endl;
std::cout<<GridLogIRL <<" running "<<Nm-Nk <<" steps: "<<std::endl;
for(int k=Nk; k<Nm; ++k) step(eval,lme,evec,f,Nm,k);
f *= lme[Nm-1];
std::cout<<GridLogIRL <<" "<<Nm-Nk <<" steps done "<<std::endl;
std::cout<<GridLogIRL <<"Initial steps:OrthoTime "<<OrthoTime<< "seconds"<<std::endl;
//////////////////////////////////
// getting eigenvalues
//////////////////////////////////
for(int k=0; k<Nm; ++k){
eval2[k] = eval[k+k1-1];
lme2[k] = lme[k+k1-1];
}
Qt = Eigen::MatrixXd::Identity(Nm,Nm);
diagonalize(eval2,lme2,Nm,Nm,Qt,grid);
std::cout<<GridLogIRL <<" diagonalized "<<std::endl;
//////////////////////////////////
// sorting
//////////////////////////////////
eval2_copy = eval2;
std::partial_sort(eval2.begin(),eval2.begin()+Nm,eval2.end(),std::greater<RealD>());
std::cout<<GridLogIRL <<" evals sorted "<<std::endl;
const int chunk=8;
for(int io=0; io<k2;io+=chunk){
std::cout<<GridLogIRL << "eval "<< std::setw(3) << io ;
for(int ii=0;ii<chunk;ii++){
if ( (io+ii)<k2 )
std::cout<< " "<< std::setw(12)<< eval2[io+ii];
}
std::cout << std::endl;
}
//////////////////////////////////
// Implicitly shifted QR transformations
//////////////////////////////////
Qt = Eigen::MatrixXd::Identity(Nm,Nm);
for(int ip=k2; ip<Nm; ++ip){
QR_decomp(eval,lme,Nm,Nm,Qt,eval2[ip],k1,Nm);
}
std::cout<<GridLogIRL <<"QR decomposed "<<std::endl;
assert(k2<Nm); assert(k2<Nm); assert(k1>0);
basisRotate(evec,Qt,k1-1,k2+1,0,Nm,Nm); /// big constraint on the basis
std::cout<<GridLogIRL <<"basisRotated by Qt *"<<k1-1<<","<<k2+1<<")"<<std::endl;
////////////////////////////////////////////////////
// Compressed vector f and beta(k2)
////////////////////////////////////////////////////
f *= Qt(k2-1,Nm-1);
f += lme[k2-1] * evec[k2];
beta_k = norm2(f);
beta_k = std::sqrt(beta_k);
std::cout<<GridLogIRL<<" beta(k) = "<<beta_k<<std::endl;
RealD betar = 1.0/beta_k;
evec[k2] = betar * f;
lme[k2-1] = beta_k;
////////////////////////////////////////////////////
// Convergence test
////////////////////////////////////////////////////
for(int k=0; k<Nm; ++k){
eval2[k] = eval[k];
lme2[k] = lme[k];
}
Qt = Eigen::MatrixXd::Identity(Nm,Nm);
diagonalize(eval2,lme2,Nk,Nm,Qt,grid);
std::cout<<GridLogIRL <<" Diagonalized "<<std::endl;
Nconv = 0;
if (iter >= MinRestart) {
std::cout << GridLogIRL << "Test convergence: rotate subset of vectors to test convergence " << std::endl;
Field B(grid); B.Checkerboard() = evec[0].Checkerboard();
// power of two search pattern; not every evalue in eval2 is assessed.
int allconv =1;
for(int jj = 1; jj<=Nstop; jj*=2){
int j = Nstop-jj;
RealD e = eval2_copy[j]; // Discard the evalue
basisRotateJ(B,evec,Qt,j,0,Nk,Nm);
if( !_Tester.TestConvergence(j,eresid,B,e,evalMaxApprox) ) {
allconv=0;
}
}
// Do evec[0] for good measure
{
int j=0;
RealD e = eval2_copy[0];
basisRotateJ(B,evec,Qt,j,0,Nk,Nm);
if( !_Tester.TestConvergence(j,eresid,B,e,evalMaxApprox) ) allconv=0;
}
if ( allconv ) Nconv = Nstop;
// test if we converged, if so, terminate
std::cout<<GridLogIRL<<" #modes converged: >= "<<Nconv<<"/"<<Nstop<<std::endl;
// if( Nconv>=Nstop || beta_k < betastp){
if( Nconv>=Nstop){
goto converged;
}
} else {
std::cout << GridLogIRL << "iter < MinRestart: do not yet test for convergence\n";
} // end of iter loop
}
std::cout<<GridLogError<<"\n NOT converged.\n";
abort();
converged:
{
Field B(grid); B.Checkerboard() = evec[0].Checkerboard();
basisRotate(evec,Qt,0,Nk,0,Nk,Nm);
std::cout << GridLogIRL << " Rotated basis"<<std::endl;
Nconv=0;
//////////////////////////////////////////////////////////////////////
// Full final convergence test; unconditionally applied
//////////////////////////////////////////////////////////////////////
for(int j = 0; j<=Nk; j++){
B=evec[j];
if( _Tester.ReconstructEval(j,eresid,B,eval2[j],evalMaxApprox) ) {
Nconv++;
}
}
if ( Nconv < Nstop ) {
std::cout << GridLogIRL << "Nconv ("<<Nconv<<") < Nstop ("<<Nstop<<")"<<std::endl;
std::cout << GridLogIRL << "returning Nstop vectors, the last "<< Nstop-Nconv << "of which might meet convergence criterion only approximately" <<std::endl;
}
eval=eval2;
//Keep only converged
eval.resize(Nstop);// was Nconv
evec.resize(Nstop,grid);// was Nconv
basisSortInPlace(evec,eval,reverse);
}
std::cout << GridLogIRL <<"**************************************************************************"<< std::endl;
std::cout << GridLogIRL << "ImplicitlyRestartedLanczos CONVERGED ; Summary :\n";
std::cout << GridLogIRL <<"**************************************************************************"<< std::endl;
std::cout << GridLogIRL << " -- Iterations = "<< iter << "\n";
std::cout << GridLogIRL << " -- beta(k) = "<< beta_k << "\n";
std::cout << GridLogIRL << " -- Nconv = "<< Nconv << "\n";
std::cout << GridLogIRL <<"**************************************************************************"<< std::endl;
}
private:
/* Saad PP. 195
1. Choose an initial vector v1 of 2-norm unity. Set β1 ≡ 0, v0 ≡ 0
2. For k = 1,2,...,m Do:
3. wk:=Avk - b_k v_{k-1}
4. ak:=(wk,vk) //
5. wk:=wk-akvk // wk orthog vk
6. bk+1 := ||wk||_2. If b_k+1 = 0 then Stop
7. vk+1 := wk/b_k+1
8. EndDo
*/
void step(std::vector<RealD>& lmd,
std::vector<RealD>& lme,
std::vector<Field>& evec,
Field& w,int Nm,int k)
{
std::cout<<GridLogDebug << "Lanczos step " <<k<<std::endl;
const RealD tiny = 1.0e-20;
assert( k< Nm );
GridStopWatch gsw_op,gsw_o;
Field& evec_k = evec[k];
_PolyOp(evec_k,w); std::cout<<GridLogDebug << "PolyOp" <<std::endl;
if(k>0) w -= lme[k-1] * evec[k-1];
ComplexD zalph = innerProduct(evec_k,w);
RealD alph = real(zalph);
w = w - alph * evec_k;
RealD beta = normalise(w);
lmd[k] = alph;
lme[k] = beta;
if ( (k>0) && ( (k % orth_period) == 0 )) {
std::cout<<GridLogDebug << "Orthogonalising " <<k<<std::endl;
orthogonalize(w,evec,k); // orthonormalise
std::cout<<GridLogDebug << "Orthogonalised " <<k<<std::endl;
}
if(k < Nm-1) evec[k+1] = w;
std::cout<<GridLogIRL << "Lanczos step alpha[" << k << "] = " << zalph << " beta[" << k << "] = "<<beta<<std::endl;
if ( beta < tiny )
std::cout<<GridLogIRL << " beta is tiny "<<beta<<std::endl;
std::cout<<GridLogDebug << "Lanczos step complete " <<k<<std::endl;
}
void diagonalize_Eigen(std::vector<RealD>& lmd, std::vector<RealD>& lme,
int Nk, int Nm,
Eigen::MatrixXd & Qt, // Nm x Nm
GridBase *grid)
{
Eigen::MatrixXd TriDiag = Eigen::MatrixXd::Zero(Nk,Nk);
for(int i=0;i<Nk;i++) TriDiag(i,i) = lmd[i];
for(int i=0;i<Nk-1;i++) TriDiag(i,i+1) = lme[i];
for(int i=0;i<Nk-1;i++) TriDiag(i+1,i) = lme[i];
Eigen::SelfAdjointEigenSolver<Eigen::MatrixXd> eigensolver(TriDiag);
for (int i = 0; i < Nk; i++) {
lmd[Nk-1-i] = eigensolver.eigenvalues()(i);
}
for (int i = 0; i < Nk; i++) {
for (int j = 0; j < Nk; j++) {
Qt(Nk-1-i,j) = eigensolver.eigenvectors()(j,i);
}
}
}
///////////////////////////////////////////////////////////////////////////
// File could end here if settle on Eigen ??? !!!
///////////////////////////////////////////////////////////////////////////
void QR_decomp(std::vector<RealD>& lmd, // Nm
std::vector<RealD>& lme, // Nm
int Nk, int Nm, // Nk, Nm
Eigen::MatrixXd& Qt, // Nm x Nm matrix
RealD Dsh, int kmin, int kmax)
{
int k = kmin-1;
RealD x;
RealD Fden = 1.0/hypot(lmd[k]-Dsh,lme[k]);
RealD c = ( lmd[k] -Dsh) *Fden;
RealD s = -lme[k] *Fden;
RealD tmpa1 = lmd[k];
RealD tmpa2 = lmd[k+1];
RealD tmpb = lme[k];
lmd[k] = c*c*tmpa1 +s*s*tmpa2 -2.0*c*s*tmpb;
lmd[k+1] = s*s*tmpa1 +c*c*tmpa2 +2.0*c*s*tmpb;
lme[k] = c*s*(tmpa1-tmpa2) +(c*c-s*s)*tmpb;
x =-s*lme[k+1];
lme[k+1] = c*lme[k+1];
for(int i=0; i<Nk; ++i){
RealD Qtmp1 = Qt(k,i);
RealD Qtmp2 = Qt(k+1,i);
Qt(k,i) = c*Qtmp1 - s*Qtmp2;
Qt(k+1,i)= s*Qtmp1 + c*Qtmp2;
}
// Givens transformations
for(int k = kmin; k < kmax-1; ++k){
RealD Fden = 1.0/hypot(x,lme[k-1]);
RealD c = lme[k-1]*Fden;
RealD s = - x*Fden;
RealD tmpa1 = lmd[k];
RealD tmpa2 = lmd[k+1];
RealD tmpb = lme[k];
lmd[k] = c*c*tmpa1 +s*s*tmpa2 -2.0*c*s*tmpb;
lmd[k+1] = s*s*tmpa1 +c*c*tmpa2 +2.0*c*s*tmpb;
lme[k] = c*s*(tmpa1-tmpa2) +(c*c-s*s)*tmpb;
lme[k-1] = c*lme[k-1] -s*x;
if(k != kmax-2){
x = -s*lme[k+1];
lme[k+1] = c*lme[k+1];
}
for(int i=0; i<Nk; ++i){
RealD Qtmp1 = Qt(k,i);
RealD Qtmp2 = Qt(k+1,i);
Qt(k,i) = c*Qtmp1 -s*Qtmp2;
Qt(k+1,i) = s*Qtmp1 +c*Qtmp2;
}
}
}
void diagonalize(std::vector<RealD>& lmd, std::vector<RealD>& lme,
int Nk, int Nm,
Eigen::MatrixXd & Qt,
GridBase *grid)
{
Qt = Eigen::MatrixXd::Identity(Nm,Nm);
if ( diagonalisation == IRLdiagonaliseWithDSTEGR ) {
diagonalize_lapack(lmd,lme,Nk,Nm,Qt,grid);
} else if ( diagonalisation == IRLdiagonaliseWithQR ) {
diagonalize_QR(lmd,lme,Nk,Nm,Qt,grid);
} else if ( diagonalisation == IRLdiagonaliseWithEigen ) {
diagonalize_Eigen(lmd,lme,Nk,Nm,Qt,grid);
} else {
assert(0);
}
}
#ifdef USE_LAPACK
void LAPACK_dstegr(char *jobz, char *range, int *n, double *d, double *e,
double *vl, double *vu, int *il, int *iu, double *abstol,
int *m, double *w, double *z, int *ldz, int *isuppz,
double *work, int *lwork, int *iwork, int *liwork,
int *info);
#endif
void diagonalize_lapack(std::vector<RealD>& lmd,
std::vector<RealD>& lme,
int Nk, int Nm,
Eigen::MatrixXd& Qt,
GridBase *grid)
{
#ifdef USE_LAPACK
const int size = Nm;
int NN = Nk;
double evals_tmp[NN];
double evec_tmp[NN][NN];
memset(evec_tmp[0],0,sizeof(double)*NN*NN);
double DD[NN];
double EE[NN];
for (int i = 0; i< NN; i++) {
for (int j = i - 1; j <= i + 1; j++) {
if ( j < NN && j >= 0 ) {
if (i==j) DD[i] = lmd[i];
if (i==j) evals_tmp[i] = lmd[i];
if (j==(i-1)) EE[j] = lme[j];
}
}
}
int evals_found;
int lwork = ( (18*NN) > (1+4*NN+NN*NN)? (18*NN):(1+4*NN+NN*NN)) ;
int liwork = 3+NN*10 ;
int iwork[liwork];
double work[lwork];
int isuppz[2*NN];
char jobz = 'V'; // calculate evals & evecs
char range = 'I'; // calculate all evals
// char range = 'A'; // calculate all evals
char uplo = 'U'; // refer to upper half of original matrix
char compz = 'I'; // Compute eigenvectors of tridiagonal matrix
int ifail[NN];
int info;
int total = grid->_Nprocessors;
int node = grid->_processor;
int interval = (NN/total)+1;
double vl = 0.0, vu = 0.0;
int il = interval*node+1 , iu = interval*(node+1);
if (iu > NN) iu=NN;
double tol = 0.0;
if (1) {
memset(evals_tmp,0,sizeof(double)*NN);
if ( il <= NN){
LAPACK_dstegr(&jobz, &range, &NN,
(double*)DD, (double*)EE,
&vl, &vu, &il, &iu, // these four are ignored if second parameteris 'A'
&tol, // tolerance
&evals_found, evals_tmp, (double*)evec_tmp, &NN,
isuppz,
work, &lwork, iwork, &liwork,
&info);
for (int i = iu-1; i>= il-1; i--){
evals_tmp[i] = evals_tmp[i - (il-1)];
if (il>1) evals_tmp[i-(il-1)]=0.;
for (int j = 0; j< NN; j++){
evec_tmp[i][j] = evec_tmp[i - (il-1)][j];
if (il>1) evec_tmp[i-(il-1)][j]=0.;
}
}
}
{
grid->GlobalSumVector(evals_tmp,NN);
grid->GlobalSumVector((double*)evec_tmp,NN*NN);
}
}
// Safer to sort instead of just reversing it,
// but the document of the routine says evals are sorted in increasing order.
// qr gives evals in decreasing order.
for(int i=0;i<NN;i++){
lmd [NN-1-i]=evals_tmp[i];
for(int j=0;j<NN;j++){
Qt((NN-1-i),j)=evec_tmp[i][j];
}
}
#else
assert(0);
#endif
}
void diagonalize_QR(std::vector<RealD>& lmd, std::vector<RealD>& lme,
int Nk, int Nm,
Eigen::MatrixXd & Qt,
GridBase *grid)
{
int QRiter = 100*Nm;
int kmin = 1;
int kmax = Nk;
// (this should be more sophisticated)
for(int iter=0; iter<QRiter; ++iter){
// determination of 2x2 leading submatrix
RealD dsub = lmd[kmax-1]-lmd[kmax-2];
RealD dd = std::sqrt(dsub*dsub + 4.0*lme[kmax-2]*lme[kmax-2]);
RealD Dsh = 0.5*(lmd[kmax-2]+lmd[kmax-1] +dd*(dsub/fabs(dsub)));
// (Dsh: shift)
// transformation
QR_decomp(lmd,lme,Nk,Nm,Qt,Dsh,kmin,kmax); // Nk, Nm
// Convergence criterion (redef of kmin and kamx)
for(int j=kmax-1; j>= kmin; --j){
RealD dds = fabs(lmd[j-1])+fabs(lmd[j]);
if(fabs(lme[j-1])+dds > dds){
kmax = j+1;
goto continued;
}
}
QRiter = iter;
return;
continued:
for(int j=0; j<kmax-1; ++j){
RealD dds = fabs(lmd[j])+fabs(lmd[j+1]);
if(fabs(lme[j])+dds > dds){
kmin = j+1;
break;
}
}
}
std::cout << GridLogError << "[QL method] Error - Too many iteration: "<<QRiter<<"\n";
abort();
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,454 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/LocalCoherenceLanczos.h
Copyright (C) 2015
Author: Christoph Lehner <clehner@bnl.gov>
Author: paboyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_LOCAL_COHERENCE_IRL_H
#define GRID_LOCAL_COHERENCE_IRL_H
NAMESPACE_BEGIN(Grid);
struct LanczosParams : Serializable {
public:
GRID_SERIALIZABLE_CLASS_MEMBERS(LanczosParams,
ChebyParams, Cheby,/*Chebyshev*/
int, Nstop, /*Vecs in Lanczos must converge Nstop < Nk < Nm*/
int, Nk, /*Vecs in Lanczos seek converge*/
int, Nm, /*Total vecs in Lanczos include restart*/
RealD, resid, /*residual*/
int, MaxIt,
RealD, betastp, /* ? */
int, MinRes); // Must restart
};
//This class is the input parameter class for some testing programs
struct LocalCoherenceLanczosParams : Serializable {
public:
GRID_SERIALIZABLE_CLASS_MEMBERS(LocalCoherenceLanczosParams,
bool, saveEvecs,
bool, doFine,
bool, doFineRead,
bool, doCoarse,
bool, doCoarseRead,
LanczosParams, FineParams,
LanczosParams, CoarseParams,
ChebyParams, Smoother,
RealD , coarse_relax_tol,
std::vector<int>, blockSize,
std::string, config,
std::vector < ComplexD >, omega,
RealD, mass,
RealD, M5);
};
// Duplicate functionality; ProjectedFunctionHermOp could be used with the trivial function
template<class Fobj,class CComplex,int nbasis>
class ProjectedHermOp : public LinearFunction<Lattice<iVector<CComplex,nbasis > > > {
public:
using LinearFunction<Lattice<iVector<CComplex,nbasis > > >::operator();
typedef iVector<CComplex,nbasis > CoarseSiteVector;
typedef Lattice<CoarseSiteVector> CoarseField;
typedef Lattice<CComplex> CoarseScalar; // used for inner products on fine field
typedef Lattice<Fobj> FineField;
LinearOperatorBase<FineField> &_Linop;
std::vector<FineField> &subspace;
ProjectedHermOp(LinearOperatorBase<FineField>& linop, std::vector<FineField> & _subspace) :
_Linop(linop), subspace(_subspace)
{
assert(subspace.size() >0);
};
void operator()(const CoarseField& in, CoarseField& out) {
GridBase *FineGrid = subspace[0].Grid();
int checkerboard = subspace[0].Checkerboard();
FineField fin (FineGrid); fin.Checkerboard()= checkerboard;
FineField fout(FineGrid); fout.Checkerboard() = checkerboard;
blockPromote(in,fin,subspace); std::cout<<GridLogIRL<<"ProjectedHermop : Promote to fine"<<std::endl;
_Linop.HermOp(fin,fout); std::cout<<GridLogIRL<<"ProjectedHermop : HermOp (fine) "<<std::endl;
blockProject(out,fout,subspace); std::cout<<GridLogIRL<<"ProjectedHermop : Project to coarse "<<std::endl;
}
};
template<class Fobj,class CComplex,int nbasis>
class ProjectedFunctionHermOp : public LinearFunction<Lattice<iVector<CComplex,nbasis > > > {
public:
using LinearFunction<Lattice<iVector<CComplex,nbasis > > >::operator();
typedef iVector<CComplex,nbasis > CoarseSiteVector;
typedef Lattice<CoarseSiteVector> CoarseField;
typedef Lattice<CComplex> CoarseScalar; // used for inner products on fine field
typedef Lattice<Fobj> FineField;
OperatorFunction<FineField> & _poly;
LinearOperatorBase<FineField> &_Linop;
std::vector<FineField> &subspace;
ProjectedFunctionHermOp(OperatorFunction<FineField> & poly,
LinearOperatorBase<FineField>& linop,
std::vector<FineField> & _subspace) :
_poly(poly),
_Linop(linop),
subspace(_subspace)
{ };
void operator()(const CoarseField& in, CoarseField& out) {
GridBase *FineGrid = subspace[0].Grid();
int checkerboard = subspace[0].Checkerboard();
FineField fin (FineGrid); fin.Checkerboard() =checkerboard;
FineField fout(FineGrid);fout.Checkerboard() =checkerboard;
blockPromote(in,fin,subspace); std::cout<<GridLogIRL<<"ProjectedFunctionHermop : Promote to fine"<<std::endl;
_poly(_Linop,fin,fout); std::cout<<GridLogIRL<<"ProjectedFunctionHermop : Poly "<<std::endl;
blockProject(out,fout,subspace); std::cout<<GridLogIRL<<"ProjectedFunctionHermop : Project to coarse "<<std::endl;
}
};
template<class Fobj,class CComplex,int nbasis>
class ImplicitlyRestartedLanczosSmoothedTester : public ImplicitlyRestartedLanczosTester<Lattice<iVector<CComplex,nbasis > > >
{
public:
typedef iVector<CComplex,nbasis > CoarseSiteVector;
typedef Lattice<CoarseSiteVector> CoarseField;
typedef Lattice<CComplex> CoarseScalar; // used for inner products on fine field
typedef Lattice<Fobj> FineField;
LinearFunction<CoarseField> & _Poly;
OperatorFunction<FineField> & _smoother;
LinearOperatorBase<FineField> &_Linop;
RealD _coarse_relax_tol;
std::vector<FineField> &_subspace;
int _largestEvalIdxForReport; //The convergence of the LCL is based on the evals of the coarse grid operator, not those of the underlying fine grid operator
//As a result we do not know what the eval range of the fine operator is until the very end, making tuning the Cheby bounds very difficult
//To work around this issue, every restart we separately reconstruct the fine operator eval for the lowest and highest evec and print these
//out alongside the evals of the coarse operator. To do so we need to know the index of the largest eval (i.e. Nstop-1)
//NOTE: If largestEvalIdxForReport=-1 (default) then this is not performed
ImplicitlyRestartedLanczosSmoothedTester(LinearFunction<CoarseField> &Poly,
OperatorFunction<FineField> &smoother,
LinearOperatorBase<FineField> &Linop,
std::vector<FineField> &subspace,
RealD coarse_relax_tol=5.0e3,
int largestEvalIdxForReport=-1)
: _smoother(smoother), _Linop(Linop), _Poly(Poly), _subspace(subspace),
_coarse_relax_tol(coarse_relax_tol), _largestEvalIdxForReport(largestEvalIdxForReport)
{ };
//evalMaxApprox: approximation of largest eval of the fine Chebyshev operator (suitably wrapped by block projection)
int TestConvergence(int j,RealD eresid,CoarseField &B, RealD &eval,RealD evalMaxApprox)
{
CoarseField v(B);
RealD eval_poly = eval;
// Apply operator
_Poly(B,v);
RealD vnum = real(innerProduct(B,v)); // HermOp.
RealD vden = norm2(B);
RealD vv0 = norm2(v);
eval = vnum/vden;
v -= eval*B;
RealD vv = norm2(v) / ::pow(evalMaxApprox,2.0);
std::cout.precision(13);
std::cout<<GridLogIRL << "[" << std::setw(3)<<j<<"] "
<<"eval = "<<std::setw(25)<< eval << " (" << eval_poly << ")"
<<" |H B[i] - eval[i]B[i]|^2 / evalMaxApprox^2 " << std::setw(25) << vv
<<std::endl;
if(_largestEvalIdxForReport != -1 && (j==0 || j==_largestEvalIdxForReport)){
std::cout<<GridLogIRL << "Estimating true eval of fine grid operator for eval idx " << j << std::endl;
RealD tmp_eval;
ReconstructEval(j,eresid,B,tmp_eval,1.0); //don't use evalMaxApprox of coarse operator! (cf below)
}
int conv=0;
if( (vv<eresid*eresid) ) conv = 1;
return conv;
}
//This function is called at the end of the coarse grid Lanczos. It promotes the coarse eigenvector 'B' to the fine grid,
//applies a smoother to the result then computes the computes the *fine grid* eigenvalue (output as 'eval').
//evalMaxApprox should be the approximation of the largest eval of the fine Hermop. However when this function is called by IRL it actually passes the largest eval of the *Chebyshev* operator (as this is the max approx used for the TestConvergence above)
//As the largest eval of the Chebyshev is typically several orders of magnitude larger this makes the convergence test pass even when it should not.
//We therefore ignore evalMaxApprox here and use a value of 1.0 (note this value is already used by TestCoarse)
int ReconstructEval(int j,RealD eresid,CoarseField &B, RealD &eval,RealD evalMaxApprox)
{
evalMaxApprox = 1.0; //cf above
GridBase *FineGrid = _subspace[0].Grid();
int checkerboard = _subspace[0].Checkerboard();
FineField fB(FineGrid);fB.Checkerboard() =checkerboard;
FineField fv(FineGrid);fv.Checkerboard() =checkerboard;
blockPromote(B,fv,_subspace);
_smoother(_Linop,fv,fB);
RealD eval_poly = eval;
_Linop.HermOp(fB,fv);
RealD vnum = real(innerProduct(fB,fv)); // HermOp.
RealD vden = norm2(fB);
RealD vv0 = norm2(fv);
eval = vnum/vden;
fv -= eval*fB;
RealD vv = norm2(fv) / ::pow(evalMaxApprox,2.0);
if ( j > nbasis ) eresid = eresid*_coarse_relax_tol;
std::cout.precision(13);
std::cout<<GridLogIRL << "[" << std::setw(3)<<j<<"] "
<<"eval = "<<std::setw(25)<< eval << " (" << eval_poly << ")"
<<" |H B[i] - eval[i]B[i]|^2 / evalMaxApprox^2 " << std::setw(25) << vv << " target " << eresid*eresid
<<std::endl;
if( (vv<eresid*eresid) ) return 1;
return 0;
}
};
////////////////////////////////////////////
// Make serializable Lanczos params
////////////////////////////////////////////
template<class Fobj,class CComplex,int nbasis>
class LocalCoherenceLanczos
{
public:
typedef iVector<CComplex,nbasis > CoarseSiteVector;
typedef Lattice<CComplex> CoarseScalar; // used for inner products on fine field
typedef Lattice<CoarseSiteVector> CoarseField;
typedef Lattice<Fobj> FineField;
protected:
GridBase *_CoarseGrid;
GridBase *_FineGrid;
int _checkerboard;
LinearOperatorBase<FineField> & _FineOp;
std::vector<RealD> &evals_fine;
std::vector<RealD> &evals_coarse;
std::vector<FineField> &subspace;
std::vector<CoarseField> &evec_coarse;
private:
std::vector<RealD> _evals_fine;
std::vector<RealD> _evals_coarse;
std::vector<FineField> _subspace;
std::vector<CoarseField> _evec_coarse;
public:
LocalCoherenceLanczos(GridBase *FineGrid,
GridBase *CoarseGrid,
LinearOperatorBase<FineField> &FineOp,
int checkerboard) :
_CoarseGrid(CoarseGrid),
_FineGrid(FineGrid),
_FineOp(FineOp),
_checkerboard(checkerboard),
evals_fine (_evals_fine),
evals_coarse(_evals_coarse),
subspace (_subspace),
evec_coarse(_evec_coarse)
{
evals_fine.resize(0);
evals_coarse.resize(0);
};
//////////////////////////////////////////////////////////////////////////
// Alternate constructore, external storage for use by Hadrons module
//////////////////////////////////////////////////////////////////////////
LocalCoherenceLanczos(GridBase *FineGrid,
GridBase *CoarseGrid,
LinearOperatorBase<FineField> &FineOp,
int checkerboard,
std::vector<FineField> &ext_subspace,
std::vector<CoarseField> &ext_coarse,
std::vector<RealD> &ext_eval_fine,
std::vector<RealD> &ext_eval_coarse
) :
_CoarseGrid(CoarseGrid),
_FineGrid(FineGrid),
_FineOp(FineOp),
_checkerboard(checkerboard),
evals_fine (ext_eval_fine),
evals_coarse(ext_eval_coarse),
subspace (ext_subspace),
evec_coarse (ext_coarse)
{
evals_fine.resize(0);
evals_coarse.resize(0);
};
//The block inner product is the inner product on the fine grid locally summed over the blocks
//to give a Lattice<Scalar> on the coarse grid. This function orthnormalizes the fine-grid subspace
//vectors under the block inner product. This step must be performed after computing the fine grid
//eigenvectors and before computing the coarse grid eigenvectors.
void Orthogonalise(void ) {
CoarseScalar InnerProd(_CoarseGrid);
std::cout << GridLogMessage <<" Gramm-Schmidt pass 1"<<std::endl;
blockOrthogonalise(InnerProd,subspace);
std::cout << GridLogMessage <<" Gramm-Schmidt pass 2"<<std::endl;
blockOrthogonalise(InnerProd,subspace);
};
template<typename T> static RealD normalise(T& v)
{
RealD nn = norm2(v);
nn = ::sqrt(nn);
v = v * (1.0/nn);
return nn;
}
/*
void fakeFine(void)
{
int Nk = nbasis;
subspace.resize(Nk,_FineGrid);
subspace[0]=1.0;
subspace[0].Checkerboard()=_checkerboard;
normalise(subspace[0]);
PlainHermOp<FineField> Op(_FineOp);
for(int k=1;k<Nk;k++){
subspace[k].Checkerboard()=_checkerboard;
Op(subspace[k-1],subspace[k]);
normalise(subspace[k]);
}
}
*/
void testFine(RealD resid)
{
assert(evals_fine.size() == nbasis);
assert(subspace.size() == nbasis);
PlainHermOp<FineField> Op(_FineOp);
ImplicitlyRestartedLanczosHermOpTester<FineField> SimpleTester(Op);
for(int k=0;k<nbasis;k++){
assert(SimpleTester.ReconstructEval(k,resid,subspace[k],evals_fine[k],1.0)==1);
}
}
//While this method serves to check the coarse eigenvectors, it also recomputes the eigenvalues from the smoothed reconstructed eigenvectors
//hence the smoother can be tuned after running the coarse Lanczos by using a different smoother here
void testCoarse(RealD resid,ChebyParams cheby_smooth,RealD relax)
{
assert(evals_fine.size() == nbasis);
assert(subspace.size() == nbasis);
//////////////////////////////////////////////////////////////////////////////////////////////////
// create a smoother and see if we can get a cheap convergence test and smooth inside the IRL
//////////////////////////////////////////////////////////////////////////////////////////////////
Chebyshev<FineField> ChebySmooth(cheby_smooth);
ProjectedFunctionHermOp<Fobj,CComplex,nbasis> ChebyOp (ChebySmooth,_FineOp,subspace);
ImplicitlyRestartedLanczosSmoothedTester<Fobj,CComplex,nbasis> ChebySmoothTester(ChebyOp,ChebySmooth,_FineOp,subspace,relax);
for(int k=0;k<evec_coarse.size();k++){
if ( k < nbasis ) {
assert(ChebySmoothTester.ReconstructEval(k,resid,evec_coarse[k],evals_coarse[k],1.0)==1);
} else {
assert(ChebySmoothTester.ReconstructEval(k,resid*relax,evec_coarse[k],evals_coarse[k],1.0)==1);
}
}
}
void calcFine(ChebyParams cheby_parms,int Nstop,int Nk,int Nm,RealD resid,
RealD MaxIt, RealD betastp, int MinRes)
{
assert(nbasis<=Nm);
Chebyshev<FineField> Cheby(cheby_parms);
FunctionHermOp<FineField> ChebyOp(Cheby,_FineOp);
PlainHermOp<FineField> Op(_FineOp);
evals_fine.resize(Nm);
subspace.resize(Nm,_FineGrid);
ImplicitlyRestartedLanczos<FineField> IRL(ChebyOp,Op,Nstop,Nk,Nm,resid,MaxIt,betastp,MinRes);
FineField src(_FineGrid);
typedef typename FineField::scalar_type Scalar;
// src=1.0;
src=Scalar(1.0);
src.Checkerboard() = _checkerboard;
int Nconv;
IRL.calc(evals_fine,subspace,src,Nconv,false);
// Shrink down to number saved
assert(Nstop>=nbasis);
assert(Nconv>=nbasis);
evals_fine.resize(nbasis);
subspace.resize(nbasis,_FineGrid);
}
//cheby_op: Parameters of the fine grid Chebyshev polynomial used for the Lanczos acceleration
//cheby_smooth: Parameters of a separate Chebyshev polynomial used after the Lanczos has completed to smooth out high frequency noise in the reconstructed fine grid eigenvectors prior to computing the eigenvalue
//relax: Reconstructed eigenvectors (post smoothing) are naturally not as precise as true eigenvectors. This factor acts as a multiplier on the stopping condition when determining whether the results satisfy the user provided stopping condition
void calcCoarse(ChebyParams cheby_op,ChebyParams cheby_smooth,RealD relax,
int Nstop, int Nk, int Nm,RealD resid,
RealD MaxIt, RealD betastp, int MinRes)
{
Chebyshev<FineField> Cheby(cheby_op); //Chebyshev of fine operator on fine grid
ProjectedHermOp<Fobj,CComplex,nbasis> Op(_FineOp,subspace); //Fine operator on coarse grid with intermediate fine grid conversion
ProjectedFunctionHermOp<Fobj,CComplex,nbasis> ChebyOp (Cheby,_FineOp,subspace); //Chebyshev of fine operator on coarse grid with intermediate fine grid conversion
//////////////////////////////////////////////////////////////////////////////////////////////////
// create a smoother and see if we can get a cheap convergence test and smooth inside the IRL
//////////////////////////////////////////////////////////////////////////////////////////////////
Chebyshev<FineField> ChebySmooth(cheby_smooth); //lower order Chebyshev of fine operator on fine grid used to smooth regenerated eigenvectors
ImplicitlyRestartedLanczosSmoothedTester<Fobj,CComplex,nbasis> ChebySmoothTester(ChebyOp,ChebySmooth,_FineOp,subspace,relax,Nstop-1);
evals_coarse.resize(Nm);
evec_coarse.resize(Nm,_CoarseGrid);
CoarseField src(_CoarseGrid); src=1.0;
//Note the "tester" here is also responsible for generating the fine grid eigenvalues which are output into the "evals_coarse" array
ImplicitlyRestartedLanczos<CoarseField> IRL(ChebyOp,ChebyOp,ChebySmoothTester,Nstop,Nk,Nm,resid,MaxIt,betastp,MinRes);
int Nconv=0;
IRL.calc(evals_coarse,evec_coarse,src,Nconv,false);
assert(Nconv>=Nstop);
evals_coarse.resize(Nstop);
evec_coarse.resize (Nstop,_CoarseGrid);
for (int i=0;i<Nstop;i++){
std::cout << i << " Coarse eval = " << evals_coarse[i] << std::endl;
}
}
//Get the fine eigenvector 'i' by reconstruction
void getFineEvecEval(FineField &evec, RealD &eval, const int i) const{
blockPromote(evec_coarse[i],evec,subspace);
eval = evals_coarse[i];
}
};
NAMESPACE_END(Grid);
#endif
-157
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@@ -1,157 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/MinimalResidual.h
Copyright (C) 2015
Author: Daniel Richtmann <daniel.richtmann@ur.de>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_MINIMAL_RESIDUAL_H
#define GRID_MINIMAL_RESIDUAL_H
namespace Grid {
template<class Field> class MinimalResidual : public OperatorFunction<Field> {
public:
using OperatorFunction<Field>::operator();
bool ErrorOnNoConverge; // throw an assert when the MR fails to converge.
// Defaults true.
RealD Tolerance;
Integer MaxIterations;
RealD overRelaxParam;
Integer IterationsToComplete; // Number of iterations the MR took to finish.
// Filled in upon completion
MinimalResidual(RealD tol, Integer maxit, Real ovrelparam = 1.0, bool err_on_no_conv = true)
: Tolerance(tol), MaxIterations(maxit), overRelaxParam(ovrelparam), ErrorOnNoConverge(err_on_no_conv){};
void operator()(LinearOperatorBase<Field> &Linop, const Field &src, Field &psi) {
psi.Checkerboard() = src.Checkerboard();
conformable(psi, src);
ComplexD a, c;
RealD d;
Field Mr(src);
Field r(src);
// Initial residual computation & set up
RealD guess = norm2(psi);
assert(std::isnan(guess) == 0);
RealD ssq = norm2(src);
RealD rsq = Tolerance * Tolerance * ssq;
Linop.Op(psi, Mr);
r = src - Mr;
RealD cp = norm2(r);
std::cout << std::setprecision(4) << std::scientific;
std::cout << GridLogIterative << "MinimalResidual: guess " << guess << std::endl;
std::cout << GridLogIterative << "MinimalResidual: src " << ssq << std::endl;
std::cout << GridLogIterative << "MinimalResidual: cp,r " << cp << std::endl;
if (cp <= rsq) {
return;
}
std::cout << GridLogIterative << "MinimalResidual: k=0 residual " << cp << " target " << rsq << std::endl;
GridStopWatch LinalgTimer;
GridStopWatch MatrixTimer;
GridStopWatch SolverTimer;
SolverTimer.Start();
int k;
for (k = 1; k <= MaxIterations; k++) {
MatrixTimer.Start();
Linop.Op(r, Mr);
MatrixTimer.Stop();
LinalgTimer.Start();
c = innerProduct(Mr, r);
d = norm2(Mr);
a = c / d;
a = a * overRelaxParam;
psi = psi + r * a;
r = r - Mr * a;
cp = norm2(r);
LinalgTimer.Stop();
std::cout << GridLogIterative << "MinimalResidual: Iteration " << k
<< " residual " << cp << " target " << rsq << std::endl;
std::cout << GridLogDebug << "a = " << a << " c = " << c << " d = " << d << std::endl;
// Stopping condition
if (cp <= rsq) {
SolverTimer.Stop();
Linop.Op(psi, Mr);
r = src - Mr;
RealD srcnorm = sqrt(ssq);
RealD resnorm = sqrt(norm2(r));
RealD true_residual = resnorm / srcnorm;
std::cout << GridLogMessage << "MinimalResidual Converged on iteration " << k
<< " computed residual " << sqrt(cp / ssq)
<< " true residual " << true_residual
<< " target " << Tolerance << std::endl;
std::cout << GridLogMessage << "MR Time elapsed: Total " << SolverTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "MR Time elapsed: Matrix " << MatrixTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "MR Time elapsed: Linalg " << LinalgTimer.Elapsed() << std::endl;
if (ErrorOnNoConverge)
assert(true_residual / Tolerance < 10000.0);
IterationsToComplete = k;
return;
}
}
std::cout << GridLogMessage << "MinimalResidual did NOT converge"
<< std::endl;
if (ErrorOnNoConverge)
assert(0);
IterationsToComplete = k;
}
};
} // namespace Grid
#endif
@@ -1,276 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/MixedPrecisionFlexibleGeneralisedMinimalResidual.h
Copyright (C) 2015
Author: Daniel Richtmann <daniel.richtmann@ur.de>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_MIXED_PRECISION_FLEXIBLE_GENERALISED_MINIMAL_RESIDUAL_H
#define GRID_MIXED_PRECISION_FLEXIBLE_GENERALISED_MINIMAL_RESIDUAL_H
namespace Grid {
template<class FieldD, class FieldF, typename std::enable_if<getPrecision<FieldD>::value == 2, int>::type = 0, typename std::enable_if< getPrecision<FieldF>::value == 1, int>::type = 0>
class MixedPrecisionFlexibleGeneralisedMinimalResidual : public OperatorFunction<FieldD> {
public:
using OperatorFunction<FieldD>::operator();
bool ErrorOnNoConverge; // Throw an assert when MPFGMRES fails to converge,
// defaults to true
RealD Tolerance;
Integer MaxIterations;
Integer RestartLength;
Integer MaxNumberOfRestarts;
Integer IterationCount; // Number of iterations the MPFGMRES took to finish,
// filled in upon completion
GridStopWatch MatrixTimer;
GridStopWatch PrecTimer;
GridStopWatch LinalgTimer;
GridStopWatch QrTimer;
GridStopWatch CompSolutionTimer;
GridStopWatch ChangePrecTimer;
Eigen::MatrixXcd H;
std::vector<ComplexD> y;
std::vector<ComplexD> gamma;
std::vector<ComplexD> c;
std::vector<ComplexD> s;
GridBase* SinglePrecGrid;
LinearFunction<FieldF> &Preconditioner;
MixedPrecisionFlexibleGeneralisedMinimalResidual(RealD tol,
Integer maxit,
GridBase * sp_grid,
LinearFunction<FieldF> &Prec,
Integer restart_length,
bool err_on_no_conv = true)
: Tolerance(tol)
, MaxIterations(maxit)
, RestartLength(restart_length)
, MaxNumberOfRestarts(MaxIterations/RestartLength + ((MaxIterations%RestartLength == 0) ? 0 : 1))
, ErrorOnNoConverge(err_on_no_conv)
, H(Eigen::MatrixXcd::Zero(RestartLength, RestartLength + 1)) // sizes taken from DD-αAMG code base
, y(RestartLength + 1, 0.)
, gamma(RestartLength + 1, 0.)
, c(RestartLength + 1, 0.)
, s(RestartLength + 1, 0.)
, SinglePrecGrid(sp_grid)
, Preconditioner(Prec) {};
void operator()(LinearOperatorBase<FieldD> &LinOp, const FieldD &src, FieldD &psi) {
psi.Checkerboard() = src.Checkerboard();
conformable(psi, src);
RealD guess = norm2(psi);
assert(std::isnan(guess) == 0);
RealD cp;
RealD ssq = norm2(src);
RealD rsq = Tolerance * Tolerance * ssq;
FieldD r(src.Grid());
std::cout << std::setprecision(4) << std::scientific;
std::cout << GridLogIterative << "MPFGMRES: guess " << guess << std::endl;
std::cout << GridLogIterative << "MPFGMRES: src " << ssq << std::endl;
PrecTimer.Reset();
MatrixTimer.Reset();
LinalgTimer.Reset();
QrTimer.Reset();
CompSolutionTimer.Reset();
ChangePrecTimer.Reset();
GridStopWatch SolverTimer;
SolverTimer.Start();
IterationCount = 0;
for (int k=0; k<MaxNumberOfRestarts; k++) {
cp = outerLoopBody(LinOp, src, psi, rsq);
// Stopping condition
if (cp <= rsq) {
SolverTimer.Stop();
LinOp.Op(psi,r);
axpy(r,-1.0,src,r);
RealD srcnorm = sqrt(ssq);
RealD resnorm = sqrt(norm2(r));
RealD true_residual = resnorm / srcnorm;
std::cout << GridLogMessage << "MPFGMRES: Converged on iteration " << IterationCount
<< " computed residual " << sqrt(cp / ssq)
<< " true residual " << true_residual
<< " target " << Tolerance << std::endl;
std::cout << GridLogMessage << "MPFGMRES Time elapsed: Total " << SolverTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "MPFGMRES Time elapsed: Precon " << PrecTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "MPFGMRES Time elapsed: Matrix " << MatrixTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "MPFGMRES Time elapsed: Linalg " << LinalgTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "MPFGMRES Time elapsed: QR " << QrTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "MPFGMRES Time elapsed: CompSol " << CompSolutionTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "MPFGMRES Time elapsed: PrecChange " << ChangePrecTimer.Elapsed() << std::endl;
return;
}
}
std::cout << GridLogMessage << "MPFGMRES did NOT converge" << std::endl;
if (ErrorOnNoConverge)
assert(0);
}
RealD outerLoopBody(LinearOperatorBase<FieldD> &LinOp, const FieldD &src, FieldD &psi, RealD rsq) {
RealD cp = 0;
FieldD w(src.Grid());
FieldD r(src.Grid());
// these should probably be made class members so that they are only allocated once, not in every restart
std::vector<FieldD> v(RestartLength + 1, src.Grid()); for (auto &elem : v) elem = Zero();
std::vector<FieldD> z(RestartLength + 1, src.Grid()); for (auto &elem : z) elem = Zero();
MatrixTimer.Start();
LinOp.Op(psi, w);
MatrixTimer.Stop();
LinalgTimer.Start();
r = src - w;
gamma[0] = sqrt(norm2(r));
v[0] = (1. / gamma[0]) * r;
LinalgTimer.Stop();
for (int i=0; i<RestartLength; i++) {
IterationCount++;
arnoldiStep(LinOp, v, z, w, i);
qrUpdate(i);
cp = norm(gamma[i+1]);
std::cout << GridLogIterative << "MPFGMRES: Iteration " << IterationCount
<< " residual " << cp << " target " << rsq << std::endl;
if ((i == RestartLength - 1) || (IterationCount == MaxIterations) || (cp <= rsq)) {
computeSolution(z, psi, i);
return cp;
}
}
assert(0); // Never reached
return cp;
}
void arnoldiStep(LinearOperatorBase<FieldD> &LinOp, std::vector<FieldD> &v, std::vector<FieldD> &z, FieldD &w, int iter) {
FieldF v_f(SinglePrecGrid);
FieldF z_f(SinglePrecGrid);
ChangePrecTimer.Start();
precisionChange(v_f, v[iter]);
precisionChange(z_f, z[iter]);
ChangePrecTimer.Stop();
PrecTimer.Start();
Preconditioner(v_f, z_f);
PrecTimer.Stop();
ChangePrecTimer.Start();
precisionChange(z[iter], z_f);
ChangePrecTimer.Stop();
MatrixTimer.Start();
LinOp.Op(z[iter], w);
MatrixTimer.Stop();
LinalgTimer.Start();
for (int i = 0; i <= iter; ++i) {
H(iter, i) = innerProduct(v[i], w);
w = w - ComplexD(H(iter, i)) * v[i];
}
H(iter, iter + 1) = sqrt(norm2(w));
v[iter + 1] = ComplexD(1. / H(iter, iter + 1)) * w;
LinalgTimer.Stop();
}
void qrUpdate(int iter) {
QrTimer.Start();
for (int i = 0; i < iter ; ++i) {
auto tmp = -s[i] * ComplexD(H(iter, i)) + c[i] * ComplexD(H(iter, i + 1));
H(iter, i) = conjugate(c[i]) * ComplexD(H(iter, i)) + conjugate(s[i]) * ComplexD(H(iter, i + 1));
H(iter, i + 1) = tmp;
}
// Compute new Givens Rotation
auto nu = sqrt(std::norm(H(iter, iter)) + std::norm(H(iter, iter + 1)));
c[iter] = H(iter, iter) / nu;
s[iter] = H(iter, iter + 1) / nu;
// Apply new Givens rotation
H(iter, iter) = nu;
H(iter, iter + 1) = 0.;
gamma[iter + 1] = -s[iter] * gamma[iter];
gamma[iter] = conjugate(c[iter]) * gamma[iter];
QrTimer.Stop();
}
void computeSolution(std::vector<FieldD> const &z, FieldD &psi, int iter) {
CompSolutionTimer.Start();
for (int i = iter; i >= 0; i--) {
y[i] = gamma[i];
for (int k = i + 1; k <= iter; k++)
y[i] = y[i] - ComplexD(H(k, i)) * y[k];
y[i] = y[i] / ComplexD(H(i, i));
}
for (int i = 0; i <= iter; i++)
psi = psi + z[i] * y[i];
CompSolutionTimer.Stop();
}
};
}
#endif
-138
View File
@@ -1,138 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/NormalEquations.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_NORMAL_EQUATIONS_H
#define GRID_NORMAL_EQUATIONS_H
NAMESPACE_BEGIN(Grid);
///////////////////////////////////////////////////////////////////////////////////////////////////////
// Take a matrix and form an NE solver calling a Herm solver
///////////////////////////////////////////////////////////////////////////////////////////////////////
template<class Field> class NormalEquations : public LinearFunction<Field>{
private:
SparseMatrixBase<Field> & _Matrix;
OperatorFunction<Field> & _HermitianSolver;
LinearFunction<Field> & _Guess;
public:
/////////////////////////////////////////////////////
// Wrap the usual normal equations trick
/////////////////////////////////////////////////////
NormalEquations(SparseMatrixBase<Field> &Matrix, OperatorFunction<Field> &HermitianSolver,
LinearFunction<Field> &Guess)
: _Matrix(Matrix), _HermitianSolver(HermitianSolver), _Guess(Guess) {};
void operator() (const Field &in, Field &out){
Field src(in.Grid());
Field tmp(in.Grid());
MdagMLinearOperator<SparseMatrixBase<Field>,Field> MdagMOp(_Matrix);
_Matrix.Mdag(in,src);
_Guess(src,out);
_HermitianSolver(MdagMOp,src,out); // Mdag M out = Mdag in
}
};
template<class Field> class NormalResidual : public LinearFunction<Field>{
private:
SparseMatrixBase<Field> & _Matrix;
OperatorFunction<Field> & _HermitianSolver;
LinearFunction<Field> & _Guess;
public:
/////////////////////////////////////////////////////
// Wrap the usual normal equations trick
/////////////////////////////////////////////////////
NormalResidual(SparseMatrixBase<Field> &Matrix, OperatorFunction<Field> &HermitianSolver,
LinearFunction<Field> &Guess)
: _Matrix(Matrix), _HermitianSolver(HermitianSolver), _Guess(Guess) {};
void operator() (const Field &in, Field &out){
Field res(in.Grid());
Field tmp(in.Grid());
MMdagLinearOperator<SparseMatrixBase<Field>,Field> MMdagOp(_Matrix);
_Guess(in,res);
_HermitianSolver(MMdagOp,in,res); // M Mdag res = in ;
_Matrix.Mdag(res,out); // out = Mdag res
}
};
template<class Field> class HPDSolver : public LinearFunction<Field> {
private:
LinearOperatorBase<Field> & _Matrix;
OperatorFunction<Field> & _HermitianSolver;
LinearFunction<Field> & _Guess;
public:
/////////////////////////////////////////////////////
// Wrap the usual normal equations trick
/////////////////////////////////////////////////////
HPDSolver(LinearOperatorBase<Field> &Matrix,
OperatorFunction<Field> &HermitianSolver,
LinearFunction<Field> &Guess)
: _Matrix(Matrix), _HermitianSolver(HermitianSolver), _Guess(Guess) {};
void operator() (const Field &in, Field &out){
_Guess(in,out);
_HermitianSolver(_Matrix,in,out); //M out = in
}
};
template<class Field> class MdagMSolver : public LinearFunction<Field> {
private:
SparseMatrixBase<Field> & _Matrix;
OperatorFunction<Field> & _HermitianSolver;
LinearFunction<Field> & _Guess;
public:
/////////////////////////////////////////////////////
// Wrap the usual normal equations trick
/////////////////////////////////////////////////////
MdagMSolver(SparseMatrixBase<Field> &Matrix, OperatorFunction<Field> &HermitianSolver,
LinearFunction<Field> &Guess)
: _Matrix(Matrix), _HermitianSolver(HermitianSolver), _Guess(Guess) {};
void operator() (const Field &in, Field &out){
MdagMLinearOperator<SparseMatrixBase<Field>,Field> MdagMOp(_Matrix);
_Guess(in,out);
_HermitianSolver(MdagMOp,in,out); // Mdag M out = Mdag in
}
};
NAMESPACE_END(Grid);
#endif
-46
View File
@@ -1,46 +0,0 @@
#pragma once
namespace Grid {
template<class Field> class PowerMethod
{
public:
template<typename T> static RealD normalise(T& v)
{
RealD nn = norm2(v);
nn = sqrt(nn);
v = v * (1.0/nn);
return nn;
}
RealD operator()(LinearOperatorBase<Field> &HermOp, const Field &src)
{
GridBase *grid = src.Grid();
// quickly get an idea of the largest eigenvalue to more properly normalize the residuum
RealD evalMaxApprox = 0.0;
auto src_n = src;
auto tmp = src;
const int _MAX_ITER_EST_ = 200;
for (int i=0;i<_MAX_ITER_EST_;i++) {
normalise(src_n);
HermOp.HermOp(src_n,tmp);
RealD vnum = real(innerProduct(src_n,tmp)); // HermOp.
RealD vden = norm2(src_n);
RealD na = vnum/vden;
std::cout << GridLogMessage << "PowerMethod: Current approximation of largest eigenvalue " << na << std::endl;
// if ( (fabs(evalMaxApprox/na - 1.0) < 0.0001) || (i==_MAX_ITER_EST_-1) ) {
// evalMaxApprox = na;
// return evalMaxApprox;
// }
evalMaxApprox = na;
src_n = tmp;
}
std::cout << GridLogMessage << " Approximation of largest eigenvalue: " << evalMaxApprox << std::endl;
return evalMaxApprox;
}
};
}
-76
View File
@@ -1,76 +0,0 @@
#pragma once
namespace Grid {
class Band
{
RealD lo, hi;
public:
Band(RealD _lo,RealD _hi)
{
lo=_lo;
hi=_hi;
}
RealD operator() (RealD x){
if ( x>lo && x<hi ){
return 1.0;
} else {
return 0.0;
}
}
};
class PowerSpectrum
{
public:
template<typename T> static RealD normalise(T& v)
{
RealD nn = norm2(v);
nn = sqrt(nn);
v = v * (1.0/nn);
return nn;
}
std::vector<RealD> ranges;
std::vector<int> order;
PowerSpectrum( std::vector<RealD> &bins, std::vector<int> &_order ) : ranges(bins), order(_order) { };
template<class Field>
RealD operator()(LinearOperatorBase<Field> &HermOp, const Field &src)
{
GridBase *grid = src.Grid();
int N=ranges.size();
RealD hi = ranges[N-1];
RealD lo_band = 0.0;
RealD hi_band;
RealD nn=norm2(src);
RealD ss=0.0;
Field tmp = src;
for(int b=0;b<N;b++){
hi_band = ranges[b];
Band Notch(lo_band,hi_band);
Chebyshev<Field> polynomial;
polynomial.Init(0.0,hi,order[b],Notch);
polynomial.JacksonSmooth();
polynomial(HermOp,src,tmp) ;
RealD p=norm2(tmp);
ss=ss+p;
std::cout << GridLogMessage << " PowerSpectrum Band["<<lo_band<<","<<hi_band<<"] power "<<norm2(tmp)/nn<<std::endl;
lo_band=hi_band;
}
std::cout << GridLogMessage << " PowerSpectrum total power "<<ss/nn<<std::endl;
std::cout << GridLogMessage << " PowerSpectrum total power (unnormalised) "<<nn<<std::endl;
return 0;
};
};
}
@@ -1,119 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/PrecConjugateResidual.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_PREC_CONJUGATE_RESIDUAL_H
#define GRID_PREC_CONJUGATE_RESIDUAL_H
NAMESPACE_BEGIN(Grid);
/////////////////////////////////////////////////////////////
// Base classes for iterative processes based on operators
// single input vec, single output vec.
/////////////////////////////////////////////////////////////
template<class Field>
class PrecConjugateResidual : public OperatorFunction<Field> {
public:
RealD Tolerance;
Integer MaxIterations;
int verbose;
LinearFunction<Field> &Preconditioner;
PrecConjugateResidual(RealD tol,Integer maxit,LinearFunction<Field> &Prec) : Tolerance(tol), MaxIterations(maxit), Preconditioner(Prec)
{
verbose=1;
};
void operator() (LinearOperatorBase<Field> &Linop,const Field &src, Field &psi){
RealD a, b, c, d;
RealD cp, ssq,rsq;
RealD rAr, rAAr, rArp;
RealD pAp, pAAp;
GridBase *grid = src.Grid();
Field r(grid), p(grid), Ap(grid), Ar(grid), z(grid);
psi=zero;
r = src;
Preconditioner(r,p);
Linop.HermOpAndNorm(p,Ap,pAp,pAAp);
Ar=Ap;
rAr=pAp;
rAAr=pAAp;
cp =norm2(r);
ssq=norm2(src);
rsq=Tolerance*Tolerance*ssq;
if (verbose) std::cout<<GridLogMessage<<"PrecConjugateResidual: iteration " <<0<<" residual "<<cp<< " target"<< rsq<<std::endl;
for(int k=0;k<MaxIterations;k++){
Preconditioner(Ap,z);
RealD rq= real(innerProduct(Ap,z));
a = rAr/rq;
axpy(psi,a,p,psi);
cp = axpy_norm(r,-a,z,r);
rArp=rAr;
Linop.HermOpAndNorm(r,Ar,rAr,rAAr);
b =rAr/rArp;
axpy(p,b,p,r);
pAAp=axpy_norm(Ap,b,Ap,Ar);
if(verbose) std::cout<<GridLogMessage<<"PrecConjugateResidual: iteration " <<k<<" residual "<<cp<< " target"<< rsq<<std::endl;
if(cp<rsq) {
Linop.HermOp(psi,Ap);
axpy(r,-1.0,src,Ap);
RealD true_resid = norm2(r)/ssq;
std::cout<<GridLogMessage<<"PrecConjugateResidual: Converged on iteration " <<k
<< " computed residual "<<sqrt(cp/ssq)
<< " true residual "<<sqrt(true_resid)
<< " target " <<Tolerance <<std::endl;
return;
}
}
std::cout<<GridLogMessage<<"PrecConjugateResidual did NOT converge"<<std::endl;
assert(0);
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,239 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/PrecGeneralisedConjugateResidual.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_PREC_GCR_H
#define GRID_PREC_GCR_H
///////////////////////////////////////////////////////////////////////////////////////////////////////
//VPGCR Abe and Zhang, 2005.
//INTERNATIONAL JOURNAL OF NUMERICAL ANALYSIS AND MODELING
//Computing and Information Volume 2, Number 2, Pages 147-161
//NB. Likely not original reference since they are focussing on a preconditioner variant.
// but VPGCR was nicely written up in their paper
///////////////////////////////////////////////////////////////////////////////////////////////////////
NAMESPACE_BEGIN(Grid);
#define GCRLogLevel std::cout << GridLogMessage <<std::string(level,'\t')<< " Level "<<level<<" "
template<class Field>
class PrecGeneralisedConjugateResidual : public LinearFunction<Field> {
public:
using LinearFunction<Field>::operator();
RealD Tolerance;
Integer MaxIterations;
int verbose;
int mmax;
int nstep;
int steps;
int level;
GridStopWatch PrecTimer;
GridStopWatch MatTimer;
GridStopWatch LinalgTimer;
LinearFunction<Field> &Preconditioner;
LinearOperatorBase<Field> &Linop;
void Level(int lv) { level=lv; };
PrecGeneralisedConjugateResidual(RealD tol,Integer maxit,LinearOperatorBase<Field> &_Linop,LinearFunction<Field> &Prec,int _mmax,int _nstep) :
Tolerance(tol),
MaxIterations(maxit),
Linop(_Linop),
Preconditioner(Prec),
mmax(_mmax),
nstep(_nstep)
{
level=1;
verbose=1;
};
void operator() (const Field &src, Field &psi){
psi=Zero();
RealD cp, ssq,rsq;
ssq=norm2(src);
rsq=Tolerance*Tolerance*ssq;
Field r(src.Grid());
PrecTimer.Reset();
MatTimer.Reset();
LinalgTimer.Reset();
GridStopWatch SolverTimer;
SolverTimer.Start();
steps=0;
for(int k=0;k<MaxIterations;k++){
cp=GCRnStep(src,psi,rsq);
GCRLogLevel <<"PGCR("<<mmax<<","<<nstep<<") "<< steps <<" steps cp = "<<cp<<" target "<<rsq <<std::endl;
if(cp<rsq) {
SolverTimer.Stop();
Linop.HermOp(psi,r);
axpy(r,-1.0,src,r);
RealD tr = norm2(r);
GCRLogLevel<<"PGCR: Converged on iteration " <<steps
<< " computed residual "<<sqrt(cp/ssq)
<< " true residual " <<sqrt(tr/ssq)
<< " target " <<Tolerance <<std::endl;
GCRLogLevel<<"PGCR Time elapsed: Total "<< SolverTimer.Elapsed() <<std::endl;
/*
GCRLogLevel<<"PGCR Time elapsed: Precon "<< PrecTimer.Elapsed() <<std::endl;
GCRLogLevel<<"PGCR Time elapsed: Matrix "<< MatTimer.Elapsed() <<std::endl;
GCRLogLevel<<"PGCR Time elapsed: Linalg "<< LinalgTimer.Elapsed() <<std::endl;
*/
return;
}
}
GCRLogLevel<<"Variable Preconditioned GCR did not converge"<<std::endl;
// assert(0);
}
RealD GCRnStep(const Field &src, Field &psi,RealD rsq){
RealD cp;
RealD a, b;
RealD zAz, zAAz;
RealD rq;
GridBase *grid = src.Grid();
Field r(grid);
Field z(grid);
Field tmp(grid);
Field ttmp(grid);
Field Az(grid);
////////////////////////////////
// history for flexible orthog
////////////////////////////////
std::vector<Field> q(mmax,grid);
std::vector<Field> p(mmax,grid);
std::vector<RealD> qq(mmax);
GCRLogLevel<< "PGCR nStep("<<nstep<<")"<<std::endl;
//////////////////////////////////
// initial guess x0 is taken as nonzero.
// r0=src-A x0 = src
//////////////////////////////////
MatTimer.Start();
Linop.HermOpAndNorm(psi,Az,zAz,zAAz);
MatTimer.Stop();
LinalgTimer.Start();
r=src-Az;
LinalgTimer.Stop();
GCRLogLevel<< "PGCR true residual r = src - A psi "<<norm2(r) <<std::endl;
/////////////////////
// p = Prec(r)
/////////////////////
PrecTimer.Start();
Preconditioner(r,z);
PrecTimer.Stop();
MatTimer.Start();
Linop.HermOpAndNorm(z,Az,zAz,zAAz);
MatTimer.Stop();
LinalgTimer.Start();
//p[0],q[0],qq[0]
p[0]= z;
q[0]= Az;
qq[0]= zAAz;
cp =norm2(r);
LinalgTimer.Stop();
for(int k=0;k<nstep;k++){
steps++;
int kp = k+1;
int peri_k = k %mmax;
int peri_kp= kp%mmax;
LinalgTimer.Start();
rq= real(innerProduct(r,q[peri_k])); // what if rAr not real?
a = rq/qq[peri_k];
axpy(psi,a,p[peri_k],psi);
cp = axpy_norm(r,-a,q[peri_k],r);
LinalgTimer.Stop();
GCRLogLevel<< "PGCR step["<<steps<<"] resid " << cp << " target " <<rsq<<std::endl;
if((k==nstep-1)||(cp<rsq)){
return cp;
}
PrecTimer.Start();
Preconditioner(r,z);// solve Az = r
PrecTimer.Stop();
MatTimer.Start();
Linop.HermOpAndNorm(z,Az,zAz,zAAz);
MatTimer.Stop();
LinalgTimer.Start();
q[peri_kp]=Az;
p[peri_kp]=z;
int northog = ((kp)>(mmax-1))?(mmax-1):(kp); // if more than mmax done, we orthog all mmax history.
for(int back=0;back<northog;back++){
int peri_back=(k-back)%mmax; assert((k-back)>=0);
b=-real(innerProduct(q[peri_back],Az))/qq[peri_back];
p[peri_kp]=p[peri_kp]+b*p[peri_back];
q[peri_kp]=q[peri_kp]+b*q[peri_back];
}
qq[peri_kp]=norm2(q[peri_kp]); // could use axpy_norm
LinalgTimer.Stop();
}
assert(0); // never reached
return cp;
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,242 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/PrecGeneralisedConjugateResidual.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_PREC_GCR_NON_HERM_H
#define GRID_PREC_GCR_NON_HERM_H
///////////////////////////////////////////////////////////////////////////////////////////////////////
//VPGCR Abe and Zhang, 2005.
//INTERNATIONAL JOURNAL OF NUMERICAL ANALYSIS AND MODELING
//Computing and Information Volume 2, Number 2, Pages 147-161
//NB. Likely not original reference since they are focussing on a preconditioner variant.
// but VPGCR was nicely written up in their paper
///////////////////////////////////////////////////////////////////////////////////////////////////////
NAMESPACE_BEGIN(Grid);
#define GCRLogLevel std::cout << GridLogMessage <<std::string(level,'\t')<< " Level "<<level<<" "
template<class Field>
class PrecGeneralisedConjugateResidualNonHermitian : public LinearFunction<Field> {
public:
using LinearFunction<Field>::operator();
RealD Tolerance;
Integer MaxIterations;
int verbose;
int mmax;
int nstep;
int steps;
int level;
GridStopWatch PrecTimer;
GridStopWatch MatTimer;
GridStopWatch LinalgTimer;
LinearFunction<Field> &Preconditioner;
LinearOperatorBase<Field> &Linop;
void Level(int lv) { level=lv; };
PrecGeneralisedConjugateResidualNonHermitian(RealD tol,Integer maxit,LinearOperatorBase<Field> &_Linop,LinearFunction<Field> &Prec,int _mmax,int _nstep) :
Tolerance(tol),
MaxIterations(maxit),
Linop(_Linop),
Preconditioner(Prec),
mmax(_mmax),
nstep(_nstep)
{
level=1;
verbose=1;
};
void operator() (const Field &src, Field &psi){
psi=Zero();
RealD cp, ssq,rsq;
ssq=norm2(src);
rsq=Tolerance*Tolerance*ssq;
Field r(src.Grid());
PrecTimer.Reset();
MatTimer.Reset();
LinalgTimer.Reset();
GridStopWatch SolverTimer;
SolverTimer.Start();
steps=0;
for(int k=0;k<MaxIterations;k++){
cp=GCRnStep(src,psi,rsq);
GCRLogLevel <<"PGCR("<<mmax<<","<<nstep<<") "<< steps <<" steps cp = "<<cp<<" target "<<rsq <<std::endl;
if(cp<rsq) {
SolverTimer.Stop();
Linop.Op(psi,r);
axpy(r,-1.0,src,r);
RealD tr = norm2(r);
GCRLogLevel<<"PGCR: Converged on iteration " <<steps
<< " computed residual "<<sqrt(cp/ssq)
<< " true residual " <<sqrt(tr/ssq)
<< " target " <<Tolerance <<std::endl;
GCRLogLevel<<"PGCR Time elapsed: Total "<< SolverTimer.Elapsed() <<std::endl;
return;
}
}
GCRLogLevel<<"Variable Preconditioned GCR did not converge"<<std::endl;
// assert(0);
}
RealD GCRnStep(const Field &src, Field &psi,RealD rsq){
RealD cp;
ComplexD a, b;
// ComplexD zAz;
RealD zAAz;
ComplexD rq;
GridBase *grid = src.Grid();
Field r(grid);
Field z(grid);
Field tmp(grid);
Field ttmp(grid);
Field Az(grid);
////////////////////////////////
// history for flexible orthog
////////////////////////////////
std::vector<Field> q(mmax,grid);
std::vector<Field> p(mmax,grid);
std::vector<RealD> qq(mmax);
GCRLogLevel<< "PGCR nStep("<<nstep<<")"<<std::endl;
//////////////////////////////////
// initial guess x0 is taken as nonzero.
// r0=src-A x0 = src
//////////////////////////////////
MatTimer.Start();
Linop.Op(psi,Az);
// zAz = innerProduct(Az,psi);
zAAz= norm2(Az);
MatTimer.Stop();
LinalgTimer.Start();
r=src-Az;
LinalgTimer.Stop();
GCRLogLevel<< "PGCR true residual r = src - A psi "<<norm2(r) <<std::endl;
/////////////////////
// p = Prec(r)
/////////////////////
PrecTimer.Start();
Preconditioner(r,z);
PrecTimer.Stop();
MatTimer.Start();
Linop.Op(z,Az);
MatTimer.Stop();
LinalgTimer.Start();
// zAz = innerProduct(Az,psi);
zAAz= norm2(Az);
//p[0],q[0],qq[0]
p[0]= z;
q[0]= Az;
qq[0]= zAAz;
cp =norm2(r);
LinalgTimer.Stop();
for(int k=0;k<nstep;k++){
steps++;
int kp = k+1;
int peri_k = k %mmax;
int peri_kp= kp%mmax;
LinalgTimer.Start();
rq= innerProduct(q[peri_k],r); // what if rAr not real?
a = rq/qq[peri_k];
axpy(psi,a,p[peri_k],psi);
cp = axpy_norm(r,-a,q[peri_k],r);
LinalgTimer.Stop();
GCRLogLevel<< "PGCR step["<<steps<<"] resid " << cp << " target " <<rsq<<std::endl;
if((k==nstep-1)||(cp<rsq)){
return cp;
}
PrecTimer.Start();
Preconditioner(r,z);// solve Az = r
PrecTimer.Stop();
MatTimer.Start();
Linop.Op(z,Az);
MatTimer.Stop();
// zAz = innerProduct(Az,psi);
zAAz= norm2(Az);
LinalgTimer.Start();
q[peri_kp]=Az;
p[peri_kp]=z;
int northog = ((kp)>(mmax-1))?(mmax-1):(kp); // if more than mmax done, we orthog all mmax history.
for(int back=0;back<northog;back++){
int peri_back=(k-back)%mmax; assert((k-back)>=0);
b=-real(innerProduct(q[peri_back],Az))/qq[peri_back];
p[peri_kp]=p[peri_kp]+b*p[peri_back];
q[peri_kp]=q[peri_kp]+b*q[peri_back];
}
qq[peri_kp]=norm2(q[peri_kp]); // could use axpy_norm
LinalgTimer.Stop();
}
assert(0); // never reached
return cp;
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,371 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithmsf/iterative/QuasiMinimalResidual.h
Copyright (C) 2019
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
template<class Field>
RealD innerG5ProductReal(Field &l, Field &r)
{
Gamma G5(Gamma::Algebra::Gamma5);
Field tmp(l.Grid());
// tmp = G5*r;
G5R5(tmp,r);
ComplexD ip =innerProduct(l,tmp);
std::cout << "innerProductRealG5R5 "<<ip<<std::endl;
return ip.real();
}
template<class Field>
class QuasiMinimalResidual : public OperatorFunction<Field> {
public:
using OperatorFunction<Field>::operator();
bool ErrorOnNoConverge;
RealD Tolerance;
Integer MaxIterations;
Integer IterationCount;
QuasiMinimalResidual(RealD tol,
Integer maxit,
bool err_on_no_conv = true)
: Tolerance(tol)
, MaxIterations(maxit)
, ErrorOnNoConverge(err_on_no_conv)
{};
#if 1
void operator()(LinearOperatorBase<Field> &LinOp, const Field &b, Field &x)
{
RealD resid;
IterationCount=0;
RealD rho, rho_1, xi, gamma, gamma_1, theta, theta_1;
RealD eta, delta, ep, beta;
GridBase *Grid = b.Grid();
Field r(Grid), d(Grid), s(Grid);
Field v(Grid), w(Grid), y(Grid), z(Grid);
Field v_tld(Grid), w_tld(Grid), y_tld(Grid), z_tld(Grid);
Field p(Grid), q(Grid), p_tld(Grid);
Real normb = norm2(b);
LinOp.Op(x,r); r = b - r;
assert(normb> 0.0);
resid = norm2(r)/normb;
if (resid <= Tolerance) {
return;
}
v_tld = r;
y = v_tld;
rho = norm2(y);
// Take Gamma5 conjugate
// Gamma G5(Gamma::Algebra::Gamma5);
// G5R5(w_tld,r);
// w_tld = G5* v_tld;
w_tld=v_tld;
z = w_tld;
xi = norm2(z);
gamma = 1.0;
eta = -1.0;
theta = 0.0;
for (int i = 1; i <= MaxIterations; i++) {
// Breakdown tests
assert( rho != 0.0);
assert( xi != 0.0);
v = (1. / rho) * v_tld;
y = (1. / rho) * y;
w = (1. / xi) * w_tld;
z = (1. / xi) * z;
ComplexD Zdelta = innerProduct(z, y); // Complex?
std::cout << "Zdelta "<<Zdelta<<std::endl;
delta = Zdelta.real();
y_tld = y;
z_tld = z;
if (i > 1) {
p = y_tld - (xi * delta / ep) * p;
q = z_tld - (rho * delta / ep) * q;
} else {
p = y_tld;
q = z_tld;
}
LinOp.Op(p,p_tld); // p_tld = A * p;
ComplexD Zep = innerProduct(q, p_tld);
ep=Zep.real();
std::cout << "Zep "<<Zep <<std::endl;
// Complex Audit
assert(abs(ep)>0);
beta = ep / delta;
assert(abs(beta)>0);
v_tld = p_tld - beta * v;
y = v_tld;
rho_1 = rho;
rho = norm2(y);
LinOp.AdjOp(q,w_tld);
w_tld = w_tld - beta * w;
z = w_tld;
xi = norm2(z);
gamma_1 = gamma;
theta_1 = theta;
theta = rho / (gamma_1 * beta);
gamma = 1.0 / sqrt(1.0 + theta * theta);
std::cout << "theta "<<theta<<std::endl;
std::cout << "gamma "<<gamma<<std::endl;
assert(abs(gamma)> 0.0);
eta = -eta * rho_1 * gamma* gamma / (beta * gamma_1 * gamma_1);
if (i > 1) {
d = eta * p + (theta_1 * theta_1 * gamma * gamma) * d;
s = eta * p_tld + (theta_1 * theta_1 * gamma * gamma) * s;
} else {
d = eta * p;
s = eta * p_tld;
}
x =x+d; // update approximation vector
r =r-s; // compute residual
if ((resid = norm2(r) / normb) <= Tolerance) {
return;
}
std::cout << "Iteration "<<i<<" resid " << resid<<std::endl;
}
assert(0);
return; // no convergence
}
#else
// QMRg5 SMP thesis
void operator()(LinearOperatorBase<Field> &LinOp, const Field &b, Field &x)
{
// Real scalars
GridBase *grid = b.Grid();
Field r(grid);
Field p_m(grid), p_m_minus_1(grid), p_m_minus_2(grid);
Field v_m(grid), v_m_minus_1(grid), v_m_plus_1(grid);
Field tmp(grid);
RealD w;
RealD z1, z2;
RealD delta_m, delta_m_minus_1;
RealD c_m_plus_1, c_m, c_m_minus_1;
RealD s_m_plus_1, s_m, s_m_minus_1;
RealD alpha, beta, gamma, epsilon;
RealD mu, nu, rho, theta, xi, chi;
RealD mod2r, mod2b;
RealD tau2, target2;
mod2b=norm2(b);
/////////////////////////
// Initial residual
/////////////////////////
LinOp.Op(x,tmp);
r = b - tmp;
/////////////////////////
// \mu = \rho = |r_0|
/////////////////////////
mod2r = norm2(r);
rho = sqrt( mod2r);
mu=rho;
std::cout << "QuasiMinimalResidual rho "<< rho<<std::endl;
/////////////////////////
// Zero negative history
/////////////////////////
v_m_plus_1 = Zero();
v_m_minus_1 = Zero();
p_m_minus_1 = Zero();
p_m_minus_2 = Zero();
// v0
v_m = (1.0/rho)*r;
/////////////////////////
// Initial coeffs
/////////////////////////
delta_m_minus_1 = 1.0;
c_m_minus_1 = 1.0;
c_m = 1.0;
s_m_minus_1 = 0.0;
s_m = 0.0;
/////////////////////////
// Set up convergence check
/////////////////////////
tau2 = mod2r;
target2 = mod2b * Tolerance*Tolerance;
for(int iter = 0 ; iter < MaxIterations; iter++){
/////////////////////////
// \delta_m = (v_m, \gamma_5 v_m)
/////////////////////////
delta_m = innerG5ProductReal(v_m,v_m);
std::cout << "QuasiMinimalResidual delta_m "<< delta_m<<std::endl;
/////////////////////////
// tmp = A v_m
/////////////////////////
LinOp.Op(v_m,tmp);
/////////////////////////
// \alpha = (v_m, \gamma_5 temp) / \delta_m
/////////////////////////
alpha = innerG5ProductReal(v_m,tmp);
alpha = alpha/delta_m ;
std::cout << "QuasiMinimalResidual alpha "<< alpha<<std::endl;
/////////////////////////
// \beta = \rho \delta_m / \delta_{m-1}
/////////////////////////
beta = rho * delta_m / delta_m_minus_1;
std::cout << "QuasiMinimalResidual beta "<< beta<<std::endl;
/////////////////////////
// \tilde{v}_{m+1} = temp - \alpha v_m - \beta v_{m-1}
/////////////////////////
v_m_plus_1 = tmp - alpha*v_m - beta*v_m_minus_1;
///////////////////////////////
// \rho = || \tilde{v}_{m+1} ||
///////////////////////////////
rho = sqrt( norm2(v_m_plus_1) );
std::cout << "QuasiMinimalResidual rho "<< rho<<std::endl;
///////////////////////////////
// v_{m+1} = \tilde{v}_{m+1}
///////////////////////////////
v_m_plus_1 = (1.0 / rho) * v_m_plus_1;
////////////////////////////////
// QMR recurrence coefficients.
////////////////////////////////
theta = s_m_minus_1 * beta;
gamma = c_m_minus_1 * beta;
epsilon = c_m * gamma + s_m * alpha;
xi = -s_m * gamma + c_m * alpha;
nu = sqrt( xi*xi + rho*rho );
c_m_plus_1 = fabs(xi) / nu;
if ( xi == 0.0 ) {
s_m_plus_1 = 1.0;
} else {
s_m_plus_1 = c_m_plus_1 * rho / xi;
}
chi = c_m_plus_1 * xi + s_m_plus_1 * rho;
std::cout << "QuasiMinimalResidual coeffs "<< theta <<" "<<gamma<<" "<< epsilon<<" "<< xi<<" "<< nu<<std::endl;
std::cout << "QuasiMinimalResidual coeffs "<< chi <<std::endl;
////////////////////////////////
//p_m=(v_m - \epsilon p_{m-1} - \theta p_{m-2}) / \chi
////////////////////////////////
p_m = (1.0/chi) * v_m - (epsilon/chi) * p_m_minus_1 - (theta/chi) * p_m_minus_2;
////////////////////////////////////////////////////////////////
// \psi = \psi + c_{m+1} \mu p_m
////////////////////////////////////////////////////////////////
x = x + ( c_m_plus_1 * mu ) * p_m;
////////////////////////////////////////
//
////////////////////////////////////////
mu = -s_m_plus_1 * mu;
delta_m_minus_1 = delta_m;
c_m_minus_1 = c_m;
c_m = c_m_plus_1;
s_m_minus_1 = s_m;
s_m = s_m_plus_1;
////////////////////////////////////
// Could use pointer swizzle games.
////////////////////////////////////
v_m_minus_1 = v_m;
v_m = v_m_plus_1;
p_m_minus_2 = p_m_minus_1;
p_m_minus_1 = p_m;
/////////////////////////////////////
// Convergence checks
/////////////////////////////////////
z1 = RealD(iter+1.0);
z2 = z1 + 1.0;
tau2 = tau2 *( z2 / z1 ) * s_m * s_m;
std::cout << " QuasiMinimumResidual iteration "<< iter<<std::endl;
std::cout << " QuasiMinimumResidual tau bound "<< tau2<<std::endl;
// Compute true residual
mod2r = tau2;
if ( 1 || (tau2 < (100.0 * target2)) ) {
LinOp.Op(x,tmp);
r = b - tmp;
mod2r = norm2(r);
std::cout << " QuasiMinimumResidual true residual is "<< mod2r<<std::endl;
}
if ( mod2r < target2 ) {
std::cout << " QuasiMinimumResidual has converged"<<std::endl;
return;
}
}
}
#endif
};
NAMESPACE_END(Grid);
-732
View File
@@ -1,732 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/SchurRedBlack.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_SCHUR_RED_BLACK_H
#define GRID_SCHUR_RED_BLACK_H
/*
* Red black Schur decomposition
*
* M = (Mee Meo) = (1 0 ) (Mee 0 ) (1 Mee^{-1} Meo)
* (Moe Moo) (Moe Mee^-1 1 ) (0 Moo-Moe Mee^-1 Meo) (0 1 )
* = L D U
*
* L^-1 = (1 0 )
* (-MoeMee^{-1} 1 )
* L^{dag} = ( 1 Mee^{-dag} Moe^{dag} )
* ( 0 1 )
* L^{-d} = ( 1 -Mee^{-dag} Moe^{dag} )
* ( 0 1 )
*
* U^-1 = (1 -Mee^{-1} Meo)
* (0 1 )
* U^{dag} = ( 1 0)
* (Meo^dag Mee^{-dag} 1)
* U^{-dag} = ( 1 0)
* (-Meo^dag Mee^{-dag} 1)
***********************
* M psi = eta
***********************
*Odd
* i) D_oo psi_o = L^{-1} eta_o
* eta_o' = (D_oo)^dag (eta_o - Moe Mee^{-1} eta_e)
*
* Wilson:
* (D_oo)^{\dag} D_oo psi_o = (D_oo)^dag L^{-1} eta_o
* Stag:
* D_oo psi_o = L^{-1} eta = (eta_o - Moe Mee^{-1} eta_e)
*
* L^-1 eta_o= (1 0 ) (e
* (-MoeMee^{-1} 1 )
*
*Even
* ii) Mee psi_e + Meo psi_o = src_e
*
* => sol_e = M_ee^-1 * ( src_e - Meo sol_o )...
*
*
* TODO: Other options:
*
* a) change checkerboards for Schur e<->o
*
* Left precon by Moo^-1
* b) Doo^{dag} M_oo^-dag Moo^-1 Doo psi_0 = (D_oo)^dag M_oo^-dag Moo^-1 L^{-1} eta_o
* eta_o' = (D_oo)^dag M_oo^-dag Moo^-1 (eta_o - Moe Mee^{-1} eta_e)
*
* Right precon by Moo^-1
* c) M_oo^-dag Doo^{dag} Doo Moo^-1 phi_0 = M_oo^-dag (D_oo)^dag L^{-1} eta_o
* eta_o' = M_oo^-dag (D_oo)^dag (eta_o - Moe Mee^{-1} eta_e)
* psi_o = M_oo^-1 phi_o
* TODO: Deflation
*/
namespace Grid {
///////////////////////////////////////////////////////////////////////////////////////////////////////
// Use base class to share code
///////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////////////////////////////////
// Take a matrix and form a Red Black solver calling a Herm solver
// Use of RB info prevents making SchurRedBlackSolve conform to standard interface
///////////////////////////////////////////////////////////////////////////////////////////////////////
template<class Field> class SchurRedBlackBase {
protected:
typedef CheckerBoardedSparseMatrixBase<Field> Matrix;
OperatorFunction<Field> & _HermitianRBSolver;
int CBfactorise;
bool subGuess;
bool useSolnAsInitGuess; // if true user-supplied solution vector is used as initial guess for solver
public:
SchurRedBlackBase(OperatorFunction<Field> &HermitianRBSolver, const bool initSubGuess = false,
const bool _solnAsInitGuess = false) :
_HermitianRBSolver(HermitianRBSolver),
useSolnAsInitGuess(_solnAsInitGuess)
{
CBfactorise = 0;
subtractGuess(initSubGuess);
};
void subtractGuess(const bool initSubGuess)
{
subGuess = initSubGuess;
}
bool isSubtractGuess(void)
{
return subGuess;
}
/////////////////////////////////////////////////////////////
// Shared code
/////////////////////////////////////////////////////////////
void operator() (Matrix & _Matrix,const Field &in, Field &out){
ZeroGuesser<Field> guess;
(*this)(_Matrix,in,out,guess);
}
void operator()(Matrix &_Matrix, const std::vector<Field> &in, std::vector<Field> &out)
{
ZeroGuesser<Field> guess;
(*this)(_Matrix,in,out,guess);
}
void RedBlackSource(Matrix &_Matrix, const std::vector<Field> &in, std::vector<Field> &src_o)
{
GridBase *grid = _Matrix.RedBlackGrid();
Field tmp(grid);
int nblock = in.size();
for(int b=0;b<nblock;b++){
RedBlackSource(_Matrix,in[b],tmp,src_o[b]);
}
}
// James can write his own deflated guesser
// with optimised code for the inner products
// RedBlackSolveSplitGrid();
// RedBlackSolve(_Matrix,src_o,sol_o);
void RedBlackSolution(Matrix &_Matrix, const std::vector<Field> &in, const std::vector<Field> &sol_o, std::vector<Field> &out)
{
GridBase *grid = _Matrix.RedBlackGrid();
Field tmp(grid);
int nblock = in.size();
for(int b=0;b<nblock;b++) {
pickCheckerboard(Even,tmp,in[b]);
RedBlackSolution(_Matrix,sol_o[b],tmp,out[b]);
}
}
template<class Guesser>
void operator()(Matrix &_Matrix, const std::vector<Field> &in, std::vector<Field> &out,Guesser &guess)
{
GridBase *grid = _Matrix.RedBlackGrid();
GridBase *fgrid= _Matrix.Grid();
int nblock = in.size();
std::vector<Field> src_o(nblock,grid);
std::vector<Field> sol_o(nblock,grid);
std::vector<Field> guess_save;
Field resid(fgrid);
Field tmp(grid);
////////////////////////////////////////////////
// Prepare RedBlack source
////////////////////////////////////////////////
RedBlackSource(_Matrix,in,src_o);
// for(int b=0;b<nblock;b++){
// RedBlackSource(_Matrix,in[b],tmp,src_o[b]);
// }
////////////////////////////////////////////////
// Make the guesses
////////////////////////////////////////////////
if ( subGuess ) guess_save.resize(nblock,grid);
if(useSolnAsInitGuess) {
for(int b=0;b<nblock;b++){
pickCheckerboard(Odd, sol_o[b], out[b]);
}
} else {
guess(src_o, sol_o);
}
if ( subGuess ) {
for(int b=0;b<nblock;b++){
guess_save[b] = sol_o[b];
}
}
//////////////////////////////////////////////////////////////
// Call the block solver
//////////////////////////////////////////////////////////////
std::cout<<GridLogMessage << "SchurRedBlackBase calling the solver for "<<nblock<<" RHS" <<std::endl;
RedBlackSolve(_Matrix,src_o,sol_o);
////////////////////////////////////////////////
// A2A boolean behavioural control & reconstruct other checkerboard
////////////////////////////////////////////////
for(int b=0;b<nblock;b++) {
if (subGuess) sol_o[b] = sol_o[b] - guess_save[b];
///////// Needs even source //////////////
pickCheckerboard(Even,tmp,in[b]);
RedBlackSolution(_Matrix,sol_o[b],tmp,out[b]);
/////////////////////////////////////////////////
// Check unprec residual if possible
/////////////////////////////////////////////////
if ( ! subGuess ) {
_Matrix.M(out[b],resid);
resid = resid-in[b];
RealD ns = norm2(in[b]);
RealD nr = norm2(resid);
std::cout<<GridLogMessage<< "SchurRedBlackBase solver true unprec resid["<<b<<"] "<<std::sqrt(nr/ns) << std::endl;
} else {
std::cout<<GridLogMessage<< "SchurRedBlackBase Guess subtracted after solve["<<b<<"] " << std::endl;
}
}
}
template<class Guesser>
void operator() (Matrix & _Matrix,const Field &in, Field &out,Guesser &guess){
// FIXME CGdiagonalMee not implemented virtual function
// FIXME use CBfactorise to control schur decomp
GridBase *grid = _Matrix.RedBlackGrid();
GridBase *fgrid= _Matrix.Grid();
Field resid(fgrid);
Field src_o(grid);
Field src_e(grid);
Field sol_o(grid);
////////////////////////////////////////////////
// RedBlack source
////////////////////////////////////////////////
RedBlackSource(_Matrix,in,src_e,src_o);
////////////////////////////////
// Construct the guess
////////////////////////////////
if(useSolnAsInitGuess) {
pickCheckerboard(Odd, sol_o, out);
} else {
guess(src_o,sol_o);
}
Field guess_save(grid);
guess_save = sol_o;
//////////////////////////////////////////////////////////////
// Call the red-black solver
//////////////////////////////////////////////////////////////
RedBlackSolve(_Matrix,src_o,sol_o);
////////////////////////////////////////////////
// Fionn A2A boolean behavioural control
////////////////////////////////////////////////
if (subGuess) sol_o= sol_o-guess_save;
///////////////////////////////////////////////////
// RedBlack solution needs the even source
///////////////////////////////////////////////////
RedBlackSolution(_Matrix,sol_o,src_e,out);
// Verify the unprec residual
if ( ! subGuess ) {
_Matrix.M(out,resid);
resid = resid-in;
RealD ns = norm2(in);
RealD nr = norm2(resid);
std::cout<<GridLogMessage << "SchurRedBlackBase solver true unprec resid "<< std::sqrt(nr/ns) << std::endl;
} else {
std::cout << GridLogMessage << "SchurRedBlackBase Guess subtracted after solve." << std::endl;
}
}
/////////////////////////////////////////////////////////////
// Override in derived.
/////////////////////////////////////////////////////////////
virtual void RedBlackSource (Matrix & _Matrix,const Field &src, Field &src_e,Field &src_o) =0;
virtual void RedBlackSolution(Matrix & _Matrix,const Field &sol_o, const Field &src_e,Field &sol) =0;
virtual void RedBlackSolve (Matrix & _Matrix,const Field &src_o, Field &sol_o) =0;
virtual void RedBlackSolve (Matrix & _Matrix,const std::vector<Field> &src_o, std::vector<Field> &sol_o)=0;
};
template<class Field> class SchurRedBlackStaggeredSolve : public SchurRedBlackBase<Field> {
public:
typedef CheckerBoardedSparseMatrixBase<Field> Matrix;
SchurRedBlackStaggeredSolve(OperatorFunction<Field> &HermitianRBSolver, const bool initSubGuess = false,
const bool _solnAsInitGuess = false)
: SchurRedBlackBase<Field> (HermitianRBSolver,initSubGuess,_solnAsInitGuess)
{
}
//////////////////////////////////////////////////////
// Override RedBlack specialisation
//////////////////////////////////////////////////////
virtual void RedBlackSource(Matrix & _Matrix,const Field &src, Field &src_e,Field &src_o)
{
GridBase *grid = _Matrix.RedBlackGrid();
GridBase *fgrid= _Matrix.Grid();
Field tmp(grid);
Field Mtmp(grid);
pickCheckerboard(Even,src_e,src);
pickCheckerboard(Odd ,src_o,src);
/////////////////////////////////////////////////////
// src_o = (source_o - Moe MeeInv source_e)
/////////////////////////////////////////////////////
_Matrix.MooeeInv(src_e,tmp); assert( tmp.Checkerboard() ==Even);
_Matrix.Meooe (tmp,Mtmp); assert( Mtmp.Checkerboard() ==Odd);
tmp=src_o-Mtmp; assert( tmp.Checkerboard() ==Odd);
_Matrix.Mooee(tmp,src_o); // Extra factor of "m" in source from dumb choice of matrix norm.
}
virtual void RedBlackSolution(Matrix & _Matrix,const Field &sol_o, const Field &src_e_c,Field &sol)
{
GridBase *grid = _Matrix.RedBlackGrid();
GridBase *fgrid= _Matrix.Grid();
Field tmp(grid);
Field sol_e(grid);
Field src_e(grid);
src_e = src_e_c; // Const correctness
///////////////////////////////////////////////////
// sol_e = M_ee^-1 * ( src_e - Meo sol_o )...
///////////////////////////////////////////////////
_Matrix.Meooe(sol_o,tmp); assert( tmp.Checkerboard() ==Even);
src_e = src_e-tmp; assert( src_e.Checkerboard() ==Even);
_Matrix.MooeeInv(src_e,sol_e); assert( sol_e.Checkerboard() ==Even);
setCheckerboard(sol,sol_e); assert( sol_e.Checkerboard() ==Even);
setCheckerboard(sol,sol_o); assert( sol_o.Checkerboard() ==Odd );
}
virtual void RedBlackSolve (Matrix & _Matrix,const Field &src_o, Field &sol_o)
{
SchurStaggeredOperator<Matrix,Field> _HermOpEO(_Matrix);
this->_HermitianRBSolver(_HermOpEO,src_o,sol_o); assert(sol_o.Checkerboard()==Odd);
};
virtual void RedBlackSolve (Matrix & _Matrix,const std::vector<Field> &src_o, std::vector<Field> &sol_o)
{
SchurStaggeredOperator<Matrix,Field> _HermOpEO(_Matrix);
this->_HermitianRBSolver(_HermOpEO,src_o,sol_o);
}
};
template<class Field> using SchurRedBlackStagSolve = SchurRedBlackStaggeredSolve<Field>;
///////////////////////////////////////////////////////////////////////////////////////////////////////
// Site diagonal has Mooee on it.
///////////////////////////////////////////////////////////////////////////////////////////////////////
template<class Field> class SchurRedBlackDiagMooeeSolve : public SchurRedBlackBase<Field> {
public:
typedef CheckerBoardedSparseMatrixBase<Field> Matrix;
SchurRedBlackDiagMooeeSolve(OperatorFunction<Field> &HermitianRBSolver, const bool initSubGuess = false,
const bool _solnAsInitGuess = false)
: SchurRedBlackBase<Field> (HermitianRBSolver,initSubGuess,_solnAsInitGuess) {};
//////////////////////////////////////////////////////
// Override RedBlack specialisation
//////////////////////////////////////////////////////
virtual void RedBlackSource(Matrix & _Matrix,const Field &src, Field &src_e,Field &src_o)
{
GridBase *grid = _Matrix.RedBlackGrid();
GridBase *fgrid= _Matrix.Grid();
Field tmp(grid);
Field Mtmp(grid);
pickCheckerboard(Even,src_e,src);
pickCheckerboard(Odd ,src_o,src);
/////////////////////////////////////////////////////
// src_o = Mdag * (source_o - Moe MeeInv source_e)
/////////////////////////////////////////////////////
_Matrix.MooeeInv(src_e,tmp); assert( tmp.Checkerboard() ==Even);
_Matrix.Meooe (tmp,Mtmp); assert( Mtmp.Checkerboard() ==Odd);
tmp=src_o-Mtmp; assert( tmp.Checkerboard() ==Odd);
// get the right MpcDag
SchurDiagMooeeOperator<Matrix,Field> _HermOpEO(_Matrix);
_HermOpEO.MpcDag(tmp,src_o); assert(src_o.Checkerboard() ==Odd);
}
virtual void RedBlackSolution(Matrix & _Matrix,const Field &sol_o, const Field &src_e,Field &sol)
{
GridBase *grid = _Matrix.RedBlackGrid();
GridBase *fgrid= _Matrix.Grid();
Field tmp(grid);
Field sol_e(grid);
Field src_e_i(grid);
///////////////////////////////////////////////////
// sol_e = M_ee^-1 * ( src_e - Meo sol_o )...
///////////////////////////////////////////////////
_Matrix.Meooe(sol_o,tmp); assert( tmp.Checkerboard() ==Even);
src_e_i = src_e-tmp; assert( src_e_i.Checkerboard() ==Even);
_Matrix.MooeeInv(src_e_i,sol_e); assert( sol_e.Checkerboard() ==Even);
setCheckerboard(sol,sol_e); assert( sol_e.Checkerboard() ==Even);
setCheckerboard(sol,sol_o); assert( sol_o.Checkerboard() ==Odd );
}
virtual void RedBlackSolve (Matrix & _Matrix,const Field &src_o, Field &sol_o)
{
SchurDiagMooeeOperator<Matrix,Field> _HermOpEO(_Matrix);
this->_HermitianRBSolver(_HermOpEO,src_o,sol_o); assert(sol_o.Checkerboard()==Odd);
};
virtual void RedBlackSolve (Matrix & _Matrix,const std::vector<Field> &src_o, std::vector<Field> &sol_o)
{
SchurDiagMooeeOperator<Matrix,Field> _HermOpEO(_Matrix);
this->_HermitianRBSolver(_HermOpEO,src_o,sol_o);
}
};
template<class Field> class NonHermitianSchurRedBlackDiagMooeeSolve : public SchurRedBlackBase<Field>
{
public:
typedef CheckerBoardedSparseMatrixBase<Field> Matrix;
NonHermitianSchurRedBlackDiagMooeeSolve(OperatorFunction<Field>& RBSolver, const bool initSubGuess = false,
const bool _solnAsInitGuess = false)
: SchurRedBlackBase<Field>(RBSolver, initSubGuess, _solnAsInitGuess) {};
//////////////////////////////////////////////////////
// Override RedBlack specialisation
//////////////////////////////////////////////////////
virtual void RedBlackSource(Matrix& _Matrix, const Field& src, Field& src_e, Field& src_o)
{
GridBase* grid = _Matrix.RedBlackGrid();
GridBase* fgrid = _Matrix.Grid();
Field tmp(grid);
Field Mtmp(grid);
pickCheckerboard(Even, src_e, src);
pickCheckerboard(Odd , src_o, src);
/////////////////////////////////////////////////////
// src_o = Mdag * (source_o - Moe MeeInv source_e)
/////////////////////////////////////////////////////
_Matrix.MooeeInv(src_e, tmp); assert( tmp.Checkerboard() == Even );
_Matrix.Meooe (tmp, Mtmp); assert( Mtmp.Checkerboard() == Odd );
src_o -= Mtmp; assert( src_o.Checkerboard() == Odd );
}
virtual void RedBlackSolution(Matrix& _Matrix, const Field& sol_o, const Field& src_e, Field& sol)
{
GridBase* grid = _Matrix.RedBlackGrid();
GridBase* fgrid = _Matrix.Grid();
Field tmp(grid);
Field sol_e(grid);
Field src_e_i(grid);
///////////////////////////////////////////////////
// sol_e = M_ee^-1 * ( src_e - Meo sol_o )...
///////////////////////////////////////////////////
_Matrix.Meooe(sol_o, tmp); assert( tmp.Checkerboard() == Even );
src_e_i = src_e - tmp; assert( src_e_i.Checkerboard() == Even );
_Matrix.MooeeInv(src_e_i, sol_e); assert( sol_e.Checkerboard() == Even );
setCheckerboard(sol, sol_e); assert( sol_e.Checkerboard() == Even );
setCheckerboard(sol, sol_o); assert( sol_o.Checkerboard() == Odd );
}
virtual void RedBlackSolve(Matrix& _Matrix, const Field& src_o, Field& sol_o)
{
NonHermitianSchurDiagMooeeOperator<Matrix,Field> _OpEO(_Matrix);
this->_HermitianRBSolver(_OpEO, src_o, sol_o); assert(sol_o.Checkerboard() == Odd);
}
virtual void RedBlackSolve(Matrix& _Matrix, const std::vector<Field>& src_o, std::vector<Field>& sol_o)
{
NonHermitianSchurDiagMooeeOperator<Matrix,Field> _OpEO(_Matrix);
this->_HermitianRBSolver(_OpEO, src_o, sol_o);
}
};
///////////////////////////////////////////////////////////////////////////////////////////////////////
// Site diagonal is identity, left preconditioned by Mee^inv
// ( 1 - Mee^inv Meo Moo^inv Moe ) phi = Mee_inv ( Mee - Meo Moo^inv Moe Mee^inv ) phi = Mee_inv eta
//
// Solve:
// ( 1 - Mee^inv Meo Moo^inv Moe )^dag ( 1 - Mee^inv Meo Moo^inv Moe ) phi = ( 1 - Mee^inv Meo Moo^inv Moe )^dag Mee_inv eta
//
// Old notation e<->o
//
// Left precon by Moo^-1
// b) (Doo^{dag} M_oo^-dag) (Moo^-1 Doo) psi_o = [ (D_oo)^dag M_oo^-dag ] Moo^-1 L^{-1} eta_o
// eta_o' = (D_oo)^dag M_oo^-dag Moo^-1 (eta_o - Moe Mee^{-1} eta_e)
///////////////////////////////////////////////////////////////////////////////////////////////////////
template<class Field> class SchurRedBlackDiagOneSolve : public SchurRedBlackBase<Field> {
public:
typedef CheckerBoardedSparseMatrixBase<Field> Matrix;
/////////////////////////////////////////////////////
// Wrap the usual normal equations Schur trick
/////////////////////////////////////////////////////
SchurRedBlackDiagOneSolve(OperatorFunction<Field> &HermitianRBSolver, const bool initSubGuess = false,
const bool _solnAsInitGuess = false)
: SchurRedBlackBase<Field>(HermitianRBSolver,initSubGuess,_solnAsInitGuess) {};
virtual void RedBlackSource(Matrix & _Matrix,const Field &src, Field &src_e,Field &src_o)
{
GridBase *grid = _Matrix.RedBlackGrid();
GridBase *fgrid= _Matrix.Grid();
SchurDiagOneOperator<Matrix,Field> _HermOpEO(_Matrix);
Field tmp(grid);
Field Mtmp(grid);
pickCheckerboard(Even,src_e,src);
pickCheckerboard(Odd ,src_o,src);
/////////////////////////////////////////////////////
// src_o = Mpcdag *MooeeInv * (source_o - Moe MeeInv source_e)
/////////////////////////////////////////////////////
_Matrix.MooeeInv(src_e,tmp); assert( tmp.Checkerboard() ==Even);
_Matrix.Meooe (tmp,Mtmp); assert( Mtmp.Checkerboard() ==Odd);
Mtmp=src_o-Mtmp;
_Matrix.MooeeInv(Mtmp,tmp); assert( tmp.Checkerboard() ==Odd);
// get the right MpcDag
_HermOpEO.MpcDag(tmp,src_o); assert(src_o.Checkerboard() ==Odd);
}
virtual void RedBlackSolution(Matrix & _Matrix,const Field &sol_o, const Field &src_e,Field &sol)
{
GridBase *grid = _Matrix.RedBlackGrid();
GridBase *fgrid= _Matrix.Grid();
Field tmp(grid);
Field sol_e(grid);
///////////////////////////////////////////////////
// sol_e = M_ee^-1 * ( src_e - Meo sol_o )...
///////////////////////////////////////////////////
_Matrix.Meooe(sol_o,tmp); assert( tmp.Checkerboard() ==Even);
tmp = src_e-tmp; assert( src_e.Checkerboard() ==Even);
_Matrix.MooeeInv(tmp,sol_e); assert( sol_e.Checkerboard() ==Even);
setCheckerboard(sol,sol_e); assert( sol_e.Checkerboard() ==Even);
setCheckerboard(sol,sol_o); assert( sol_o.Checkerboard() ==Odd );
};
virtual void RedBlackSolve (Matrix & _Matrix,const Field &src_o, Field &sol_o)
{
SchurDiagOneOperator<Matrix,Field> _HermOpEO(_Matrix);
this->_HermitianRBSolver(_HermOpEO,src_o,sol_o);
};
virtual void RedBlackSolve (Matrix & _Matrix,const std::vector<Field> &src_o, std::vector<Field> &sol_o)
{
SchurDiagOneOperator<Matrix,Field> _HermOpEO(_Matrix);
this->_HermitianRBSolver(_HermOpEO,src_o,sol_o);
}
};
///////////////////////////////////////////////////////////////////////////////////////////////////////
// Site diagonal is identity, right preconditioned by Mee^inv
// ( 1 - Meo Moo^inv Moe Mee^inv ) phi =( 1 - Meo Moo^inv Moe Mee^inv ) Mee psi = = eta = eta
//=> psi = MeeInv phi
///////////////////////////////////////////////////////////////////////////////////////////////////////
template<class Field> class SchurRedBlackDiagTwoSolve : public SchurRedBlackBase<Field> {
public:
typedef CheckerBoardedSparseMatrixBase<Field> Matrix;
/////////////////////////////////////////////////////
// Wrap the usual normal equations Schur trick
/////////////////////////////////////////////////////
SchurRedBlackDiagTwoSolve(OperatorFunction<Field> &HermitianRBSolver, const bool initSubGuess = false,
const bool _solnAsInitGuess = false)
: SchurRedBlackBase<Field>(HermitianRBSolver,initSubGuess,_solnAsInitGuess) {};
virtual void RedBlackSource(Matrix & _Matrix,const Field &src, Field &src_e,Field &src_o)
{
GridBase *grid = _Matrix.RedBlackGrid();
GridBase *fgrid= _Matrix.Grid();
SchurDiagTwoOperator<Matrix,Field> _HermOpEO(_Matrix);
Field tmp(grid);
Field Mtmp(grid);
pickCheckerboard(Even,src_e,src);
pickCheckerboard(Odd ,src_o,src);
/////////////////////////////////////////////////////
// src_o = Mdag * (source_o - Moe MeeInv source_e)
/////////////////////////////////////////////////////
_Matrix.MooeeInv(src_e,tmp); assert( tmp.Checkerboard() ==Even);
_Matrix.Meooe (tmp,Mtmp); assert( Mtmp.Checkerboard() ==Odd);
tmp=src_o-Mtmp; assert( tmp.Checkerboard() ==Odd);
// get the right MpcDag
_HermOpEO.MpcDag(tmp,src_o); assert(src_o.Checkerboard() ==Odd);
}
virtual void RedBlackSolution(Matrix & _Matrix,const Field &sol_o, const Field &src_e,Field &sol)
{
GridBase *grid = _Matrix.RedBlackGrid();
GridBase *fgrid= _Matrix.Grid();
Field sol_o_i(grid);
Field tmp(grid);
Field sol_e(grid);
////////////////////////////////////////////////
// MooeeInv due to pecond
////////////////////////////////////////////////
_Matrix.MooeeInv(sol_o,tmp);
sol_o_i = tmp;
///////////////////////////////////////////////////
// sol_e = M_ee^-1 * ( src_e - Meo sol_o )...
///////////////////////////////////////////////////
_Matrix.Meooe(sol_o_i,tmp); assert( tmp.Checkerboard() ==Even);
tmp = src_e-tmp; assert( src_e.Checkerboard() ==Even);
_Matrix.MooeeInv(tmp,sol_e); assert( sol_e.Checkerboard() ==Even);
setCheckerboard(sol,sol_e); assert( sol_e.Checkerboard() ==Even);
setCheckerboard(sol,sol_o_i); assert( sol_o_i.Checkerboard() ==Odd );
};
virtual void RedBlackSolve (Matrix & _Matrix,const Field &src_o, Field &sol_o)
{
SchurDiagTwoOperator<Matrix,Field> _HermOpEO(_Matrix);
this->_HermitianRBSolver(_HermOpEO,src_o,sol_o);
};
virtual void RedBlackSolve (Matrix & _Matrix,const std::vector<Field> &src_o, std::vector<Field> &sol_o)
{
SchurDiagTwoOperator<Matrix,Field> _HermOpEO(_Matrix);
this->_HermitianRBSolver(_HermOpEO,src_o,sol_o);
}
};
template<class Field> class NonHermitianSchurRedBlackDiagTwoSolve : public SchurRedBlackBase<Field>
{
public:
typedef CheckerBoardedSparseMatrixBase<Field> Matrix;
/////////////////////////////////////////////////////
// Wrap the usual normal equations Schur trick
/////////////////////////////////////////////////////
NonHermitianSchurRedBlackDiagTwoSolve(OperatorFunction<Field>& RBSolver, const bool initSubGuess = false,
const bool _solnAsInitGuess = false)
: SchurRedBlackBase<Field>(RBSolver, initSubGuess, _solnAsInitGuess) {};
virtual void RedBlackSource(Matrix& _Matrix, const Field& src, Field& src_e, Field& src_o)
{
GridBase* grid = _Matrix.RedBlackGrid();
GridBase* fgrid = _Matrix.Grid();
Field tmp(grid);
Field Mtmp(grid);
pickCheckerboard(Even, src_e, src);
pickCheckerboard(Odd , src_o, src);
/////////////////////////////////////////////////////
// src_o = Mdag * (source_o - Moe MeeInv source_e)
/////////////////////////////////////////////////////
_Matrix.MooeeInv(src_e, tmp); assert( tmp.Checkerboard() == Even );
_Matrix.Meooe (tmp, Mtmp); assert( Mtmp.Checkerboard() == Odd );
src_o -= Mtmp; assert( src_o.Checkerboard() == Odd );
}
virtual void RedBlackSolution(Matrix& _Matrix, const Field& sol_o, const Field& src_e, Field& sol)
{
GridBase* grid = _Matrix.RedBlackGrid();
GridBase* fgrid = _Matrix.Grid();
Field sol_o_i(grid);
Field tmp(grid);
Field sol_e(grid);
////////////////////////////////////////////////
// MooeeInv due to pecond
////////////////////////////////////////////////
_Matrix.MooeeInv(sol_o, tmp);
sol_o_i = tmp;
///////////////////////////////////////////////////
// sol_e = M_ee^-1 * ( src_e - Meo sol_o )...
///////////////////////////////////////////////////
_Matrix.Meooe(sol_o_i, tmp); assert( tmp.Checkerboard() == Even );
tmp = src_e - tmp; assert( src_e.Checkerboard() == Even );
_Matrix.MooeeInv(tmp, sol_e); assert( sol_e.Checkerboard() == Even );
setCheckerboard(sol, sol_e); assert( sol_e.Checkerboard() == Even );
setCheckerboard(sol, sol_o_i); assert( sol_o_i.Checkerboard() == Odd );
};
virtual void RedBlackSolve(Matrix& _Matrix, const Field& src_o, Field& sol_o)
{
NonHermitianSchurDiagTwoOperator<Matrix,Field> _OpEO(_Matrix);
this->_HermitianRBSolver(_OpEO, src_o, sol_o);
};
virtual void RedBlackSolve(Matrix& _Matrix, const std::vector<Field>& src_o, std::vector<Field>& sol_o)
{
NonHermitianSchurDiagTwoOperator<Matrix,Field> _OpEO(_Matrix);
this->_HermitianRBSolver(_OpEO, src_o, sol_o);
}
};
}
#endif
-542
View File
@@ -1,542 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/Aggregates.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: Peter Boyle <peterboyle@Peters-MacBook-Pro-2.local>
Author: paboyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
inline RealD AggregatePowerLaw(RealD x)
{
// return std::pow(x,-4);
// return std::pow(x,-3);
return std::pow(x,-5);
}
template<class Fobj,class CComplex,int nbasis>
class Aggregation {
public:
constexpr int Nbasis(void) { return nbasis; };
typedef iVector<CComplex,nbasis > siteVector;
typedef Lattice<siteVector> CoarseVector;
typedef Lattice<iMatrix<CComplex,nbasis > > CoarseMatrix;
typedef Lattice< CComplex > CoarseScalar; // used for inner products on fine field
typedef Lattice<Fobj > FineField;
GridBase *CoarseGrid;
GridBase *FineGrid;
std::vector<Lattice<Fobj> > subspace;
int checkerboard;
int Checkerboard(void){return checkerboard;}
Aggregation(GridBase *_CoarseGrid,GridBase *_FineGrid,int _checkerboard) :
CoarseGrid(_CoarseGrid),
FineGrid(_FineGrid),
subspace(nbasis,_FineGrid),
checkerboard(_checkerboard)
{
};
void Orthogonalise(void){
CoarseScalar InnerProd(CoarseGrid);
// std::cout << GridLogMessage <<" Block Gramm-Schmidt pass 1"<<std::endl;
blockOrthogonalise(InnerProd,subspace);
}
void ProjectToSubspace(CoarseVector &CoarseVec,const FineField &FineVec){
blockProject(CoarseVec,FineVec,subspace);
}
void PromoteFromSubspace(const CoarseVector &CoarseVec,FineField &FineVec){
FineVec.Checkerboard() = subspace[0].Checkerboard();
blockPromote(CoarseVec,FineVec,subspace);
}
virtual void CreateSubspaceRandom(GridParallelRNG &RNG) {
int nn=nbasis;
RealD scale;
FineField noise(FineGrid);
for(int b=0;b<nn;b++){
subspace[b] = Zero();
gaussian(RNG,noise);
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
subspace[b] = noise;
}
}
virtual void CreateSubspace(GridParallelRNG &RNG,LinearOperatorBase<FineField> &hermop,int nn=nbasis)
{
RealD scale;
ConjugateGradient<FineField> CG(1.0e-2,100,false);
FineField noise(FineGrid);
FineField Mn(FineGrid);
for(int b=0;b<nn;b++){
subspace[b] = Zero();
gaussian(RNG,noise);
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
hermop.Op(noise,Mn); std::cout<<GridLogMessage << "noise ["<<b<<"] <n|MdagM|n> "<<norm2(Mn)<<std::endl;
for(int i=0;i<1;i++){
CG(hermop,noise,subspace[b]);
noise = subspace[b];
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
}
hermop.Op(noise,Mn); std::cout<<GridLogMessage << "filtered["<<b<<"] <f|MdagM|f> "<<norm2(Mn)<<std::endl;
subspace[b] = noise;
}
}
////////////////////////////////////////////////////////////////////////////////////////////////
// World of possibilities here. But have tried quite a lot of experiments (250+ jobs run on Summit)
// and this is the best I found
////////////////////////////////////////////////////////////////////////////////////////////////
virtual void CreateSubspaceChebyshev(GridParallelRNG &RNG,LinearOperatorBase<FineField> &hermop,
int nn,
double hi,
double lo,
int orderfilter,
int ordermin,
int orderstep,
double filterlo
) {
RealD scale;
FineField noise(FineGrid);
FineField Mn(FineGrid);
FineField tmp(FineGrid);
// New normalised noise
gaussian(RNG,noise);
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
std::cout << GridLogMessage<<" Chebyshev subspace pass-1 : ord "<<orderfilter<<" ["<<lo<<","<<hi<<"]"<<std::endl;
std::cout << GridLogMessage<<" Chebyshev subspace pass-2 : nbasis"<<nn<<" min "
<<ordermin<<" step "<<orderstep
<<" lo"<<filterlo<<std::endl;
// Initial matrix element
hermop.Op(noise,Mn); std::cout<<GridLogMessage << "noise <n|MdagM|n> "<<norm2(Mn)<<std::endl;
int b =0;
{
// Filter
Chebyshev<FineField> Cheb(lo,hi,orderfilter);
Cheb(hermop,noise,Mn);
// normalise
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale;
subspace[b] = Mn;
hermop.Op(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
b++;
}
// Generate a full sequence of Chebyshevs
{
lo=filterlo;
noise=Mn;
FineField T0(FineGrid); T0 = noise;
FineField T1(FineGrid);
FineField T2(FineGrid);
FineField y(FineGrid);
FineField *Tnm = &T0;
FineField *Tn = &T1;
FineField *Tnp = &T2;
// Tn=T1 = (xscale M + mscale)in
RealD xscale = 2.0/(hi-lo);
RealD mscale = -(hi+lo)/(hi-lo);
hermop.HermOp(T0,y);
T1=y*xscale+noise*mscale;
for(int n=2;n<=ordermin+orderstep*(nn-2);n++){
hermop.HermOp(*Tn,y);
autoView( y_v , y, AcceleratorWrite);
autoView( Tn_v , (*Tn), AcceleratorWrite);
autoView( Tnp_v , (*Tnp), AcceleratorWrite);
autoView( Tnm_v , (*Tnm), AcceleratorWrite);
const int Nsimd = CComplex::Nsimd();
accelerator_for(ss, FineGrid->oSites(), Nsimd, {
coalescedWrite(y_v[ss],xscale*y_v(ss)+mscale*Tn_v(ss));
coalescedWrite(Tnp_v[ss],2.0*y_v(ss)-Tnm_v(ss));
});
// Possible more fine grained control is needed than a linear sweep,
// but huge productivity gain if this is simple algorithm and not a tunable
int m =1;
if ( n>=ordermin ) m=n-ordermin;
if ( (m%orderstep)==0 ) {
Mn=*Tnp;
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale;
subspace[b] = Mn;
hermop.Op(Mn,tmp);
std::cout<<GridLogMessage << n<<" filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
b++;
}
// Cycle pointers to avoid copies
FineField *swizzle = Tnm;
Tnm =Tn;
Tn =Tnp;
Tnp =swizzle;
}
}
assert(b==nn);
}
virtual void CreateSubspacePolyCheby(GridParallelRNG &RNG,LinearOperatorBase<FineField> &hermop,
int nn,
double hi,
double lo1,
int orderfilter,
double lo2,
int orderstep)
{
RealD scale;
FineField noise(FineGrid);
FineField Mn(FineGrid);
FineField tmp(FineGrid);
// New normalised noise
gaussian(RNG,noise);
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
std::cout << GridLogMessage<<" CreateSubspacePolyCheby "<<std::endl;
// Initial matrix element
hermop.Op(noise,Mn);
std::cout<<GridLogMessage << "noise <n|MdagM|n> "<<norm2(Mn)<<std::endl;
int b =0;
{
// Filter
std::cout << GridLogMessage << "Cheby "<<lo1<<","<<hi<<" "<<orderstep<<std::endl;
Chebyshev<FineField> Cheb(lo1,hi,orderfilter);
Cheb(hermop,noise,Mn);
// normalise
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale;
subspace[b] = Mn;
hermop.Op(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|n> "<<norm2(Mn)<<std::endl;
}
// Generate a full sequence of Chebyshevs
for(int n=1;n<nn;n++){
std::cout << GridLogMessage << "Cheby "<<lo2<<","<<hi<<" "<<orderstep<<std::endl;
Chebyshev<FineField> Cheb(lo2,hi,orderstep);
Cheb(hermop,subspace[n-1],Mn);
for(int m=0;m<n;m++){
ComplexD c = innerProduct(subspace[m],Mn);
Mn = Mn - c*subspace[m];
}
// normalise
scale = std::pow(norm2(Mn),-0.5);
Mn=Mn*scale;
subspace[n]=Mn;
hermop.Op(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<n<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
std::cout<<GridLogMessage << "filt ["<<n<<"] <n|n> "<<norm2(Mn)<<std::endl;
}
}
virtual void CreateSubspaceChebyshev(GridParallelRNG &RNG,LinearOperatorBase<FineField> &hermop,
int nn,
double hi,
double lo,
int orderfilter
) {
RealD scale;
FineField noise(FineGrid);
FineField Mn(FineGrid);
FineField tmp(FineGrid);
// New normalised noise
std::cout << GridLogMessage<<" Chebyshev subspace pure noise : ord "<<orderfilter<<" ["<<lo<<","<<hi<<"]"<<std::endl;
std::cout << GridLogMessage<<" Chebyshev subspace pure noise : nbasis "<<nn<<std::endl;
for(int b =0;b<nbasis;b++)
{
gaussian(RNG,noise);
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
// Initial matrix element
hermop.Op(noise,Mn);
if(b==0) std::cout<<GridLogMessage << "noise <n|MdagM|n> "<<norm2(Mn)<<std::endl;
// Filter
Chebyshev<FineField> Cheb(lo,hi,orderfilter);
Cheb(hermop,noise,Mn);
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale;
// Refine
Chebyshev<FineField> PowerLaw(lo,hi,1000,AggregatePowerLaw);
noise = Mn;
PowerLaw(hermop,noise,Mn);
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale;
// normalise
subspace[b] = Mn;
hermop.Op(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
}
}
virtual void CreateSubspaceChebyshevPowerLaw(GridParallelRNG &RNG,LinearOperatorBase<FineField> &hermop,
int nn,
double hi,
int orderfilter
) {
RealD scale;
FineField noise(FineGrid);
FineField Mn(FineGrid);
FineField tmp(FineGrid);
// New normalised noise
std::cout << GridLogMessage<<" Chebyshev subspace pure noise : ord "<<orderfilter<<" [0,"<<hi<<"]"<<std::endl;
std::cout << GridLogMessage<<" Chebyshev subspace pure noise : nbasis "<<nn<<std::endl;
for(int b =0;b<nbasis;b++)
{
gaussian(RNG,noise);
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
// Initial matrix element
hermop.Op(noise,Mn);
if(b==0) std::cout<<GridLogMessage << "noise <n|MdagM|n> "<<norm2(Mn)<<std::endl;
// Filter
Chebyshev<FineField> Cheb(0.0,hi,orderfilter,AggregatePowerLaw);
Cheb(hermop,noise,Mn);
// normalise
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale;
subspace[b] = Mn;
hermop.Op(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
}
}
virtual void CreateSubspaceChebyshevNew(GridParallelRNG &RNG,LinearOperatorBase<FineField> &hermop,
double hi
) {
RealD scale;
FineField noise(FineGrid);
FineField Mn(FineGrid);
FineField tmp(FineGrid);
// New normalised noise
for(int b =0;b<nbasis;b++)
{
gaussian(RNG,noise);
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
// Initial matrix element
hermop.Op(noise,Mn);
if(b==0) std::cout<<GridLogMessage << "noise <n|MdagM|n> "<<norm2(Mn)<<std::endl;
// Filter
//#opt2(x) = acheb(x,3,90,300)* acheb(x,1,90,50) * acheb(x,0.5,90,200) * acheb(x,0.05,90,400) * acheb(x,0.01,90,1500)
/*266
Chebyshev<FineField> Cheb1(3.0,hi,300);
Chebyshev<FineField> Cheb2(1.0,hi,50);
Chebyshev<FineField> Cheb3(0.5,hi,300);
Chebyshev<FineField> Cheb4(0.05,hi,500);
Chebyshev<FineField> Cheb5(0.01,hi,2000);
*/
/* 242 */
/*
Chebyshev<FineField> Cheb3(0.1,hi,300);
Chebyshev<FineField> Cheb2(0.02,hi,1000);
Chebyshev<FineField> Cheb1(0.003,hi,2000);
8?
*/
/* How many??
*/
Chebyshev<FineField> Cheb2(0.001,hi,2500); // 169 iters on HDCG after refine
Chebyshev<FineField> Cheb1(0.02,hi,600);
// Chebyshev<FineField> Cheb2(0.001,hi,1500);
// Chebyshev<FineField> Cheb1(0.02,hi,600);
Cheb1(hermop,noise,Mn); scale = std::pow(norm2(Mn),-0.5); noise=Mn*scale;
hermop.Op(noise,tmp); std::cout<<GridLogMessage << "Cheb1 <n|MdagM|n> "<<norm2(tmp)<<std::endl;
Cheb2(hermop,noise,Mn); scale = std::pow(norm2(Mn),-0.5); noise=Mn*scale;
hermop.Op(noise,tmp); std::cout<<GridLogMessage << "Cheb2 <n|MdagM|n> "<<norm2(tmp)<<std::endl;
// Cheb3(hermop,noise,Mn); scale = std::pow(norm2(Mn),-0.5); noise=Mn*scale;
// hermop.Op(noise,tmp); std::cout<<GridLogMessage << "Cheb3 <n|MdagM|n> "<<norm2(tmp)<<std::endl;
// Cheb4(hermop,noise,Mn); scale = std::pow(norm2(Mn),-0.5); noise=Mn*scale;
// hermop.Op(noise,tmp); std::cout<<GridLogMessage << "Cheb4 <n|MdagM|n> "<<norm2(tmp)<<std::endl;
// Cheb5(hermop,noise,Mn); scale = std::pow(norm2(Mn),-0.5); noise=Mn*scale;
// hermop.Op(noise,tmp); std::cout<<GridLogMessage << "Cheb5 <n|MdagM|n> "<<norm2(tmp)<<std::endl;
subspace[b] = noise;
hermop.Op(subspace[b],tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<< " norm " << norm2(noise)<<std::endl;
}
}
virtual void CreateSubspaceMultishift(GridParallelRNG &RNG,LinearOperatorBase<FineField> &hermop,
double Lo,double tol,int maxit)
{
RealD scale;
FineField noise(FineGrid);
FineField Mn(FineGrid);
FineField tmp(FineGrid);
// New normalised noise
std::cout << GridLogMessage<<" Multishift subspace : Lo "<<Lo<<std::endl;
// Filter
// [ 1/6(x+Lo) - 1/2(x+2Lo) + 1/2(x+3Lo) -1/6(x+4Lo) = Lo^3 /[ (x+1Lo)(x+2Lo)(x+3Lo)(x+4Lo) ]
//
// 1/(x+Lo) - 1/(x+2 Lo)
double epsilon = Lo/3;
std::vector<RealD> alpha({1.0/6.0,-1.0/2.0,1.0/2.0,-1.0/6.0});
std::vector<RealD> shifts({Lo,Lo+epsilon,Lo+2*epsilon,Lo+3*epsilon});
std::vector<RealD> tols({tol,tol,tol,tol});
std::cout << "sizes "<<alpha.size()<<" "<<shifts.size()<<" "<<tols.size()<<std::endl;
MultiShiftFunction msf(4,0.0,95.0);
std::cout << "msf constructed "<<std::endl;
msf.poles=shifts;
msf.residues=alpha;
msf.tolerances=tols;
msf.norm=0.0;
msf.order=alpha.size();
ConjugateGradientMultiShift<FineField> MSCG(maxit,msf);
for(int b =0;b<nbasis;b++)
{
gaussian(RNG,noise);
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
// Initial matrix element
hermop.Op(noise,Mn);
if(b==0) std::cout<<GridLogMessage << "noise <n|MdagM|n> "<<norm2(Mn)<<std::endl;
MSCG(hermop,noise,Mn);
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale;
subspace[b] = Mn;
hermop.Op(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
}
}
virtual void RefineSubspace(LinearOperatorBase<FineField> &hermop,
double Lo,double tol,int maxit)
{
FineField tmp(FineGrid);
for(int b =0;b<nbasis;b++)
{
ConjugateGradient<FineField> CGsloppy(tol,maxit,false);
ShiftedHermOpLinearOperator<FineField> ShiftedFineHermOp(hermop,Lo);
tmp=Zero();
CGsloppy(hermop,subspace[b],tmp);
RealD scale = std::pow(norm2(tmp),-0.5); tmp=tmp*scale;
subspace[b]=tmp;
hermop.Op(subspace[b],tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
}
}
virtual void RefineSubspaceHDCG(LinearOperatorBase<FineField> &hermop,
TwoLevelADEF2mrhs<FineField,CoarseVector> & theHDCG,
int nrhs)
{
std::vector<FineField> src_mrhs(nrhs,FineGrid);
std::vector<FineField> res_mrhs(nrhs,FineGrid);
FineField tmp(FineGrid);
for(int b =0;b<nbasis;b+=nrhs)
{
tmp = subspace[b];
RealD scale = std::pow(norm2(tmp),-0.5); tmp=tmp*scale;
subspace[b] =tmp;
hermop.Op(subspace[b],tmp);
std::cout<<GridLogMessage << "before filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
for(int r=0;r<MIN(nbasis-b,nrhs);r++){
src_mrhs[r] = subspace[b+r];
}
for(int r=0;r<nrhs;r++){
res_mrhs[r] = Zero();
}
theHDCG(src_mrhs,res_mrhs);
for(int r=0;r<MIN(nbasis-b,nrhs);r++){
tmp = res_mrhs[r];
RealD scale = std::pow(norm2(tmp),-0.5); tmp=tmp*scale;
subspace[b+r]=tmp;
}
hermop.Op(subspace[b],tmp);
std::cout<<GridLogMessage << "after filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
}
}
};
NAMESPACE_END(Grid);
-814
View File
@@ -1,814 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/CoarsenedMatrix.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: Peter Boyle <peterboyle@Peters-MacBook-Pro-2.local>
Author: paboyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_ALGORITHM_COARSENED_MATRIX_H
#define GRID_ALGORITHM_COARSENED_MATRIX_H
#include <Grid/qcd/QCD.h> // needed for Dagger(Yes|No), Inverse(Yes|No)
NAMESPACE_BEGIN(Grid);
template<class vobj,class CComplex>
inline void blockMaskedInnerProduct(Lattice<CComplex> &CoarseInner,
const Lattice<decltype(innerProduct(vobj(),vobj()))> &FineMask,
const Lattice<vobj> &fineX,
const Lattice<vobj> &fineY)
{
typedef decltype(innerProduct(vobj(),vobj())) dotp;
GridBase *coarse(CoarseInner.Grid());
GridBase *fine (fineX.Grid());
Lattice<dotp> fine_inner(fine); fine_inner.Checkerboard() = fineX.Checkerboard();
Lattice<dotp> fine_inner_msk(fine);
// Multiply could be fused with innerProduct
// Single block sum kernel could do both masks.
fine_inner = localInnerProduct(fineX,fineY);
mult(fine_inner_msk, fine_inner,FineMask);
blockSum(CoarseInner,fine_inner_msk);
}
// Fine Object == (per site) type of fine field
// nbasis == number of deflation vectors
template<class Fobj,class CComplex,int nbasis>
class CoarsenedMatrix : public CheckerBoardedSparseMatrixBase<Lattice<iVector<CComplex,nbasis > > > {
public:
typedef iVector<CComplex,nbasis > siteVector;
typedef Lattice<CComplex > CoarseComplexField;
typedef Lattice<siteVector> CoarseVector;
typedef Lattice<iMatrix<CComplex,nbasis > > CoarseMatrix;
typedef iMatrix<CComplex,nbasis > Cobj;
typedef Lattice< CComplex > CoarseScalar; // used for inner products on fine field
typedef Lattice<Fobj > FineField;
typedef CoarseVector FermionField;
// enrich interface, use default implementation as in FermionOperator ///////
void Dminus(CoarseVector const& in, CoarseVector& out) { out = in; }
void DminusDag(CoarseVector const& in, CoarseVector& out) { out = in; }
void ImportPhysicalFermionSource(CoarseVector const& input, CoarseVector& imported) { imported = input; }
void ImportUnphysicalFermion(CoarseVector const& input, CoarseVector& imported) { imported = input; }
void ExportPhysicalFermionSolution(CoarseVector const& solution, CoarseVector& exported) { exported = solution; };
void ExportPhysicalFermionSource(CoarseVector const& solution, CoarseVector& exported) { exported = solution; };
////////////////////
// Data members
////////////////////
Geometry geom;
GridBase * _grid;
GridBase* _cbgrid;
int hermitian;
CartesianStencil<siteVector,siteVector,DefaultImplParams> Stencil;
CartesianStencil<siteVector,siteVector,DefaultImplParams> StencilEven;
CartesianStencil<siteVector,siteVector,DefaultImplParams> StencilOdd;
std::vector<CoarseMatrix> A;
std::vector<CoarseMatrix> Aeven;
std::vector<CoarseMatrix> Aodd;
CoarseMatrix AselfInv;
CoarseMatrix AselfInvEven;
CoarseMatrix AselfInvOdd;
Vector<RealD> dag_factor;
///////////////////////
// Interface
///////////////////////
GridBase * Grid(void) { return _grid; }; // this is all the linalg routines need to know
GridBase * RedBlackGrid() { return _cbgrid; };
int ConstEE() { return 0; }
void M (const CoarseVector &in, CoarseVector &out)
{
conformable(_grid,in.Grid());
conformable(in.Grid(),out.Grid());
out.Checkerboard() = in.Checkerboard();
SimpleCompressor<siteVector> compressor;
Stencil.HaloExchange(in,compressor);
autoView( in_v , in, AcceleratorRead);
autoView( out_v , out, AcceleratorWrite);
autoView( Stencil_v , Stencil, AcceleratorRead);
int npoint = geom.npoint;
typedef LatticeView<Cobj> Aview;
Vector<Aview> AcceleratorViewContainer;
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer.push_back(A[p].View(AcceleratorRead));
Aview *Aview_p = & AcceleratorViewContainer[0];
const int Nsimd = CComplex::Nsimd();
typedef decltype(coalescedRead(in_v[0])) calcVector;
typedef decltype(coalescedRead(in_v[0](0))) calcComplex;
int osites=Grid()->oSites();
accelerator_for(sss, Grid()->oSites()*nbasis, Nsimd, {
int ss = sss/nbasis;
int b = sss%nbasis;
calcComplex res = Zero();
calcVector nbr;
int ptype;
StencilEntry *SE;
for(int point=0;point<npoint;point++){
SE=Stencil_v.GetEntry(ptype,point,ss);
if(SE->_is_local) {
nbr = coalescedReadPermute(in_v[SE->_offset],ptype,SE->_permute);
} else {
nbr = coalescedRead(Stencil_v.CommBuf()[SE->_offset]);
}
acceleratorSynchronise();
for(int bb=0;bb<nbasis;bb++) {
res = res + coalescedRead(Aview_p[point][ss](b,bb))*nbr(bb);
}
}
coalescedWrite(out_v[ss](b),res);
});
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer[p].ViewClose();
};
void Mdag (const CoarseVector &in, CoarseVector &out)
{
if(hermitian) {
// corresponds to Petrov-Galerkin coarsening
return M(in,out);
} else {
// corresponds to Galerkin coarsening
return MdagNonHermitian(in, out);
}
};
void MdagNonHermitian(const CoarseVector &in, CoarseVector &out)
{
conformable(_grid,in.Grid());
conformable(in.Grid(),out.Grid());
out.Checkerboard() = in.Checkerboard();
SimpleCompressor<siteVector> compressor;
Stencil.HaloExchange(in,compressor);
autoView( in_v , in, AcceleratorRead);
autoView( out_v , out, AcceleratorWrite);
autoView( Stencil_v , Stencil, AcceleratorRead);
int npoint = geom.npoint;
typedef LatticeView<Cobj> Aview;
Vector<Aview> AcceleratorViewContainer;
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer.push_back(A[p].View(AcceleratorRead));
Aview *Aview_p = & AcceleratorViewContainer[0];
const int Nsimd = CComplex::Nsimd();
typedef decltype(coalescedRead(in_v[0])) calcVector;
typedef decltype(coalescedRead(in_v[0](0))) calcComplex;
int osites=Grid()->oSites();
Vector<int> points(geom.npoint, 0);
for(int p=0; p<geom.npoint; p++)
points[p] = geom.points_dagger[p];
auto points_p = &points[0];
RealD* dag_factor_p = &dag_factor[0];
accelerator_for(sss, Grid()->oSites()*nbasis, Nsimd, {
int ss = sss/nbasis;
int b = sss%nbasis;
calcComplex res = Zero();
calcVector nbr;
int ptype;
StencilEntry *SE;
for(int p=0;p<npoint;p++){
int point = points_p[p];
SE=Stencil_v.GetEntry(ptype,point,ss);
if(SE->_is_local) {
nbr = coalescedReadPermute(in_v[SE->_offset],ptype,SE->_permute);
} else {
nbr = coalescedRead(Stencil_v.CommBuf()[SE->_offset]);
}
acceleratorSynchronise();
for(int bb=0;bb<nbasis;bb++) {
res = res + dag_factor_p[b*nbasis+bb]*coalescedRead(Aview_p[point][ss](b,bb))*nbr(bb);
}
}
coalescedWrite(out_v[ss](b),res);
});
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer[p].ViewClose();
}
void MdirComms(const CoarseVector &in)
{
SimpleCompressor<siteVector> compressor;
Stencil.HaloExchange(in,compressor);
}
void MdirCalc(const CoarseVector &in, CoarseVector &out, int point)
{
conformable(_grid,in.Grid());
conformable(_grid,out.Grid());
out.Checkerboard() = in.Checkerboard();
typedef LatticeView<Cobj> Aview;
Vector<Aview> AcceleratorViewContainer;
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer.push_back(A[p].View(AcceleratorRead));
Aview *Aview_p = & AcceleratorViewContainer[0];
autoView( out_v , out, AcceleratorWrite);
autoView( in_v , in, AcceleratorRead);
autoView( Stencil_v , Stencil, AcceleratorRead);
const int Nsimd = CComplex::Nsimd();
typedef decltype(coalescedRead(in_v[0])) calcVector;
typedef decltype(coalescedRead(in_v[0](0))) calcComplex;
accelerator_for(sss, Grid()->oSites()*nbasis, Nsimd, {
int ss = sss/nbasis;
int b = sss%nbasis;
calcComplex res = Zero();
calcVector nbr;
int ptype;
StencilEntry *SE;
SE=Stencil_v.GetEntry(ptype,point,ss);
if(SE->_is_local) {
nbr = coalescedReadPermute(in_v[SE->_offset],ptype,SE->_permute);
} else {
nbr = coalescedRead(Stencil_v.CommBuf()[SE->_offset]);
}
acceleratorSynchronise();
for(int bb=0;bb<nbasis;bb++) {
res = res + coalescedRead(Aview_p[point][ss](b,bb))*nbr(bb);
}
coalescedWrite(out_v[ss](b),res);
});
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer[p].ViewClose();
}
void MdirAll(const CoarseVector &in,std::vector<CoarseVector> &out)
{
this->MdirComms(in);
int ndir=geom.npoint-1;
if ((out.size()!=ndir)&&(out.size()!=ndir+1)) {
std::cout <<"MdirAll out size "<< out.size()<<std::endl;
std::cout <<"MdirAll ndir "<< ndir<<std::endl;
assert(0);
}
for(int p=0;p<ndir;p++){
MdirCalc(in,out[p],p);
}
};
void Mdir(const CoarseVector &in, CoarseVector &out, int dir, int disp){
this->MdirComms(in);
MdirCalc(in,out,geom.point(dir,disp));
};
void Mdiag(const CoarseVector &in, CoarseVector &out)
{
int point=geom.npoint-1;
MdirCalc(in, out, point); // No comms
};
void Mooee(const CoarseVector &in, CoarseVector &out) {
MooeeInternal(in, out, DaggerNo, InverseNo);
}
void MooeeInv(const CoarseVector &in, CoarseVector &out) {
MooeeInternal(in, out, DaggerNo, InverseYes);
}
void MooeeDag(const CoarseVector &in, CoarseVector &out) {
MooeeInternal(in, out, DaggerYes, InverseNo);
}
void MooeeInvDag(const CoarseVector &in, CoarseVector &out) {
MooeeInternal(in, out, DaggerYes, InverseYes);
}
void Meooe(const CoarseVector &in, CoarseVector &out) {
if(in.Checkerboard() == Odd) {
DhopEO(in, out, DaggerNo);
} else {
DhopOE(in, out, DaggerNo);
}
}
void MeooeDag(const CoarseVector &in, CoarseVector &out) {
if(in.Checkerboard() == Odd) {
DhopEO(in, out, DaggerYes);
} else {
DhopOE(in, out, DaggerYes);
}
}
void Dhop(const CoarseVector &in, CoarseVector &out, int dag) {
conformable(in.Grid(), _grid); // verifies full grid
conformable(in.Grid(), out.Grid());
out.Checkerboard() = in.Checkerboard();
DhopInternal(Stencil, A, in, out, dag);
}
void DhopOE(const CoarseVector &in, CoarseVector &out, int dag) {
conformable(in.Grid(), _cbgrid); // verifies half grid
conformable(in.Grid(), out.Grid()); // drops the cb check
assert(in.Checkerboard() == Even);
out.Checkerboard() = Odd;
DhopInternal(StencilEven, Aodd, in, out, dag);
}
void DhopEO(const CoarseVector &in, CoarseVector &out, int dag) {
conformable(in.Grid(), _cbgrid); // verifies half grid
conformable(in.Grid(), out.Grid()); // drops the cb check
assert(in.Checkerboard() == Odd);
out.Checkerboard() = Even;
DhopInternal(StencilOdd, Aeven, in, out, dag);
}
void MooeeInternal(const CoarseVector &in, CoarseVector &out, int dag, int inv) {
out.Checkerboard() = in.Checkerboard();
assert(in.Checkerboard() == Odd || in.Checkerboard() == Even);
CoarseMatrix *Aself = nullptr;
if(in.Grid()->_isCheckerBoarded) {
if(in.Checkerboard() == Odd) {
Aself = (inv) ? &AselfInvOdd : &Aodd[geom.npoint-1];
DselfInternal(StencilOdd, *Aself, in, out, dag);
} else {
Aself = (inv) ? &AselfInvEven : &Aeven[geom.npoint-1];
DselfInternal(StencilEven, *Aself, in, out, dag);
}
} else {
Aself = (inv) ? &AselfInv : &A[geom.npoint-1];
DselfInternal(Stencil, *Aself, in, out, dag);
}
assert(Aself != nullptr);
}
void DselfInternal(CartesianStencil<siteVector,siteVector,DefaultImplParams> &st, CoarseMatrix &a,
const CoarseVector &in, CoarseVector &out, int dag) {
int point = geom.npoint-1;
autoView( out_v, out, AcceleratorWrite);
autoView( in_v, in, AcceleratorRead);
autoView( st_v, st, AcceleratorRead);
autoView( a_v, a, AcceleratorRead);
const int Nsimd = CComplex::Nsimd();
typedef decltype(coalescedRead(in_v[0])) calcVector;
typedef decltype(coalescedRead(in_v[0](0))) calcComplex;
RealD* dag_factor_p = &dag_factor[0];
if(dag) {
accelerator_for(sss, in.Grid()->oSites()*nbasis, Nsimd, {
int ss = sss/nbasis;
int b = sss%nbasis;
calcComplex res = Zero();
calcVector nbr;
int ptype;
StencilEntry *SE;
SE=st_v.GetEntry(ptype,point,ss);
if(SE->_is_local) {
nbr = coalescedReadPermute(in_v[SE->_offset],ptype,SE->_permute);
} else {
nbr = coalescedRead(st_v.CommBuf()[SE->_offset]);
}
acceleratorSynchronise();
for(int bb=0;bb<nbasis;bb++) {
res = res + dag_factor_p[b*nbasis+bb]*coalescedRead(a_v[ss](b,bb))*nbr(bb);
}
coalescedWrite(out_v[ss](b),res);
});
} else {
accelerator_for(sss, in.Grid()->oSites()*nbasis, Nsimd, {
int ss = sss/nbasis;
int b = sss%nbasis;
calcComplex res = Zero();
calcVector nbr;
int ptype;
StencilEntry *SE;
SE=st_v.GetEntry(ptype,point,ss);
if(SE->_is_local) {
nbr = coalescedReadPermute(in_v[SE->_offset],ptype,SE->_permute);
} else {
nbr = coalescedRead(st_v.CommBuf()[SE->_offset]);
}
acceleratorSynchronise();
for(int bb=0;bb<nbasis;bb++) {
res = res + coalescedRead(a_v[ss](b,bb))*nbr(bb);
}
coalescedWrite(out_v[ss](b),res);
});
}
}
void DhopInternal(CartesianStencil<siteVector,siteVector,DefaultImplParams> &st, std::vector<CoarseMatrix> &a,
const CoarseVector &in, CoarseVector &out, int dag) {
SimpleCompressor<siteVector> compressor;
st.HaloExchange(in,compressor);
autoView( in_v, in, AcceleratorRead);
autoView( out_v, out, AcceleratorWrite);
autoView( st_v , st, AcceleratorRead);
typedef LatticeView<Cobj> Aview;
// determine in what order we need the points
int npoint = geom.npoint-1;
Vector<int> points(npoint, 0);
for(int p=0; p<npoint; p++)
points[p] = (dag && !hermitian) ? geom.points_dagger[p] : p;
auto points_p = &points[0];
Vector<Aview> AcceleratorViewContainer;
for(int p=0;p<npoint;p++) AcceleratorViewContainer.push_back(a[p].View(AcceleratorRead));
Aview *Aview_p = & AcceleratorViewContainer[0];
const int Nsimd = CComplex::Nsimd();
typedef decltype(coalescedRead(in_v[0])) calcVector;
typedef decltype(coalescedRead(in_v[0](0))) calcComplex;
RealD* dag_factor_p = &dag_factor[0];
if(dag) {
accelerator_for(sss, in.Grid()->oSites()*nbasis, Nsimd, {
int ss = sss/nbasis;
int b = sss%nbasis;
calcComplex res = Zero();
calcVector nbr;
int ptype;
StencilEntry *SE;
for(int p=0;p<npoint;p++){
int point = points_p[p];
SE=st_v.GetEntry(ptype,point,ss);
if(SE->_is_local) {
nbr = coalescedReadPermute(in_v[SE->_offset],ptype,SE->_permute);
} else {
nbr = coalescedRead(st_v.CommBuf()[SE->_offset]);
}
acceleratorSynchronise();
for(int bb=0;bb<nbasis;bb++) {
res = res + dag_factor_p[b*nbasis+bb]*coalescedRead(Aview_p[point][ss](b,bb))*nbr(bb);
}
}
coalescedWrite(out_v[ss](b),res);
});
} else {
accelerator_for(sss, in.Grid()->oSites()*nbasis, Nsimd, {
int ss = sss/nbasis;
int b = sss%nbasis;
calcComplex res = Zero();
calcVector nbr;
int ptype;
StencilEntry *SE;
for(int p=0;p<npoint;p++){
int point = points_p[p];
SE=st_v.GetEntry(ptype,point,ss);
if(SE->_is_local) {
nbr = coalescedReadPermute(in_v[SE->_offset],ptype,SE->_permute);
} else {
nbr = coalescedRead(st_v.CommBuf()[SE->_offset]);
}
acceleratorSynchronise();
for(int bb=0;bb<nbasis;bb++) {
res = res + coalescedRead(Aview_p[point][ss](b,bb))*nbr(bb);
}
}
coalescedWrite(out_v[ss](b),res);
});
}
for(int p=0;p<npoint;p++) AcceleratorViewContainer[p].ViewClose();
}
CoarsenedMatrix(GridCartesian &CoarseGrid, int hermitian_=0) :
_grid(&CoarseGrid),
_cbgrid(new GridRedBlackCartesian(&CoarseGrid)),
geom(CoarseGrid._ndimension),
hermitian(hermitian_),
Stencil(&CoarseGrid,geom.npoint,Even,geom.directions,geom.displacements),
StencilEven(_cbgrid,geom.npoint,Even,geom.directions,geom.displacements),
StencilOdd(_cbgrid,geom.npoint,Odd,geom.directions,geom.displacements),
A(geom.npoint,&CoarseGrid),
Aeven(geom.npoint,_cbgrid),
Aodd(geom.npoint,_cbgrid),
AselfInv(&CoarseGrid),
AselfInvEven(_cbgrid),
AselfInvOdd(_cbgrid),
dag_factor(nbasis*nbasis)
{
fillFactor();
};
CoarsenedMatrix(GridCartesian &CoarseGrid, GridRedBlackCartesian &CoarseRBGrid, int hermitian_=0) :
_grid(&CoarseGrid),
_cbgrid(&CoarseRBGrid),
geom(CoarseGrid._ndimension),
hermitian(hermitian_),
Stencil(&CoarseGrid,geom.npoint,Even,geom.directions,geom.displacements),
StencilEven(&CoarseRBGrid,geom.npoint,Even,geom.directions,geom.displacements),
StencilOdd(&CoarseRBGrid,geom.npoint,Odd,geom.directions,geom.displacements),
A(geom.npoint,&CoarseGrid),
Aeven(geom.npoint,&CoarseRBGrid),
Aodd(geom.npoint,&CoarseRBGrid),
AselfInv(&CoarseGrid),
AselfInvEven(&CoarseRBGrid),
AselfInvOdd(&CoarseRBGrid),
dag_factor(nbasis*nbasis)
{
fillFactor();
};
void fillFactor() {
Eigen::MatrixXd dag_factor_eigen = Eigen::MatrixXd::Ones(nbasis, nbasis);
if(!hermitian) {
const int nb = nbasis/2;
dag_factor_eigen.block(0,nb,nb,nb) *= -1.0;
dag_factor_eigen.block(nb,0,nb,nb) *= -1.0;
}
// GPU readable prefactor
thread_for(i, nbasis*nbasis, {
int j = i/nbasis;
int k = i%nbasis;
dag_factor[i] = dag_factor_eigen(j, k);
});
}
void CoarsenOperator(GridBase *FineGrid,LinearOperatorBase<Lattice<Fobj> > &linop,
Aggregation<Fobj,CComplex,nbasis> & Subspace)
{
typedef Lattice<typename Fobj::tensor_reduced> FineComplexField;
typedef typename Fobj::scalar_type scalar_type;
std::cout << GridLogMessage<< "CoarsenMatrix "<< std::endl;
FineComplexField one(FineGrid); one=scalar_type(1.0,0.0);
FineComplexField zero(FineGrid); zero=scalar_type(0.0,0.0);
std::vector<FineComplexField> masks(geom.npoint,FineGrid);
FineComplexField imask(FineGrid); // contributions from within this block
FineComplexField omask(FineGrid); // contributions from outwith this block
FineComplexField evenmask(FineGrid);
FineComplexField oddmask(FineGrid);
FineField phi(FineGrid);
FineField tmp(FineGrid);
FineField zz(FineGrid); zz=Zero();
FineField Mphi(FineGrid);
FineField Mphie(FineGrid);
FineField Mphio(FineGrid);
std::vector<FineField> Mphi_p(geom.npoint,FineGrid);
Lattice<iScalar<vInteger> > coor (FineGrid);
Lattice<iScalar<vInteger> > bcoor(FineGrid);
Lattice<iScalar<vInteger> > bcb (FineGrid); bcb = Zero();
CoarseVector iProj(Grid());
CoarseVector oProj(Grid());
CoarseVector SelfProj(Grid());
CoarseComplexField iZProj(Grid());
CoarseComplexField oZProj(Grid());
CoarseScalar InnerProd(Grid());
std::cout << GridLogMessage<< "CoarsenMatrix Orthog "<< std::endl;
// Orthogonalise the subblocks over the basis
blockOrthogonalise(InnerProd,Subspace.subspace);
// Compute the matrix elements of linop between this orthonormal
// set of vectors.
std::cout << GridLogMessage<< "CoarsenMatrix masks "<< std::endl;
int self_stencil=-1;
for(int p=0;p<geom.npoint;p++)
{
int dir = geom.directions[p];
int disp = geom.displacements[p];
A[p]=Zero();
if( geom.displacements[p]==0){
self_stencil=p;
}
Integer block=(FineGrid->_rdimensions[dir])/(Grid()->_rdimensions[dir]);
LatticeCoordinate(coor,dir);
///////////////////////////////////////////////////////
// Work out even and odd block checkerboarding for fast diagonal term
///////////////////////////////////////////////////////
if ( disp==1 ) {
bcb = bcb + div(coor,block);
}
if ( disp==0 ) {
masks[p]= Zero();
} else if ( disp==1 ) {
masks[p] = where(mod(coor,block)==(block-1),one,zero);
} else if ( disp==-1 ) {
masks[p] = where(mod(coor,block)==(Integer)0,one,zero);
}
}
evenmask = where(mod(bcb,2)==(Integer)0,one,zero);
oddmask = one-evenmask;
assert(self_stencil!=-1);
for(int i=0;i<nbasis;i++){
phi=Subspace.subspace[i];
std::cout << GridLogMessage<< "CoarsenMatrix vector "<<i << std::endl;
linop.OpDirAll(phi,Mphi_p);
linop.OpDiag (phi,Mphi_p[geom.npoint-1]);
for(int p=0;p<geom.npoint;p++){
Mphi = Mphi_p[p];
int dir = geom.directions[p];
int disp = geom.displacements[p];
if ( (disp==-1) || (!hermitian ) ) {
////////////////////////////////////////////////////////////////////////
// Pick out contributions coming from this cell and neighbour cell
////////////////////////////////////////////////////////////////////////
omask = masks[p];
imask = one-omask;
for(int j=0;j<nbasis;j++){
blockMaskedInnerProduct(oZProj,omask,Subspace.subspace[j],Mphi);
autoView( iZProj_v , iZProj, AcceleratorRead) ;
autoView( oZProj_v , oZProj, AcceleratorRead) ;
autoView( A_p , A[p], AcceleratorWrite);
autoView( A_self , A[self_stencil], AcceleratorWrite);
accelerator_for(ss, Grid()->oSites(), Fobj::Nsimd(),{ coalescedWrite(A_p[ss](j,i),oZProj_v(ss)); });
if ( hermitian && (disp==-1) ) {
for(int pp=0;pp<geom.npoint;pp++){// Find the opposite link and set <j|A|i> = <i|A|j>*
int dirp = geom.directions[pp];
int dispp = geom.displacements[pp];
if ( (dirp==dir) && (dispp==1) ){
auto sft = conjugate(Cshift(oZProj,dir,1));
autoView( sft_v , sft , AcceleratorWrite);
autoView( A_pp , A[pp], AcceleratorWrite);
accelerator_for(ss, Grid()->oSites(), Fobj::Nsimd(),{ coalescedWrite(A_pp[ss](i,j),sft_v(ss)); });
}
}
}
}
}
}
///////////////////////////////////////////
// Faster alternate self coupling.. use hermiticity to save 2x
///////////////////////////////////////////
{
mult(tmp,phi,evenmask); linop.Op(tmp,Mphie);
mult(tmp,phi,oddmask ); linop.Op(tmp,Mphio);
{
autoView( tmp_ , tmp, AcceleratorWrite);
autoView( evenmask_ , evenmask, AcceleratorRead);
autoView( oddmask_ , oddmask, AcceleratorRead);
autoView( Mphie_ , Mphie, AcceleratorRead);
autoView( Mphio_ , Mphio, AcceleratorRead);
accelerator_for(ss, FineGrid->oSites(), Fobj::Nsimd(),{
coalescedWrite(tmp_[ss],evenmask_(ss)*Mphie_(ss) + oddmask_(ss)*Mphio_(ss));
});
}
blockProject(SelfProj,tmp,Subspace.subspace);
autoView( SelfProj_ , SelfProj, AcceleratorRead);
autoView( A_self , A[self_stencil], AcceleratorWrite);
accelerator_for(ss, Grid()->oSites(), Fobj::Nsimd(),{
for(int j=0;j<nbasis;j++){
coalescedWrite(A_self[ss](j,i), SelfProj_(ss)(j));
}
});
}
}
if(hermitian) {
std::cout << GridLogMessage << " ForceHermitian, new code "<<std::endl;
}
InvertSelfStencilLink(); std::cout << GridLogMessage << "Coarse self link inverted" << std::endl;
FillHalfCbs(); std::cout << GridLogMessage << "Coarse half checkerboards filled" << std::endl;
}
void InvertSelfStencilLink() {
std::cout << GridLogDebug << "CoarsenedMatrix::InvertSelfStencilLink" << std::endl;
int localVolume = Grid()->lSites();
typedef typename Cobj::scalar_object scalar_object;
autoView(Aself_v, A[geom.npoint-1], CpuRead);
autoView(AselfInv_v, AselfInv, CpuWrite);
thread_for(site, localVolume, { // NOTE: Not able to bring this to GPU because of Eigen + peek/poke
Eigen::MatrixXcd selfLinkEigen = Eigen::MatrixXcd::Zero(nbasis, nbasis);
Eigen::MatrixXcd selfLinkInvEigen = Eigen::MatrixXcd::Zero(nbasis, nbasis);
scalar_object selfLink = Zero();
scalar_object selfLinkInv = Zero();
Coordinate lcoor;
Grid()->LocalIndexToLocalCoor(site, lcoor);
peekLocalSite(selfLink, Aself_v, lcoor);
for (int i = 0; i < nbasis; ++i)
for (int j = 0; j < nbasis; ++j)
selfLinkEigen(i, j) = static_cast<ComplexD>(TensorRemove(selfLink(i, j)));
selfLinkInvEigen = selfLinkEigen.inverse();
for(int i = 0; i < nbasis; ++i)
for(int j = 0; j < nbasis; ++j)
selfLinkInv(i, j) = selfLinkInvEigen(i, j);
pokeLocalSite(selfLinkInv, AselfInv_v, lcoor);
});
}
void FillHalfCbs() {
std::cout << GridLogDebug << "CoarsenedMatrix::FillHalfCbs" << std::endl;
for(int p = 0; p < geom.npoint; ++p) {
pickCheckerboard(Even, Aeven[p], A[p]);
pickCheckerboard(Odd, Aodd[p], A[p]);
}
pickCheckerboard(Even, AselfInvEven, AselfInv);
pickCheckerboard(Odd, AselfInvOdd, AselfInv);
}
};
NAMESPACE_END(Grid);
#endif
@@ -1,619 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/GeneralCoarsenedMatrix.h
Copyright (C) 2015
Author: Peter Boyle <pboyle@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
#include <Grid/qcd/QCD.h> // needed for Dagger(Yes|No), Inverse(Yes|No)
#include <Grid/lattice/PaddedCell.h>
#include <Grid/stencil/GeneralLocalStencil.h>
NAMESPACE_BEGIN(Grid);
// Fine Object == (per site) type of fine field
// nbasis == number of deflation vectors
template<class Fobj,class CComplex,int nbasis>
class GeneralCoarsenedMatrix : public SparseMatrixBase<Lattice<iVector<CComplex,nbasis > > > {
public:
typedef GeneralCoarsenedMatrix<Fobj,CComplex,nbasis> GeneralCoarseOp;
typedef iVector<CComplex,nbasis > siteVector;
typedef iMatrix<CComplex,nbasis > siteMatrix;
typedef Lattice<iScalar<CComplex> > CoarseComplexField;
typedef Lattice<siteVector> CoarseVector;
typedef Lattice<iMatrix<CComplex,nbasis > > CoarseMatrix;
typedef iMatrix<CComplex,nbasis > Cobj;
typedef iVector<CComplex,nbasis > Cvec;
typedef Lattice< CComplex > CoarseScalar; // used for inner products on fine field
typedef Lattice<Fobj > FineField;
typedef Lattice<CComplex > FineComplexField;
typedef CoarseVector Field;
////////////////////
// Data members
////////////////////
int hermitian;
GridBase * _FineGrid;
GridCartesian * _CoarseGrid;
NonLocalStencilGeometry &geom;
PaddedCell Cell;
GeneralLocalStencil Stencil;
std::vector<CoarseMatrix> _A;
std::vector<CoarseMatrix> _Adag;
std::vector<CoarseVector> MultTemporaries;
///////////////////////
// Interface
///////////////////////
GridBase * Grid(void) { return _CoarseGrid; }; // this is all the linalg routines need to know
GridBase * FineGrid(void) { return _FineGrid; }; // this is all the linalg routines need to know
GridCartesian * CoarseGrid(void) { return _CoarseGrid; }; // this is all the linalg routines need to know
/* void ShiftMatrix(RealD shift)
{
int Nd=_FineGrid->Nd();
Coordinate zero_shift(Nd,0);
for(int p=0;p<geom.npoint;p++){
if ( zero_shift==geom.shifts[p] ) {
_A[p] = _A[p]+shift;
// _Adag[p] = _Adag[p]+shift;
}
}
}
void ProjectNearestNeighbour(RealD shift, GeneralCoarseOp &CopyMe)
{
int nfound=0;
std::cout << GridLogMessage <<"GeneralCoarsenedMatrix::ProjectNearestNeighbour "<< CopyMe._A[0].Grid()<<std::endl;
for(int p=0;p<geom.npoint;p++){
for(int pp=0;pp<CopyMe.geom.npoint;pp++){
// Search for the same relative shift
// Avoids brutal handling of Grid pointers
if ( CopyMe.geom.shifts[pp]==geom.shifts[p] ) {
_A[p] = CopyMe.Cell.Extract(CopyMe._A[pp]);
// _Adag[p] = CopyMe.Cell.Extract(CopyMe._Adag[pp]);
nfound++;
}
}
}
assert(nfound==geom.npoint);
ExchangeCoarseLinks();
}
*/
GeneralCoarsenedMatrix(NonLocalStencilGeometry &_geom,GridBase *FineGrid, GridCartesian * CoarseGrid)
: geom(_geom),
_FineGrid(FineGrid),
_CoarseGrid(CoarseGrid),
hermitian(1),
Cell(_geom.Depth(),_CoarseGrid),
Stencil(Cell.grids.back(),geom.shifts)
{
{
int npoint = _geom.npoint;
}
_A.resize(geom.npoint,CoarseGrid);
// _Adag.resize(geom.npoint,CoarseGrid);
}
void M (const CoarseVector &in, CoarseVector &out)
{
Mult(_A,in,out);
}
void Mdag (const CoarseVector &in, CoarseVector &out)
{
assert(hermitian);
Mult(_A,in,out);
// if ( hermitian ) M(in,out);
// else Mult(_Adag,in,out);
}
void Mult (std::vector<CoarseMatrix> &A,const CoarseVector &in, CoarseVector &out)
{
RealD tviews=0; RealD ttot=0; RealD tmult=0; RealD texch=0; RealD text=0; RealD ttemps=0; RealD tcopy=0;
RealD tmult2=0;
ttot=-usecond();
conformable(CoarseGrid(),in.Grid());
conformable(in.Grid(),out.Grid());
out.Checkerboard() = in.Checkerboard();
CoarseVector tin=in;
texch-=usecond();
CoarseVector pin = Cell.ExchangePeriodic(tin);
texch+=usecond();
CoarseVector pout(pin.Grid());
int npoint = geom.npoint;
typedef LatticeView<Cobj> Aview;
typedef LatticeView<Cvec> Vview;
const int Nsimd = CComplex::Nsimd();
int64_t osites=pin.Grid()->oSites();
RealD flops = 1.0* npoint * nbasis * nbasis * 8.0 * osites * CComplex::Nsimd();
RealD bytes = 1.0*osites*sizeof(siteMatrix)*npoint
+ 2.0*osites*sizeof(siteVector)*npoint;
{
tviews-=usecond();
autoView( in_v , pin, AcceleratorRead);
autoView( out_v , pout, AcceleratorWriteDiscard);
autoView( Stencil_v , Stencil, AcceleratorRead);
tviews+=usecond();
// Static and prereserve to keep UVM region live and not resized across multiple calls
ttemps-=usecond();
MultTemporaries.resize(npoint,pin.Grid());
ttemps+=usecond();
std::vector<Aview> AcceleratorViewContainer_h;
std::vector<Vview> AcceleratorVecViewContainer_h;
tviews-=usecond();
for(int p=0;p<npoint;p++) {
AcceleratorViewContainer_h.push_back( A[p].View(AcceleratorRead));
AcceleratorVecViewContainer_h.push_back(MultTemporaries[p].View(AcceleratorWrite));
}
tviews+=usecond();
static deviceVector<Aview> AcceleratorViewContainer; AcceleratorViewContainer.resize(npoint);
static deviceVector<Vview> AcceleratorVecViewContainer; AcceleratorVecViewContainer.resize(npoint);
auto Aview_p = &AcceleratorViewContainer[0];
auto Vview_p = &AcceleratorVecViewContainer[0];
tcopy-=usecond();
acceleratorCopyToDevice(&AcceleratorViewContainer_h[0],&AcceleratorViewContainer[0],npoint *sizeof(Aview));
acceleratorCopyToDevice(&AcceleratorVecViewContainer_h[0],&AcceleratorVecViewContainer[0],npoint *sizeof(Vview));
tcopy+=usecond();
tmult-=usecond();
accelerator_for(spb, osites*nbasis*npoint, Nsimd, {
typedef decltype(coalescedRead(in_v[0](0))) calcComplex;
int32_t ss = spb/(nbasis*npoint);
int32_t bp = spb%(nbasis*npoint);
int32_t point= bp/nbasis;
int32_t b = bp%nbasis;
auto SE = Stencil_v.GetEntry(point,ss);
auto nbr = coalescedReadGeneralPermute(in_v[SE->_offset],SE->_permute,Nd);
auto res = coalescedRead(Aview_p[point][ss](0,b))*nbr(0);
for(int bb=1;bb<nbasis;bb++) {
res = res + coalescedRead(Aview_p[point][ss](bb,b))*nbr(bb);
}
coalescedWrite(Vview_p[point][ss](b),res);
});
tmult2-=usecond();
accelerator_for(sb, osites*nbasis, Nsimd, {
int ss = sb/nbasis;
int b = sb%nbasis;
auto res = coalescedRead(Vview_p[0][ss](b));
for(int point=1;point<npoint;point++){
res = res + coalescedRead(Vview_p[point][ss](b));
}
coalescedWrite(out_v[ss](b),res);
});
tmult2+=usecond();
tmult+=usecond();
for(int p=0;p<npoint;p++) {
AcceleratorViewContainer_h[p].ViewClose();
AcceleratorVecViewContainer_h[p].ViewClose();
}
}
text-=usecond();
out = Cell.Extract(pout);
text+=usecond();
ttot+=usecond();
std::cout << GridLogPerformance<<"Coarse 1rhs Mult Aviews "<<tviews<<" us"<<std::endl;
std::cout << GridLogPerformance<<"Coarse Mult exch "<<texch<<" us"<<std::endl;
std::cout << GridLogPerformance<<"Coarse Mult mult "<<tmult<<" us"<<std::endl;
std::cout << GridLogPerformance<<" of which mult2 "<<tmult2<<" us"<<std::endl;
std::cout << GridLogPerformance<<"Coarse Mult ext "<<text<<" us"<<std::endl;
std::cout << GridLogPerformance<<"Coarse Mult temps "<<ttemps<<" us"<<std::endl;
std::cout << GridLogPerformance<<"Coarse Mult copy "<<tcopy<<" us"<<std::endl;
std::cout << GridLogPerformance<<"Coarse Mult tot "<<ttot<<" us"<<std::endl;
// std::cout << GridLogPerformance<<std::endl;
std::cout << GridLogPerformance<<"Coarse Kernel flops "<< flops<<std::endl;
std::cout << GridLogPerformance<<"Coarse Kernel flop/s "<< flops/tmult<<" mflop/s"<<std::endl;
std::cout << GridLogPerformance<<"Coarse Kernel bytes/s "<< bytes/tmult<<" MB/s"<<std::endl;
std::cout << GridLogPerformance<<"Coarse overall flops/s "<< flops/ttot<<" mflop/s"<<std::endl;
std::cout << GridLogPerformance<<"Coarse total bytes "<< bytes/1e6<<" MB"<<std::endl;
};
void PopulateAdag(void)
{
for(int64_t bidx=0;bidx<CoarseGrid()->gSites() ;bidx++){
Coordinate bcoor;
CoarseGrid()->GlobalIndexToGlobalCoor(bidx,bcoor);
for(int p=0;p<geom.npoint;p++){
Coordinate scoor = bcoor;
for(int mu=0;mu<bcoor.size();mu++){
int L = CoarseGrid()->GlobalDimensions()[mu];
scoor[mu] = (bcoor[mu] - geom.shifts[p][mu] + L) % L; // Modulo arithmetic
}
// Flip to poke/peekLocalSite and not too bad
auto link = peekSite(_A[p],scoor);
int pp = geom.Reverse(p);
pokeSite(adj(link),_Adag[pp],bcoor);
}
}
}
/////////////////////////////////////////////////////////////
//
// A) Only reduced flops option is to use a padded cell of depth 4
// and apply MpcDagMpc in the padded cell.
//
// Makes for ONE application of MpcDagMpc per vector instead of 30 or 80.
// With the effective cell size around (B+8)^4 perhaps 12^4/4^4 ratio
// Cost is 81x more, same as stencil size.
//
// But: can eliminate comms and do as local dirichlet.
//
// Local exchange gauge field once.
// Apply to all vectors, local only computation.
// Must exchange ghost subcells in reverse process of PaddedCell to take inner products
//
// B) Can reduce cost: pad by 1, apply Deo (4^4+6^4+8^4+8^4 )/ (4x 4^4)
// pad by 2, apply Doe
// pad by 3, apply Deo
// then break out 8x directions; cost is ~10x MpcDagMpc per vector
//
// => almost factor of 10 in setup cost, excluding data rearrangement
//
// Intermediates -- ignore the corner terms, leave approximate and force Hermitian
// Intermediates -- pad by 2 and apply 1+8+24 = 33 times.
/////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////
// BFM HDCG style approach: Solve a system of equations to get Aij
//////////////////////////////////////////////////////////
/*
* Here, k,l index which possible shift within the 3^Nd "ball" connected by MdagM.
*
* conj(phases[block]) proj[k][ block*Nvec+j ] = \sum_ball e^{i q_k . delta} < phi_{block,j} | MdagM | phi_{(block+delta),i} >
* = \sum_ball e^{iqk.delta} A_ji
*
* Must invert matrix M_k,l = e^[i q_k . delta_l]
*
* Where q_k = delta_k . (2*M_PI/global_nb[mu])
*/
#if 0
void CoarsenOperator(LinearOperatorBase<Lattice<Fobj> > &linop,
Aggregation<Fobj,CComplex,nbasis> & Subspace)
{
std::cout << GridLogMessage<< "GeneralCoarsenMatrix "<< std::endl;
GridBase *grid = FineGrid();
RealD tproj=0.0;
RealD teigen=0.0;
RealD tmat=0.0;
RealD tphase=0.0;
RealD tinv=0.0;
/////////////////////////////////////////////////////////////
// Orthogonalise the subblocks over the basis
/////////////////////////////////////////////////////////////
CoarseScalar InnerProd(CoarseGrid());
blockOrthogonalise(InnerProd,Subspace.subspace);
const int npoint = geom.npoint;
Coordinate clatt = CoarseGrid()->GlobalDimensions();
int Nd = CoarseGrid()->Nd();
/*
* Here, k,l index which possible momentum/shift within the N-points connected by MdagM.
* Matrix index i is mapped to this shift via
* geom.shifts[i]
*
* conj(pha[block]) proj[k (which mom)][j (basis vec cpt)][block]
* = \sum_{l in ball} e^{i q_k . delta_l} < phi_{block,j} | MdagM | phi_{(block+delta_l),i} >
* = \sum_{l in ball} e^{iqk.delta_l} A_ji^{b.b+l}
* = M_{kl} A_ji^{b.b+l}
*
* Must assemble and invert matrix M_k,l = e^[i q_k . delta_l]
*
* Where q_k = delta_k . (2*M_PI/global_nb[mu])
*
* Then A{ji}^{b,b+l} = M^{-1}_{lm} ComputeProj_{m,b,i,j}
*/
teigen-=usecond();
Eigen::MatrixXcd Mkl = Eigen::MatrixXcd::Zero(npoint,npoint);
Eigen::MatrixXcd invMkl = Eigen::MatrixXcd::Zero(npoint,npoint);
ComplexD ci(0.0,1.0);
for(int k=0;k<npoint;k++){ // Loop over momenta
for(int l=0;l<npoint;l++){ // Loop over nbr relative
ComplexD phase(0.0,0.0);
for(int mu=0;mu<Nd;mu++){
RealD TwoPiL = M_PI * 2.0/ clatt[mu];
phase=phase+TwoPiL*geom.shifts[k][mu]*geom.shifts[l][mu];
}
phase=exp(phase*ci);
Mkl(k,l) = phase;
}
}
invMkl = Mkl.inverse();
teigen+=usecond();
///////////////////////////////////////////////////////////////////////
// Now compute the matrix elements of linop between the orthonormal
// set of vectors.
///////////////////////////////////////////////////////////////////////
FineField phaV(grid); // Phased block basis vector
FineField MphaV(grid);// Matrix applied
CoarseVector coarseInner(CoarseGrid());
std::vector<CoarseVector> ComputeProj(npoint,CoarseGrid());
std::vector<CoarseVector> FT(npoint,CoarseGrid());
for(int i=0;i<nbasis;i++){// Loop over basis vectors
std::cout << GridLogMessage<< "CoarsenMatrixColoured vec "<<i<<"/"<<nbasis<< std::endl;
for(int p=0;p<npoint;p++){ // Loop over momenta in npoint
/////////////////////////////////////////////////////
// Stick a phase on every block
/////////////////////////////////////////////////////
tphase-=usecond();
CoarseComplexField coor(CoarseGrid());
CoarseComplexField pha(CoarseGrid()); pha=Zero();
for(int mu=0;mu<Nd;mu++){
LatticeCoordinate(coor,mu);
RealD TwoPiL = M_PI * 2.0/ clatt[mu];
pha = pha + (TwoPiL * geom.shifts[p][mu]) * coor;
}
pha =exp(pha*ci);
phaV=Zero();
blockZAXPY(phaV,pha,Subspace.subspace[i],phaV);
tphase+=usecond();
/////////////////////////////////////////////////////////////////////
// Multiple phased subspace vector by matrix and project to subspace
// Remove local bulk phase to leave relative phases
/////////////////////////////////////////////////////////////////////
tmat-=usecond();
linop.Op(phaV,MphaV);
tmat+=usecond();
tproj-=usecond();
blockProject(coarseInner,MphaV,Subspace.subspace);
coarseInner = conjugate(pha) * coarseInner;
ComputeProj[p] = coarseInner;
tproj+=usecond();
}
tinv-=usecond();
for(int k=0;k<npoint;k++){
FT[k] = Zero();
for(int l=0;l<npoint;l++){
FT[k]= FT[k]+ invMkl(l,k)*ComputeProj[l];
}
int osites=CoarseGrid()->oSites();
autoView( A_v , _A[k], AcceleratorWrite);
autoView( FT_v , FT[k], AcceleratorRead);
accelerator_for(sss, osites, 1, {
for(int j=0;j<nbasis;j++){
A_v[sss](i,j) = FT_v[sss](j);
}
});
}
tinv+=usecond();
}
// Only needed if nonhermitian
if ( ! hermitian ) {
// std::cout << GridLogMessage<<"PopulateAdag "<<std::endl;
// PopulateAdag();
}
// Need to write something to populate Adag from A
ExchangeCoarseLinks();
std::cout << GridLogMessage<<"CoarsenOperator eigen "<<teigen<<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator phase "<<tphase<<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator mat "<<tmat <<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator proj "<<tproj<<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator inv "<<tinv<<" us"<<std::endl;
}
#else
void CoarsenOperator(LinearOperatorBase<Lattice<Fobj> > &linop,
Aggregation<Fobj,CComplex,nbasis> & Subspace)
{
std::cout << GridLogMessage<< "GeneralCoarsenMatrix "<< std::endl;
GridBase *grid = FineGrid();
RealD tproj=0.0;
RealD teigen=0.0;
RealD tmat=0.0;
RealD tphase=0.0;
RealD tphaseBZ=0.0;
RealD tinv=0.0;
/////////////////////////////////////////////////////////////
// Orthogonalise the subblocks over the basis
/////////////////////////////////////////////////////////////
CoarseScalar InnerProd(CoarseGrid());
blockOrthogonalise(InnerProd,Subspace.subspace);
// for(int s=0;s<Subspace.subspace.size();s++){
// std::cout << " subspace norm "<<norm2(Subspace.subspace[s])<<std::endl;
// }
const int npoint = geom.npoint;
Coordinate clatt = CoarseGrid()->GlobalDimensions();
int Nd = CoarseGrid()->Nd();
/*
* Here, k,l index which possible momentum/shift within the N-points connected by MdagM.
* Matrix index i is mapped to this shift via
* geom.shifts[i]
*
* conj(pha[block]) proj[k (which mom)][j (basis vec cpt)][block]
* = \sum_{l in ball} e^{i q_k . delta_l} < phi_{block,j} | MdagM | phi_{(block+delta_l),i} >
* = \sum_{l in ball} e^{iqk.delta_l} A_ji^{b.b+l}
* = M_{kl} A_ji^{b.b+l}
*
* Must assemble and invert matrix M_k,l = e^[i q_k . delta_l]
*
* Where q_k = delta_k . (2*M_PI/global_nb[mu])
*
* Then A{ji}^{b,b+l} = M^{-1}_{lm} ComputeProj_{m,b,i,j}
*/
teigen-=usecond();
Eigen::MatrixXcd Mkl = Eigen::MatrixXcd::Zero(npoint,npoint);
Eigen::MatrixXcd invMkl = Eigen::MatrixXcd::Zero(npoint,npoint);
ComplexD ci(0.0,1.0);
for(int k=0;k<npoint;k++){ // Loop over momenta
for(int l=0;l<npoint;l++){ // Loop over nbr relative
ComplexD phase(0.0,0.0);
for(int mu=0;mu<Nd;mu++){
RealD TwoPiL = M_PI * 2.0/ clatt[mu];
phase=phase+TwoPiL*geom.shifts[k][mu]*geom.shifts[l][mu];
}
phase=exp(phase*ci);
Mkl(k,l) = phase;
}
}
invMkl = Mkl.inverse();
teigen+=usecond();
///////////////////////////////////////////////////////////////////////
// Now compute the matrix elements of linop between the orthonormal
// set of vectors.
///////////////////////////////////////////////////////////////////////
FineField phaV(grid); // Phased block basis vector
FineField MphaV(grid);// Matrix applied
std::vector<FineComplexField> phaF(npoint,grid);
std::vector<CoarseComplexField> pha(npoint,CoarseGrid());
CoarseVector coarseInner(CoarseGrid());
typedef typename CComplex::scalar_type SComplex;
FineComplexField one(grid); one=SComplex(1.0);
FineComplexField zz(grid); zz = Zero();
tphase=-usecond();
for(int p=0;p<npoint;p++){ // Loop over momenta in npoint
/////////////////////////////////////////////////////
// Stick a phase on every block
/////////////////////////////////////////////////////
CoarseComplexField coor(CoarseGrid());
pha[p]=Zero();
for(int mu=0;mu<Nd;mu++){
LatticeCoordinate(coor,mu);
RealD TwoPiL = M_PI * 2.0/ clatt[mu];
pha[p] = pha[p] + (TwoPiL * geom.shifts[p][mu]) * coor;
}
pha[p] =exp(pha[p]*ci);
blockZAXPY(phaF[p],pha[p],one,zz);
}
tphase+=usecond();
std::vector<CoarseVector> ComputeProj(npoint,CoarseGrid());
std::vector<CoarseVector> FT(npoint,CoarseGrid());
for(int i=0;i<nbasis;i++){// Loop over basis vectors
std::cout << GridLogMessage<< "CoarsenMatrixColoured vec "<<i<<"/"<<nbasis<< std::endl;
for(int p=0;p<npoint;p++){ // Loop over momenta in npoint
tphaseBZ-=usecond();
phaV = phaF[p]*Subspace.subspace[i];
tphaseBZ+=usecond();
/////////////////////////////////////////////////////////////////////
// Multiple phased subspace vector by matrix and project to subspace
// Remove local bulk phase to leave relative phases
/////////////////////////////////////////////////////////////////////
tmat-=usecond();
linop.Op(phaV,MphaV);
tmat+=usecond();
// std::cout << i << " " <<p << " MphaV "<<norm2(MphaV)<<" "<<norm2(phaV)<<std::endl;
tproj-=usecond();
blockProject(coarseInner,MphaV,Subspace.subspace);
coarseInner = conjugate(pha[p]) * coarseInner;
ComputeProj[p] = coarseInner;
tproj+=usecond();
// std::cout << i << " " <<p << " ComputeProj "<<norm2(ComputeProj[p])<<std::endl;
}
tinv-=usecond();
for(int k=0;k<npoint;k++){
FT[k] = Zero();
for(int l=0;l<npoint;l++){
FT[k]= FT[k]+ invMkl(l,k)*ComputeProj[l];
}
int osites=CoarseGrid()->oSites();
autoView( A_v , _A[k], AcceleratorWrite);
autoView( FT_v , FT[k], AcceleratorRead);
accelerator_for(sss, osites, 1, {
for(int j=0;j<nbasis;j++){
A_v[sss](i,j) = FT_v[sss](j);
}
});
}
tinv+=usecond();
}
// Only needed if nonhermitian
if ( ! hermitian ) {
// std::cout << GridLogMessage<<"PopulateAdag "<<std::endl;
// PopulateAdag();
}
for(int p=0;p<geom.npoint;p++){
std::cout << " _A["<<p<<"] "<<norm2(_A[p])<<std::endl;
}
// Need to write something to populate Adag from A
ExchangeCoarseLinks();
std::cout << GridLogMessage<<"CoarsenOperator eigen "<<teigen<<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator phase "<<tphase<<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator phaseBZ "<<tphaseBZ<<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator mat "<<tmat <<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator proj "<<tproj<<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator inv "<<tinv<<" us"<<std::endl;
}
#endif
void ExchangeCoarseLinks(void){
for(int p=0;p<geom.npoint;p++){
_A[p] = Cell.ExchangePeriodic(_A[p]);
// _Adag[p]= Cell.ExchangePeriodic(_Adag[p]);
}
}
virtual void Mdiag (const Field &in, Field &out){ assert(0);};
virtual void Mdir (const Field &in, Field &out,int dir, int disp){assert(0);};
virtual void MdirAll (const Field &in, std::vector<Field> &out){assert(0);};
};
NAMESPACE_END(Grid);
@@ -1,729 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/GeneralCoarsenedMatrixMultiRHS.h
Copyright (C) 2015
Author: Peter Boyle <pboyle@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
// Fine Object == (per site) type of fine field
// nbasis == number of deflation vectors
template<class Fobj,class CComplex,int nbasis>
class MultiGeneralCoarsenedMatrix : public SparseMatrixBase<Lattice<iVector<CComplex,nbasis > > > {
public:
typedef typename CComplex::scalar_object SComplex;
typedef GeneralCoarsenedMatrix<Fobj,CComplex,nbasis> GeneralCoarseOp;
typedef MultiGeneralCoarsenedMatrix<Fobj,CComplex,nbasis> MultiGeneralCoarseOp;
typedef iVector<CComplex,nbasis > siteVector;
typedef iMatrix<CComplex,nbasis > siteMatrix;
typedef iVector<SComplex,nbasis > calcVector;
typedef iMatrix<SComplex,nbasis > calcMatrix;
typedef Lattice<iScalar<CComplex> > CoarseComplexField;
typedef Lattice<siteVector> CoarseVector;
typedef Lattice<iMatrix<CComplex,nbasis > > CoarseMatrix;
typedef iMatrix<CComplex,nbasis > Cobj;
typedef iVector<CComplex,nbasis > Cvec;
typedef Lattice< CComplex > CoarseScalar; // used for inner products on fine field
typedef Lattice<Fobj > FineField;
typedef Lattice<CComplex > FineComplexField;
typedef CoarseVector Field;
////////////////////
// Data members
////////////////////
GridCartesian * _CoarseGridMulti;
NonLocalStencilGeometry geom;
NonLocalStencilGeometry geom_srhs;
PaddedCell Cell;
GeneralLocalStencil Stencil;
deviceVector<calcVector> BLAS_B;
deviceVector<calcVector> BLAS_C;
std::vector<deviceVector<calcMatrix> > BLAS_A;
std::vector<deviceVector<ComplexD *> > BLAS_AP;
std::vector<deviceVector<ComplexD *> > BLAS_BP;
deviceVector<ComplexD *> BLAS_CP;
///////////////////////
// Interface
///////////////////////
GridBase * Grid(void) { return _CoarseGridMulti; }; // this is all the linalg routines need to know
GridCartesian * CoarseGrid(void) { return _CoarseGridMulti; }; // this is all the linalg routines need to know
// Can be used to do I/O on the operator matrices externally
void SetMatrix (int p,CoarseMatrix & A)
{
assert(A.size()==geom_srhs.npoint);
GridtoBLAS(A[p],BLAS_A[p]);
}
void GetMatrix (int p,CoarseMatrix & A)
{
assert(A.size()==geom_srhs.npoint);
BLAStoGrid(A[p],BLAS_A[p]);
}
void CopyMatrix (GeneralCoarseOp &_Op)
{
for(int p=0;p<geom.npoint;p++){
auto Aup = _Op.Cell.Extract(_Op._A[p]);
//Unpadded
GridtoBLAS(Aup,BLAS_A[p]);
}
}
/*
void CheckMatrix (GeneralCoarseOp &_Op)
{
std::cout <<"************* Checking the little direc operator mRHS"<<std::endl;
for(int p=0;p<geom.npoint;p++){
//Unpadded
auto Aup = _Op.Cell.Extract(_Op._A[p]);
auto Ack = Aup;
BLAStoGrid(Ack,BLAS_A[p]);
std::cout << p<<" Ack "<<norm2(Ack)<<std::endl;
std::cout << p<<" Aup "<<norm2(Aup)<<std::endl;
}
std::cout <<"************* "<<std::endl;
}
*/
MultiGeneralCoarsenedMatrix(NonLocalStencilGeometry &_geom,GridCartesian *CoarseGridMulti) :
_CoarseGridMulti(CoarseGridMulti),
geom_srhs(_geom),
geom(_CoarseGridMulti,_geom.hops,_geom.skip+1),
Cell(geom.Depth(),_CoarseGridMulti),
Stencil(Cell.grids.back(),geom.shifts) // padded cell stencil
{
int32_t padded_sites = Cell.grids.back()->lSites();
int32_t unpadded_sites = CoarseGridMulti->lSites();
int32_t nrhs = CoarseGridMulti->FullDimensions()[0]; // # RHS
int32_t orhs = nrhs/CComplex::Nsimd();
padded_sites = padded_sites/nrhs;
unpadded_sites = unpadded_sites/nrhs;
/////////////////////////////////////////////////
// Device data vector storage
/////////////////////////////////////////////////
BLAS_A.resize(geom.npoint);
for(int p=0;p<geom.npoint;p++){
BLAS_A[p].resize (unpadded_sites); // no ghost zone, npoint elements
}
BLAS_B.resize(nrhs *padded_sites); // includes ghost zone
BLAS_C.resize(nrhs *unpadded_sites); // no ghost zone
BLAS_AP.resize(geom.npoint);
BLAS_BP.resize(geom.npoint);
for(int p=0;p<geom.npoint;p++){
BLAS_AP[p].resize(unpadded_sites);
BLAS_BP[p].resize(unpadded_sites);
}
BLAS_CP.resize(unpadded_sites);
/////////////////////////////////////////////////
// Pointers to data
/////////////////////////////////////////////////
// Site identity mapping for A
for(int p=0;p<geom.npoint;p++){
for(int ss=0;ss<unpadded_sites;ss++){
ComplexD *ptr = (ComplexD *)&BLAS_A[p][ss];
acceleratorPut(BLAS_AP[p][ss],ptr);
}
}
// Site identity mapping for C
for(int ss=0;ss<unpadded_sites;ss++){
ComplexD *ptr = (ComplexD *)&BLAS_C[ss*nrhs];
acceleratorPut(BLAS_CP[ss],ptr);
}
// Neighbour table is more complicated
int32_t j=0; // Interior point counter (unpadded)
for(int32_t s=0;s<padded_sites;s++){ // 4 volume, padded
int ghost_zone=0;
for(int32_t point = 0 ; point < geom.npoint; point++){
int i=s*orhs*geom.npoint+point;
if( Stencil._entries[i]._wrap ) { // stencil is indexed by the oSite of the CoarseGridMulti, hence orhs factor
ghost_zone=1; // If general stencil wrapped in any direction, wrap=1
}
}
if( ghost_zone==0) {
for(int32_t point = 0 ; point < geom.npoint; point++){
int i=s*orhs*geom.npoint+point;
int32_t nbr = Stencil._entries[i]._offset*CComplex::Nsimd(); // oSite -> lSite
assert(nbr<BLAS_B.size());
ComplexD * ptr = (ComplexD *)&BLAS_B[nbr];
acceleratorPut(BLAS_BP[point][j],ptr); // neighbour indexing in ghost zone volume
}
j++;
}
}
assert(j==unpadded_sites);
}
template<class vobj> void GridtoBLAS(const Lattice<vobj> &from,deviceVector<typename vobj::scalar_object> &to)
{
typedef typename vobj::scalar_object sobj;
typedef typename vobj::scalar_type scalar_type;
typedef typename vobj::vector_type vector_type;
GridBase *Fg = from.Grid();
assert(!Fg->_isCheckerBoarded);
int nd = Fg->_ndimension;
to.resize(Fg->lSites());
Coordinate LocalLatt = Fg->LocalDimensions();
size_t nsite = 1;
for(int i=0;i<nd;i++) nsite *= LocalLatt[i];
////////////////////////////////////////////////////////////////////////////////////////////////
// do the index calc on the GPU
////////////////////////////////////////////////////////////////////////////////////////////////
Coordinate f_ostride = Fg->_ostride;
Coordinate f_istride = Fg->_istride;
Coordinate f_rdimensions = Fg->_rdimensions;
autoView(from_v,from,AcceleratorRead);
auto to_v = &to[0];
const int words=sizeof(vobj)/sizeof(vector_type);
accelerator_for(idx,nsite,1,{
Coordinate from_coor, base;
Lexicographic::CoorFromIndex(base,idx,LocalLatt);
for(int i=0;i<nd;i++){
from_coor[i] = base[i];
}
int from_oidx = 0; for(int d=0;d<nd;d++) from_oidx+=f_ostride[d]*(from_coor[d]%f_rdimensions[d]);
int from_lane = 0; for(int d=0;d<nd;d++) from_lane+=f_istride[d]*(from_coor[d]/f_rdimensions[d]);
const vector_type* from = (const vector_type *)&from_v[from_oidx];
scalar_type* to = (scalar_type *)&to_v[idx];
scalar_type stmp;
for(int w=0;w<words;w++){
stmp = getlane(from[w], from_lane);
to[w] = stmp;
}
});
}
template<class vobj> void BLAStoGrid(Lattice<vobj> &grid,deviceVector<typename vobj::scalar_object> &in)
{
typedef typename vobj::scalar_object sobj;
typedef typename vobj::scalar_type scalar_type;
typedef typename vobj::vector_type vector_type;
GridBase *Tg = grid.Grid();
assert(!Tg->_isCheckerBoarded);
int nd = Tg->_ndimension;
assert(in.size()==Tg->lSites());
Coordinate LocalLatt = Tg->LocalDimensions();
size_t nsite = 1;
for(int i=0;i<nd;i++) nsite *= LocalLatt[i];
////////////////////////////////////////////////////////////////////////////////////////////////
// do the index calc on the GPU
////////////////////////////////////////////////////////////////////////////////////////////////
Coordinate t_ostride = Tg->_ostride;
Coordinate t_istride = Tg->_istride;
Coordinate t_rdimensions = Tg->_rdimensions;
autoView(to_v,grid,AcceleratorWrite);
auto from_v = &in[0];
const int words=sizeof(vobj)/sizeof(vector_type);
accelerator_for(idx,nsite,1,{
Coordinate to_coor, base;
Lexicographic::CoorFromIndex(base,idx,LocalLatt);
for(int i=0;i<nd;i++){
to_coor[i] = base[i];
}
int to_oidx = 0; for(int d=0;d<nd;d++) to_oidx+=t_ostride[d]*(to_coor[d]%t_rdimensions[d]);
int to_lane = 0; for(int d=0;d<nd;d++) to_lane+=t_istride[d]*(to_coor[d]/t_rdimensions[d]);
vector_type* to = (vector_type *)&to_v[to_oidx];
scalar_type* from = (scalar_type *)&from_v[idx];
scalar_type stmp;
for(int w=0;w<words;w++){
stmp=from[w];
putlane(to[w], stmp, to_lane);
}
});
}
void CoarsenOperator(LinearOperatorBase<Lattice<Fobj> > &linop,
Aggregation<Fobj,CComplex,nbasis> & Subspace,
GridBase *CoarseGrid)
{
#if 0
std::cout << GridLogMessage<< "GeneralCoarsenMatrixMrhs "<< std::endl;
GridBase *grid = Subspace.FineGrid;
/////////////////////////////////////////////////////////////
// Orthogonalise the subblocks over the basis
/////////////////////////////////////////////////////////////
CoarseScalar InnerProd(CoarseGrid);
blockOrthogonalise(InnerProd,Subspace.subspace);
const int npoint = geom_srhs.npoint;
Coordinate clatt = CoarseGrid->GlobalDimensions();
int Nd = CoarseGrid->Nd();
/*
* Here, k,l index which possible momentum/shift within the N-points connected by MdagM.
* Matrix index i is mapped to this shift via
* geom.shifts[i]
*
* conj(pha[block]) proj[k (which mom)][j (basis vec cpt)][block]
* = \sum_{l in ball} e^{i q_k . delta_l} < phi_{block,j} | MdagM | phi_{(block+delta_l),i} >
* = \sum_{l in ball} e^{iqk.delta_l} A_ji^{b.b+l}
* = M_{kl} A_ji^{b.b+l}
*
* Must assemble and invert matrix M_k,l = e^[i q_k . delta_l]
*
* Where q_k = delta_k . (2*M_PI/global_nb[mu])
*
* Then A{ji}^{b,b+l} = M^{-1}_{lm} ComputeProj_{m,b,i,j}
*/
Eigen::MatrixXcd Mkl = Eigen::MatrixXcd::Zero(npoint,npoint);
Eigen::MatrixXcd invMkl = Eigen::MatrixXcd::Zero(npoint,npoint);
ComplexD ci(0.0,1.0);
for(int k=0;k<npoint;k++){ // Loop over momenta
for(int l=0;l<npoint;l++){ // Loop over nbr relative
ComplexD phase(0.0,0.0);
for(int mu=0;mu<Nd;mu++){
RealD TwoPiL = M_PI * 2.0/ clatt[mu];
phase=phase+TwoPiL*geom_srhs.shifts[k][mu]*geom_srhs.shifts[l][mu];
}
phase=exp(phase*ci);
Mkl(k,l) = phase;
}
}
invMkl = Mkl.inverse();
///////////////////////////////////////////////////////////////////////
// Now compute the matrix elements of linop between the orthonormal
// set of vectors.
///////////////////////////////////////////////////////////////////////
FineField phaV(grid); // Phased block basis vector
FineField MphaV(grid);// Matrix applied
std::vector<FineComplexField> phaF(npoint,grid);
std::vector<CoarseComplexField> pha(npoint,CoarseGrid);
CoarseVector coarseInner(CoarseGrid);
typedef typename CComplex::scalar_type SComplex;
FineComplexField one(grid); one=SComplex(1.0);
FineComplexField zz(grid); zz = Zero();
for(int p=0;p<npoint;p++){ // Loop over momenta in npoint
/////////////////////////////////////////////////////
// Stick a phase on every block
/////////////////////////////////////////////////////
CoarseComplexField coor(CoarseGrid);
pha[p]=Zero();
for(int mu=0;mu<Nd;mu++){
LatticeCoordinate(coor,mu);
RealD TwoPiL = M_PI * 2.0/ clatt[mu];
pha[p] = pha[p] + (TwoPiL * geom_srhs.shifts[p][mu]) * coor;
}
pha[p] =exp(pha[p]*ci);
blockZAXPY(phaF[p],pha[p],one,zz);
}
// Could save on temporary storage here
std::vector<CoarseMatrix> _A;
_A.resize(geom_srhs.npoint,CoarseGrid);
std::vector<CoarseVector> ComputeProj(npoint,CoarseGrid);
CoarseVector FT(CoarseGrid);
for(int i=0;i<nbasis;i++){// Loop over basis vectors
std::cout << GridLogMessage<< "CoarsenMatrixColoured vec "<<i<<"/"<<nbasis<< std::endl;
for(int p=0;p<npoint;p++){ // Loop over momenta in npoint
phaV = phaF[p]*Subspace.subspace[i];
/////////////////////////////////////////////////////////////////////
// Multiple phased subspace vector by matrix and project to subspace
// Remove local bulk phase to leave relative phases
/////////////////////////////////////////////////////////////////////
linop.Op(phaV,MphaV);
// Fixme, could use batched block projector here
blockProject(coarseInner,MphaV,Subspace.subspace);
coarseInner = conjugate(pha[p]) * coarseInner;
ComputeProj[p] = coarseInner;
}
// Could do this with a block promote or similar BLAS call via the MultiRHSBlockProjector with a const matrix.
for(int k=0;k<npoint;k++){
FT = Zero();
for(int l=0;l<npoint;l++){
FT= FT+ invMkl(l,k)*ComputeProj[l];
}
int osites=CoarseGrid->oSites();
autoView( A_v , _A[k], AcceleratorWrite);
autoView( FT_v , FT, AcceleratorRead);
accelerator_for(sss, osites, 1, {
for(int j=0;j<nbasis;j++){
A_v[sss](i,j) = FT_v[sss](j);
}
});
}
}
// Only needed if nonhermitian
// if ( ! hermitian ) {
// std::cout << GridLogMessage<<"PopulateAdag "<<std::endl;
// PopulateAdag();
// }
// Need to write something to populate Adag from A
for(int p=0;p<geom_srhs.npoint;p++){
GridtoBLAS(_A[p],BLAS_A[p]);
}
/*
Grid : Message : 11698.730546 s : CoarsenOperator eigen 1334 us
Grid : Message : 11698.730563 s : CoarsenOperator phase 34729 us
Grid : Message : 11698.730565 s : CoarsenOperator phaseBZ 2423814 us
Grid : Message : 11698.730566 s : CoarsenOperator mat 127890998 us
Grid : Message : 11698.730567 s : CoarsenOperator proj 515840840 us
Grid : Message : 11698.730568 s : CoarsenOperator inv 103948313 us
Takes 600s to compute matrix elements, DOMINATED by the block project.
Easy to speed up with the batched block project.
Store npoint vectors, get npoint x Nbasis block projection, and 81 fold faster.
// Block project below taks to 240s
Grid : Message : 328.193418 s : CoarsenOperator phase 38338 us
Grid : Message : 328.193434 s : CoarsenOperator phaseBZ 1711226 us
Grid : Message : 328.193436 s : CoarsenOperator mat 122213270 us
//Grid : Message : 328.193438 s : CoarsenOperator proj 1181154 us <-- this is mistimed
//Grid : Message : 11698.730568 s : CoarsenOperator inv 103948313 us <-- Cut this ~10x if lucky by loop fusion
*/
#else
RealD tproj=0.0;
RealD tmat=0.0;
RealD tphase=0.0;
RealD tphaseBZ=0.0;
RealD tinv=0.0;
std::cout << GridLogMessage<< "GeneralCoarsenMatrixMrhs "<< std::endl;
GridBase *grid = Subspace.FineGrid;
/////////////////////////////////////////////////////////////
// Orthogonalise the subblocks over the basis
/////////////////////////////////////////////////////////////
CoarseScalar InnerProd(CoarseGrid);
blockOrthogonalise(InnerProd,Subspace.subspace);
MultiRHSBlockProject<Lattice<Fobj> > Projector;
Projector.Allocate(nbasis,grid,CoarseGrid);
Projector.ImportBasis(Subspace.subspace);
const int npoint = geom_srhs.npoint;
Coordinate clatt = CoarseGrid->GlobalDimensions();
int Nd = CoarseGrid->Nd();
/*
* Here, k,l index which possible momentum/shift within the N-points connected by MdagM.
* Matrix index i is mapped to this shift via
* geom.shifts[i]
*
* conj(pha[block]) proj[k (which mom)][j (basis vec cpt)][block]
* = \sum_{l in ball} e^{i q_k . delta_l} < phi_{block,j} | MdagM | phi_{(block+delta_l),i} >
* = \sum_{l in ball} e^{iqk.delta_l} A_ji^{b.b+l}
* = M_{kl} A_ji^{b.b+l}
*
* Must assemble and invert matrix M_k,l = e^[i q_k . delta_l]
*
* Where q_k = delta_k . (2*M_PI/global_nb[mu])
*
* Then A{ji}^{b,b+l} = M^{-1}_{lm} ComputeProj_{m,b,i,j}
*/
Eigen::MatrixXcd Mkl = Eigen::MatrixXcd::Zero(npoint,npoint);
Eigen::MatrixXcd invMkl = Eigen::MatrixXcd::Zero(npoint,npoint);
ComplexD ci(0.0,1.0);
for(int k=0;k<npoint;k++){ // Loop over momenta
for(int l=0;l<npoint;l++){ // Loop over nbr relative
ComplexD phase(0.0,0.0);
for(int mu=0;mu<Nd;mu++){
RealD TwoPiL = M_PI * 2.0/ clatt[mu];
phase=phase+TwoPiL*geom_srhs.shifts[k][mu]*geom_srhs.shifts[l][mu];
}
phase=exp(phase*ci);
Mkl(k,l) = phase;
}
}
invMkl = Mkl.inverse();
///////////////////////////////////////////////////////////////////////
// Now compute the matrix elements of linop between the orthonormal
// set of vectors.
///////////////////////////////////////////////////////////////////////
FineField phaV(grid); // Phased block basis vector
FineField MphaV(grid);// Matrix applied
std::vector<FineComplexField> phaF(npoint,grid);
std::vector<CoarseComplexField> pha(npoint,CoarseGrid);
CoarseVector coarseInner(CoarseGrid);
tphase=-usecond();
typedef typename CComplex::scalar_type SComplex;
FineComplexField one(grid); one=SComplex(1.0);
FineComplexField zz(grid); zz = Zero();
for(int p=0;p<npoint;p++){ // Loop over momenta in npoint
/////////////////////////////////////////////////////
// Stick a phase on every block
/////////////////////////////////////////////////////
CoarseComplexField coor(CoarseGrid);
pha[p]=Zero();
for(int mu=0;mu<Nd;mu++){
LatticeCoordinate(coor,mu);
RealD TwoPiL = M_PI * 2.0/ clatt[mu];
pha[p] = pha[p] + (TwoPiL * geom_srhs.shifts[p][mu]) * coor;
}
pha[p] =exp(pha[p]*ci);
blockZAXPY(phaF[p],pha[p],one,zz);
}
tphase+=usecond();
// Could save on temporary storage here
std::vector<CoarseMatrix> _A;
_A.resize(geom_srhs.npoint,CoarseGrid);
// Count use small chunks than npoint == 81 and save memory
int batch = 9;
std::vector<FineField> _MphaV(batch,grid);
std::vector<CoarseVector> TmpProj(batch,CoarseGrid);
std::vector<CoarseVector> ComputeProj(npoint,CoarseGrid);
CoarseVector FT(CoarseGrid);
for(int i=0;i<nbasis;i++){// Loop over basis vectors
std::cout << GridLogMessage<< "CoarsenMatrixColoured vec "<<i<<"/"<<nbasis<< std::endl;
// std::cout << GridLogMessage << " phasing the fine vector "<<std::endl;
// Fixme : do this in batches
for(int p=0;p<npoint;p+=batch){ // Loop over momenta in npoint
for(int b=0;b<MIN(batch,npoint-p);b++){
tphaseBZ-=usecond();
phaV = phaF[p+b]*Subspace.subspace[i];
tphaseBZ+=usecond();
/////////////////////////////////////////////////////////////////////
// Multiple phased subspace vector by matrix and project to subspace
// Remove local bulk phase to leave relative phases
/////////////////////////////////////////////////////////////////////
// Memory footprint was an issue
tmat-=usecond();
linop.Op(phaV,MphaV);
_MphaV[b] = MphaV;
tmat+=usecond();
}
// std::cout << GridLogMessage << " Calling block project "<<std::endl;
tproj-=usecond();
Projector.blockProject(_MphaV,TmpProj);
tproj+=usecond();
// std::cout << GridLogMessage << " conj phasing the coarse vectors "<<std::endl;
for(int b=0;b<MIN(batch,npoint-p);b++){
ComputeProj[p+b] = conjugate(pha[p+b])*TmpProj[b];
}
}
// Could do this with a block promote or similar BLAS call via the MultiRHSBlockProjector with a const matrix.
// std::cout << GridLogMessage << " Starting FT inv "<<std::endl;
tinv-=usecond();
for(int k=0;k<npoint;k++){
FT = Zero();
// 81 kernel calls as many ComputeProj vectors
// Could fuse with a vector of views, but ugly
// Could unroll the expression and run fewer kernels -- much more attractive
// Could also do non blocking.
#if 0
for(int l=0;l<npoint;l++){
FT= FT+ invMkl(l,k)*ComputeProj[l];
}
#else
const int radix = 9;
int ll;
for(ll=0;ll+radix-1<npoint;ll+=radix){
// When ll = npoint-radix, ll+radix-1 = npoint-1, and we do it all.
FT = FT
+ invMkl(ll+0,k)*ComputeProj[ll+0]
+ invMkl(ll+1,k)*ComputeProj[ll+1]
+ invMkl(ll+2,k)*ComputeProj[ll+2]
+ invMkl(ll+3,k)*ComputeProj[ll+3]
+ invMkl(ll+4,k)*ComputeProj[ll+4]
+ invMkl(ll+5,k)*ComputeProj[ll+5]
+ invMkl(ll+6,k)*ComputeProj[ll+6]
+ invMkl(ll+7,k)*ComputeProj[ll+7]
+ invMkl(ll+8,k)*ComputeProj[ll+8];
}
for(int l=ll;l<npoint;l++){
FT= FT+ invMkl(l,k)*ComputeProj[l];
}
#endif
// 1 kernel call -- must be cheaper
int osites=CoarseGrid->oSites();
autoView( A_v , _A[k], AcceleratorWrite);
autoView( FT_v , FT, AcceleratorRead);
accelerator_for(sss, osites, 1, {
for(int j=0;j<nbasis;j++){
A_v[sss](i,j) = FT_v[sss](j);
}
});
}
tinv+=usecond();
}
// Only needed if nonhermitian
// if ( ! hermitian ) {
// std::cout << GridLogMessage<<"PopulateAdag "<<std::endl;
// PopulateAdag();
// }
// Need to write something to populate Adag from A
// std::cout << GridLogMessage << " Calling GridtoBLAS "<<std::endl;
for(int p=0;p<geom_srhs.npoint;p++){
GridtoBLAS(_A[p],BLAS_A[p]);
}
std::cout << GridLogMessage<<"CoarsenOperator phase "<<tphase<<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator phaseBZ "<<tphaseBZ<<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator mat "<<tmat <<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator proj "<<tproj<<" us"<<std::endl;
std::cout << GridLogMessage<<"CoarsenOperator inv "<<tinv<<" us"<<std::endl;
#endif
}
void Mdag(const CoarseVector &in, CoarseVector &out)
{
this->M(in,out);
}
void M (const CoarseVector &in, CoarseVector &out)
{
// std::cout << GridLogMessage << "New Mrhs coarse"<<std::endl;
conformable(CoarseGrid(),in.Grid());
conformable(in.Grid(),out.Grid());
out.Checkerboard() = in.Checkerboard();
RealD t_tot;
RealD t_exch;
RealD t_GtoB;
RealD t_BtoG;
RealD t_mult;
t_tot=-usecond();
CoarseVector tin=in;
t_exch=-usecond();
CoarseVector pin = Cell.ExchangePeriodic(tin); //padded input
t_exch+=usecond();
CoarseVector pout(pin.Grid());
int npoint = geom.npoint;
typedef calcMatrix* Aview;
typedef LatticeView<Cvec> Vview;
const int Nsimd = CComplex::Nsimd();
int64_t nrhs =pin.Grid()->GlobalDimensions()[0];
assert(nrhs>=1);
RealD flops,bytes;
int64_t osites=in.Grid()->oSites(); // unpadded
int64_t unpadded_vol = CoarseGrid()->lSites()/nrhs;
flops = 1.0* npoint * nbasis * nbasis * 8.0 * osites * CComplex::Nsimd();
bytes = 1.0*osites*sizeof(siteMatrix)*npoint/pin.Grid()->GlobalDimensions()[0]
+ 2.0*osites*sizeof(siteVector)*npoint;
t_GtoB=-usecond();
GridtoBLAS(pin,BLAS_B);
t_GtoB+=usecond();
GridBLAS BLAS;
t_mult=-usecond();
for(int p=0;p<geom.npoint;p++){
RealD c = 1.0;
if (p==0) c = 0.0;
ComplexD beta(c);
BLAS.gemmBatched(nbasis,nrhs,nbasis,
ComplexD(1.0),
BLAS_AP[p],
BLAS_BP[p],
ComplexD(c),
BLAS_CP);
}
BLAS.synchronise();
t_mult+=usecond();
t_BtoG=-usecond();
BLAStoGrid(out,BLAS_C);
t_BtoG+=usecond();
t_tot+=usecond();
/*
std::cout << GridLogMessage << "New Mrhs coarse DONE "<<std::endl;
std::cout << GridLogMessage<<"Coarse Mult exch "<<t_exch<<" us"<<std::endl;
std::cout << GridLogMessage<<"Coarse Mult mult "<<t_mult<<" us"<<std::endl;
std::cout << GridLogMessage<<"Coarse Mult GtoB "<<t_GtoB<<" us"<<std::endl;
std::cout << GridLogMessage<<"Coarse Mult BtoG "<<t_BtoG<<" us"<<std::endl;
std::cout << GridLogMessage<<"Coarse Mult tot "<<t_tot<<" us"<<std::endl;
*/
// std::cout << GridLogMessage<<std::endl;
// std::cout << GridLogMessage<<"Coarse Kernel flops "<< flops<<std::endl;
// std::cout << GridLogMessage<<"Coarse Kernel flop/s "<< flops/t_mult<<" mflop/s"<<std::endl;
// std::cout << GridLogMessage<<"Coarse Kernel bytes/s "<< bytes/t_mult/1000<<" GB/s"<<std::endl;
// std::cout << GridLogMessage<<"Coarse overall flops/s "<< flops/t_tot<<" mflop/s"<<std::endl;
// std::cout << GridLogMessage<<"Coarse total bytes "<< bytes/1e6<<" MB"<<std::endl;
};
virtual void Mdiag (const Field &in, Field &out){ assert(0);};
virtual void Mdir (const Field &in, Field &out,int dir, int disp){assert(0);};
virtual void MdirAll (const Field &in, std::vector<Field> &out){assert(0);};
};
NAMESPACE_END(Grid);
-238
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@@ -1,238 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/GeneralCoarsenedMatrix.h
Copyright (C) 2015
Author: Peter Boyle <pboyle@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
/////////////////////////////////////////////////////////////////
// Geometry class in cartesian case
/////////////////////////////////////////////////////////////////
class Geometry {
public:
int npoint;
int base;
std::vector<int> directions ;
std::vector<int> displacements;
std::vector<int> points_dagger;
Geometry(int _d) {
base = (_d==5) ? 1:0;
// make coarse grid stencil for 4d , not 5d
if ( _d==5 ) _d=4;
npoint = 2*_d+1;
directions.resize(npoint);
displacements.resize(npoint);
points_dagger.resize(npoint);
for(int d=0;d<_d;d++){
directions[d ] = d+base;
directions[d+_d] = d+base;
displacements[d ] = +1;
displacements[d+_d]= -1;
points_dagger[d ] = d+_d;
points_dagger[d+_d] = d;
}
directions [2*_d]=0;
displacements[2*_d]=0;
points_dagger[2*_d]=2*_d;
}
int point(int dir, int disp) {
assert(disp == -1 || disp == 0 || disp == 1);
assert(base+0 <= dir && dir < base+4);
// directions faster index = new indexing
// 4d (base = 0):
// point 0 1 2 3 4 5 6 7 8
// dir 0 1 2 3 0 1 2 3 0
// disp +1 +1 +1 +1 -1 -1 -1 -1 0
// 5d (base = 1):
// point 0 1 2 3 4 5 6 7 8
// dir 1 2 3 4 1 2 3 4 0
// disp +1 +1 +1 +1 -1 -1 -1 -1 0
// displacements faster index = old indexing
// 4d (base = 0):
// point 0 1 2 3 4 5 6 7 8
// dir 0 0 1 1 2 2 3 3 0
// disp +1 -1 +1 -1 +1 -1 +1 -1 0
// 5d (base = 1):
// point 0 1 2 3 4 5 6 7 8
// dir 1 1 2 2 3 3 4 4 0
// disp +1 -1 +1 -1 +1 -1 +1 -1 0
if(dir == 0 and disp == 0)
return 8;
else // New indexing
return (1 - disp) / 2 * 4 + dir - base;
// else // Old indexing
// return (4 * (dir - base) + 1 - disp) / 2;
}
};
/////////////////////////////////////////////////////////////////
// Less local equivalent of Geometry class in cartesian case
/////////////////////////////////////////////////////////////////
class NonLocalStencilGeometry {
public:
// int depth;
int skip;
int hops;
int npoint;
std::vector<Coordinate> shifts;
Coordinate stencil_size;
Coordinate stencil_lo;
Coordinate stencil_hi;
GridCartesian *grid;
GridCartesian *Grid() {return grid;};
int Depth(void){return 1;}; // Ghost zone depth
int Hops(void){return hops;}; // # of hops=> level of corner fill in in stencil
int DimSkip(void){return skip;};
virtual ~NonLocalStencilGeometry() {};
int Reverse(int point)
{
int Nd = Grid()->Nd();
Coordinate shft = shifts[point];
Coordinate rev(Nd);
for(int mu=0;mu<Nd;mu++) rev[mu]= -shft[mu];
for(int p=0;p<npoint;p++){
if(rev==shifts[p]){
return p;
}
}
assert(0);
return -1;
}
void BuildShifts(void)
{
this->shifts.resize(0);
int Nd = this->grid->Nd();
int dd = this->DimSkip();
for(int s0=this->stencil_lo[dd+0];s0<=this->stencil_hi[dd+0];s0++){
for(int s1=this->stencil_lo[dd+1];s1<=this->stencil_hi[dd+1];s1++){
for(int s2=this->stencil_lo[dd+2];s2<=this->stencil_hi[dd+2];s2++){
for(int s3=this->stencil_lo[dd+3];s3<=this->stencil_hi[dd+3];s3++){
Coordinate sft(Nd,0);
sft[dd+0] = s0;
sft[dd+1] = s1;
sft[dd+2] = s2;
sft[dd+3] = s3;
int nhops = abs(s0)+abs(s1)+abs(s2)+abs(s3);
if(nhops<=this->hops) this->shifts.push_back(sft);
}}}}
this->npoint = this->shifts.size();
std::cout << GridLogMessage << "NonLocalStencilGeometry has "<< this->npoint << " terms in stencil "<<std::endl;
}
NonLocalStencilGeometry(GridCartesian *_coarse_grid,int _hops,int _skip) : grid(_coarse_grid), hops(_hops), skip(_skip)
{
Coordinate latt = grid->GlobalDimensions();
stencil_size.resize(grid->Nd());
stencil_lo.resize(grid->Nd());
stencil_hi.resize(grid->Nd());
for(int d=0;d<grid->Nd();d++){
if ( latt[d] == 1 ) {
stencil_lo[d] = 0;
stencil_hi[d] = 0;
stencil_size[d]= 1;
} else if ( latt[d] == 2 ) {
stencil_lo[d] = -1;
stencil_hi[d] = 0;
stencil_size[d]= 2;
} else if ( latt[d] > 2 ) {
stencil_lo[d] = -1;
stencil_hi[d] = 1;
stencil_size[d]= 3;
}
}
this->BuildShifts();
};
};
// Need to worry about red-black now
class NonLocalStencilGeometry4D : public NonLocalStencilGeometry {
public:
virtual int DerivedDimSkip(void) { return 0;};
NonLocalStencilGeometry4D(GridCartesian *Coarse,int _hops) : NonLocalStencilGeometry(Coarse,_hops,0) { };
virtual ~NonLocalStencilGeometry4D() {};
};
class NonLocalStencilGeometry5D : public NonLocalStencilGeometry {
public:
virtual int DerivedDimSkip(void) { return 1; };
NonLocalStencilGeometry5D(GridCartesian *Coarse,int _hops) : NonLocalStencilGeometry(Coarse,_hops,1) { };
virtual ~NonLocalStencilGeometry5D() {};
};
/*
* Bunch of different options classes
*/
class NextToNextToNextToNearestStencilGeometry4D : public NonLocalStencilGeometry4D {
public:
NextToNextToNextToNearestStencilGeometry4D(GridCartesian *Coarse) : NonLocalStencilGeometry4D(Coarse,4)
{
};
};
class NextToNextToNextToNearestStencilGeometry5D : public NonLocalStencilGeometry5D {
public:
NextToNextToNextToNearestStencilGeometry5D(GridCartesian *Coarse) : NonLocalStencilGeometry5D(Coarse,4)
{
};
};
class NextToNearestStencilGeometry4D : public NonLocalStencilGeometry4D {
public:
NextToNearestStencilGeometry4D(GridCartesian *Coarse) : NonLocalStencilGeometry4D(Coarse,2)
{
};
};
class NextToNearestStencilGeometry5D : public NonLocalStencilGeometry5D {
public:
NextToNearestStencilGeometry5D(GridCartesian *Coarse) : NonLocalStencilGeometry5D(Coarse,2)
{
};
};
class NearestStencilGeometry4D : public NonLocalStencilGeometry4D {
public:
NearestStencilGeometry4D(GridCartesian *Coarse) : NonLocalStencilGeometry4D(Coarse,1)
{
};
};
class NearestStencilGeometry5D : public NonLocalStencilGeometry5D {
public:
NearestStencilGeometry5D(GridCartesian *Coarse) : NonLocalStencilGeometry5D(Coarse,1)
{
};
};
NAMESPACE_END(Grid);
-34
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@@ -1,34 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: Grid/algorithms/multigrid/MultiGrid.h
Copyright (C) 2023
Author: Peter Boyle <pboyle@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
#include <Grid/algorithms/multigrid/Aggregates.h>
#include <Grid/algorithms/multigrid/Geometry.h>
#include <Grid/algorithms/multigrid/CoarsenedMatrix.h>
#include <Grid/algorithms/multigrid/GeneralCoarsenedMatrix.h>
#include <Grid/algorithms/multigrid/GeneralCoarsenedMatrixMultiRHS.h>
-240
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@@ -1,240 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/AlignedAllocator.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
template<typename _Tp>
class alignedAllocator {
public:
typedef std::size_t size_type;
typedef std::ptrdiff_t difference_type;
typedef _Tp* pointer;
typedef const _Tp* const_pointer;
typedef _Tp& reference;
typedef const _Tp& const_reference;
typedef _Tp value_type;
template<typename _Tp1> struct rebind { typedef alignedAllocator<_Tp1> other; };
alignedAllocator() throw() { }
alignedAllocator(const alignedAllocator&) throw() { }
template<typename _Tp1> alignedAllocator(const alignedAllocator<_Tp1>&) throw() { }
~alignedAllocator() throw() { }
pointer address(reference __x) const { return &__x; }
size_type max_size() const throw() { return size_t(-1) / sizeof(_Tp); }
pointer allocate(size_type __n, const void* _p= 0)
{
size_type bytes = __n*sizeof(_Tp);
profilerAllocate(bytes);
_Tp *ptr = (_Tp*) MemoryManager::CpuAllocate(bytes);
if ( (_Tp*)ptr == (_Tp *) NULL ) {
printf("Grid CPU Allocator got NULL for %lu bytes\n",(unsigned long) bytes );
}
assert( ( (_Tp*)ptr != (_Tp *)NULL ) );
return ptr;
}
void deallocate(pointer __p, size_type __n)
{
size_type bytes = __n * sizeof(_Tp);
profilerFree(bytes);
MemoryManager::CpuFree((void *)__p,bytes);
}
// FIXME: hack for the copy constructor: it must be avoided to avoid single thread loop
void construct(pointer __p, const _Tp& __val) { assert(0);};
void construct(pointer __p) { };
void destroy(pointer __p) { };
};
template<typename _Tp> inline bool operator==(const alignedAllocator<_Tp>&, const alignedAllocator<_Tp>&){ return true; }
template<typename _Tp> inline bool operator!=(const alignedAllocator<_Tp>&, const alignedAllocator<_Tp>&){ return false; }
//////////////////////////////////////////////////////////////////////////////////////
// Unified virtual memory
//////////////////////////////////////////////////////////////////////////////////////
template<typename _Tp>
class uvmAllocator {
public:
typedef std::size_t size_type;
typedef std::ptrdiff_t difference_type;
typedef _Tp* pointer;
typedef const _Tp* const_pointer;
typedef _Tp& reference;
typedef const _Tp& const_reference;
typedef _Tp value_type;
template<typename _Tp1> struct rebind { typedef uvmAllocator<_Tp1> other; };
uvmAllocator() throw() { }
uvmAllocator(const uvmAllocator&) throw() { }
template<typename _Tp1> uvmAllocator(const uvmAllocator<_Tp1>&) throw() { }
~uvmAllocator() throw() { }
pointer address(reference __x) const { return &__x; }
size_type max_size() const throw() { return size_t(-1) / sizeof(_Tp); }
pointer allocate(size_type __n, const void* _p= 0)
{
size_type bytes = __n*sizeof(_Tp);
profilerAllocate(bytes);
_Tp *ptr = (_Tp*) MemoryManager::SharedAllocate(bytes);
if ( (_Tp*)ptr == (_Tp *) NULL ) {
printf("Grid Shared Allocator got NULL for %lu bytes\n",(unsigned long) bytes );
}
assert( ( (_Tp*)ptr != (_Tp *)NULL ) );
return ptr;
}
void deallocate(pointer __p, size_type __n)
{
size_type bytes = __n * sizeof(_Tp);
profilerFree(bytes);
MemoryManager::SharedFree((void *)__p,bytes);
}
void construct(pointer __p, const _Tp& __val) { new((void *)__p) _Tp(__val); };
void construct(pointer __p) { };
void destroy(pointer __p) { };
};
template<typename _Tp> inline bool operator==(const uvmAllocator<_Tp>&, const uvmAllocator<_Tp>&){ return true; }
template<typename _Tp> inline bool operator!=(const uvmAllocator<_Tp>&, const uvmAllocator<_Tp>&){ return false; }
////////////////////////////////////////////////////////////////////////////////
// Device memory
////////////////////////////////////////////////////////////////////////////////
template<typename _Tp>
class devAllocator {
public:
typedef std::size_t size_type;
typedef std::ptrdiff_t difference_type;
typedef _Tp* pointer;
typedef const _Tp* const_pointer;
typedef _Tp& reference;
typedef const _Tp& const_reference;
typedef _Tp value_type;
template<typename _Tp1> struct rebind { typedef devAllocator<_Tp1> other; };
devAllocator() throw() { }
devAllocator(const devAllocator&) throw() { }
template<typename _Tp1> devAllocator(const devAllocator<_Tp1>&) throw() { }
~devAllocator() throw() { }
pointer address(reference __x) const { return &__x; }
size_type max_size() const throw() { return size_t(-1) / sizeof(_Tp); }
pointer allocate(size_type __n, const void* _p= 0)
{
size_type bytes = __n*sizeof(_Tp);
profilerAllocate(bytes);
_Tp *ptr = (_Tp*) MemoryManager::AcceleratorAllocate(bytes);
if ( (_Tp*)ptr == (_Tp *) NULL ) {
printf("Grid Device Allocator got NULL for %lu bytes\n",(unsigned long) bytes );
}
assert( ( (_Tp*)ptr != (_Tp *)NULL ) );
return ptr;
}
void deallocate(pointer __p, size_type __n)
{
size_type bytes = __n * sizeof(_Tp);
profilerFree(bytes);
MemoryManager::AcceleratorFree((void *)__p,bytes);
}
void construct(pointer __p, const _Tp& __val) { };
void construct(pointer __p) { };
void destroy(pointer __p) { };
};
template<typename _Tp> inline bool operator==(const devAllocator<_Tp>&, const devAllocator<_Tp>&){ return true; }
template<typename _Tp> inline bool operator!=(const devAllocator<_Tp>&, const devAllocator<_Tp>&){ return false; }
////////////////////////////////////////////////////////////////////////////////
// Template typedefs
////////////////////////////////////////////////////////////////////////////////
#ifdef ACCELERATOR_CSHIFT
// Cshift on device
template<class T> using cshiftAllocator = devAllocator<T>;
#else
// Cshift on host
template<class T> using cshiftAllocator = std::allocator<T>;
#endif
template<class T> using Vector = std::vector<T,uvmAllocator<T> >;
template<class T> using stencilVector = std::vector<T,alignedAllocator<T> >;
template<class T> using commVector = std::vector<T,devAllocator<T> >;
template<class T> using deviceVector = std::vector<T,devAllocator<T> >;
template<class T> using cshiftVector = std::vector<T,cshiftAllocator<T> >;
/*
template<class T> class vecView
{
protected:
T * data;
uint64_t size;
ViewMode mode;
void * cpu_ptr;
public:
accelerator_inline T & operator[](size_t i) const { return this->data[i]; };
vecView(std::vector<T> &refer_to_me,ViewMode _mode)
{
cpu_ptr = &refer_to_me[0];
size = refer_to_me.size();
mode = _mode;
data =(T *) MemoryManager::ViewOpen(cpu_ptr,
size*sizeof(T),
mode,
AdviseDefault);
}
void ViewClose(void)
{ // Inform the manager
MemoryManager::ViewClose(this->cpu_ptr,this->mode);
}
};
template<class T> vecView<T> VectorView(std::vector<T> &vec,ViewMode _mode)
{
vecView<T> ret(vec,_mode); // does the open
return ret; // must be closed
}
// Little autoscope assister
template<class View>
class VectorViewCloser
{
View v; // Take a copy of view and call view close when I go out of scope automatically
public:
VectorViewCloser(View &_v) : v(_v) {};
~VectorViewCloser() { auto ptr = v.cpu_ptr; v.ViewClose(); MemoryManager::NotifyDeletion(ptr);}
};
#define autoVecView(v_v,v,mode) \
auto v_v = VectorView(v,mode); \
ViewCloser<decltype(v_v)> _autoView##v_v(v_v);
*/
NAMESPACE_END(Grid);
-4
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@@ -1,4 +0,0 @@
#pragma once
#include <Grid/allocator/MemoryStats.h>
#include <Grid/allocator/MemoryManager.h>
#include <Grid/allocator/AlignedAllocator.h>
-362
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@@ -1,362 +0,0 @@
#include <Grid/GridCore.h>
NAMESPACE_BEGIN(Grid);
/*Allocation types, saying which pointer cache should be used*/
#define Cpu (0)
#define CpuHuge (1)
#define CpuSmall (2)
#define Acc (3)
#define AccHuge (4)
#define AccSmall (5)
#define Shared (6)
#define SharedHuge (7)
#define SharedSmall (8)
#undef GRID_MM_VERBOSE
uint64_t total_shared;
uint64_t total_device;
uint64_t total_host;;
#if defined(__has_feature)
#if __has_feature(leak_sanitizer)
#define ASAN_LEAK_CHECK
#endif
#endif
#ifdef ASAN_LEAK_CHECK
#include <sanitizer/asan_interface.h>
#include <sanitizer/common_interface_defs.h>
#include <sanitizer/lsan_interface.h>
#define LEAK_CHECK(A) { __lsan_do_recoverable_leak_check(); }
#else
#define LEAK_CHECK(A) { }
#endif
void MemoryManager::DisplayMallinfo(void)
{
#ifdef __linux__
struct mallinfo mi; // really want mallinfo2, but glibc version isn't uniform
mi = mallinfo();
std::cout << "MemoryManager: Total non-mmapped bytes (arena): "<< (size_t)mi.arena<<std::endl;
std::cout << "MemoryManager: # of free chunks (ordblks): "<< (size_t)mi.ordblks<<std::endl;
std::cout << "MemoryManager: # of free fastbin blocks (smblks): "<< (size_t)mi.smblks<<std::endl;
std::cout << "MemoryManager: # of mapped regions (hblks): "<< (size_t)mi.hblks<<std::endl;
std::cout << "MemoryManager: Bytes in mapped regions (hblkhd): "<< (size_t)mi.hblkhd<<std::endl;
std::cout << "MemoryManager: Max. total allocated space (usmblks): "<< (size_t)mi.usmblks<<std::endl;
std::cout << "MemoryManager: Free bytes held in fastbins (fsmblks): "<< (size_t)mi.fsmblks<<std::endl;
std::cout << "MemoryManager: Total allocated space (uordblks): "<< (size_t)mi.uordblks<<std::endl;
std::cout << "MemoryManager: Total free space (fordblks): "<< (size_t)mi.fordblks<<std::endl;
std::cout << "MemoryManager: Topmost releasable block (keepcost): "<< (size_t)mi.keepcost<<std::endl;
#endif
LEAK_CHECK();
}
void MemoryManager::PrintBytes(void)
{
std::cout << " MemoryManager : ------------------------------------ "<<std::endl;
std::cout << " MemoryManager : PrintBytes "<<std::endl;
std::cout << " MemoryManager : ------------------------------------ "<<std::endl;
std::cout << " MemoryManager : "<<(total_shared>>20)<<" shared Mbytes "<<std::endl;
std::cout << " MemoryManager : "<<(total_device>>20)<<" accelerator Mbytes "<<std::endl;
std::cout << " MemoryManager : "<<(total_host>>20) <<" cpu Mbytes "<<std::endl;
uint64_t cacheBytes;
cacheBytes = CacheBytes[Cpu];
std::cout << " MemoryManager : "<<(cacheBytes>>20) <<" cpu cache Mbytes "<<std::endl;
cacheBytes = CacheBytes[Acc];
std::cout << " MemoryManager : "<<(cacheBytes>>20) <<" acc cache Mbytes "<<std::endl;
cacheBytes = CacheBytes[Shared];
std::cout << " MemoryManager : "<<(cacheBytes>>20) <<" shared cache Mbytes "<<std::endl;
#ifdef GRID_CUDA
cuda_mem();
#endif
DisplayMallinfo();
}
uint64_t MemoryManager::DeviceCacheBytes() { return CacheBytes[Acc] + CacheBytes[AccHuge] + CacheBytes[AccSmall]; }
uint64_t MemoryManager::HostCacheBytes() { return CacheBytes[Cpu] + CacheBytes[CpuHuge] + CacheBytes[CpuSmall]; }
//////////////////////////////////////////////////////////////////////
// Data tables for recently freed pooiniter caches
//////////////////////////////////////////////////////////////////////
MemoryManager::AllocationCacheEntry MemoryManager::Entries[MemoryManager::NallocType][MemoryManager::NallocCacheMax];
int MemoryManager::Victim[MemoryManager::NallocType];
int MemoryManager::Ncache[MemoryManager::NallocType] = { 2, 0, 8, 8, 0, 16, 8, 0, 16 };
uint64_t MemoryManager::CacheBytes[MemoryManager::NallocType];
//////////////////////////////////////////////////////////////////////
// Actual allocation and deallocation utils
//////////////////////////////////////////////////////////////////////
void *MemoryManager::AcceleratorAllocate(size_t bytes)
{
total_device+=bytes;
void *ptr = (void *) Lookup(bytes,Acc);
if ( ptr == (void *) NULL ) {
ptr = (void *) acceleratorAllocDevice(bytes);
}
#ifdef GRID_MM_VERBOSE
std::cout <<"AcceleratorAllocate "<<std::endl;
PrintBytes();
#endif
return ptr;
}
void MemoryManager::AcceleratorFree (void *ptr,size_t bytes)
{
total_device-=bytes;
void *__freeme = Insert(ptr,bytes,Acc);
if ( __freeme ) {
acceleratorFreeDevice(__freeme);
}
#ifdef GRID_MM_VERBOSE
std::cout <<"AcceleratorFree "<<std::endl;
PrintBytes();
#endif
}
void *MemoryManager::SharedAllocate(size_t bytes)
{
total_shared+=bytes;
void *ptr = (void *) Lookup(bytes,Shared);
if ( ptr == (void *) NULL ) {
ptr = (void *) acceleratorAllocShared(bytes);
}
#ifdef GRID_MM_VERBOSE
std::cout <<"SharedAllocate "<<std::endl;
PrintBytes();
#endif
return ptr;
}
void MemoryManager::SharedFree (void *ptr,size_t bytes)
{
total_shared-=bytes;
void *__freeme = Insert(ptr,bytes,Shared);
if ( __freeme ) {
acceleratorFreeShared(__freeme);
}
#ifdef GRID_MM_VERBOSE
std::cout <<"SharedFree "<<std::endl;
PrintBytes();
#endif
}
#ifdef GRID_UVM
void *MemoryManager::CpuAllocate(size_t bytes)
{
total_host+=bytes;
void *ptr = (void *) Lookup(bytes,Cpu);
if ( ptr == (void *) NULL ) {
ptr = (void *) acceleratorAllocShared(bytes);
}
#ifdef GRID_MM_VERBOSE
std::cout <<"CpuAllocate "<<std::endl;
PrintBytes();
#endif
return ptr;
}
void MemoryManager::CpuFree (void *_ptr,size_t bytes)
{
total_host-=bytes;
NotifyDeletion(_ptr);
void *__freeme = Insert(_ptr,bytes,Cpu);
if ( __freeme ) {
acceleratorFreeShared(__freeme);
}
#ifdef GRID_MM_VERBOSE
std::cout <<"CpuFree "<<std::endl;
PrintBytes();
#endif
}
#else
void *MemoryManager::CpuAllocate(size_t bytes)
{
total_host+=bytes;
void *ptr = (void *) Lookup(bytes,Cpu);
if ( ptr == (void *) NULL ) {
ptr = (void *) acceleratorAllocCpu(bytes);
}
#ifdef GRID_MM_VERBOSE
std::cout <<"CpuAllocate "<<std::endl;
PrintBytes();
#endif
return ptr;
}
void MemoryManager::CpuFree (void *_ptr,size_t bytes)
{
total_host-=bytes;
NotifyDeletion(_ptr);
void *__freeme = Insert(_ptr,bytes,Cpu);
if ( __freeme ) {
acceleratorFreeCpu(__freeme);
}
#ifdef GRID_MM_VERBOSE
std::cout <<"CpuFree "<<std::endl;
PrintBytes();
#endif
}
#endif
//////////////////////////////////////////
// call only once
//////////////////////////////////////////
void MemoryManager::Init(void)
{
char * str;
int Nc;
str= getenv("GRID_ALLOC_NCACHE_LARGE");
if ( str ) {
Nc = atoi(str);
if ( (Nc>=0) && (Nc < NallocCacheMax)) {
Ncache[Cpu]=Nc;
Ncache[Acc]=Nc;
Ncache[Shared]=Nc;
}
}
str= getenv("GRID_ALLOC_NCACHE_HUGE");
if ( str ) {
Nc = atoi(str);
if ( (Nc>=0) && (Nc < NallocCacheMax)) {
Ncache[CpuHuge]=Nc;
Ncache[AccHuge]=Nc;
Ncache[SharedHuge]=Nc;
}
}
str= getenv("GRID_ALLOC_NCACHE_SMALL");
if ( str ) {
Nc = atoi(str);
if ( (Nc>=0) && (Nc < NallocCacheMax)) {
Ncache[CpuSmall]=Nc;
Ncache[AccSmall]=Nc;
Ncache[SharedSmall]=Nc;
}
}
}
void MemoryManager::InitMessage(void) {
#ifndef GRID_UVM
std::cout << GridLogMessage << "MemoryManager Cache "<< MemoryManager::DeviceMaxBytes <<" bytes "<<std::endl;
#endif
std::cout << GridLogMessage<< "MemoryManager::Init() setting up"<<std::endl;
#ifdef ALLOCATION_CACHE
std::cout << GridLogMessage<< "MemoryManager::Init() cache pool for recent host allocations: SMALL "<<Ncache[CpuSmall]<<" LARGE "<<Ncache[Cpu]<<" HUGE "<<Ncache[CpuHuge]<<std::endl;
std::cout << GridLogMessage<< "MemoryManager::Init() cache pool for recent device allocations: SMALL "<<Ncache[AccSmall]<<" LARGE "<<Ncache[Acc]<<" Huge "<<Ncache[AccHuge]<<std::endl;
std::cout << GridLogMessage<< "MemoryManager::Init() cache pool for recent shared allocations: SMALL "<<Ncache[SharedSmall]<<" LARGE "<<Ncache[Shared]<<" Huge "<<Ncache[SharedHuge]<<std::endl;
#endif
#ifdef GRID_UVM
std::cout << GridLogMessage<< "MemoryManager::Init() Unified memory space"<<std::endl;
#ifdef GRID_CUDA
std::cout << GridLogMessage<< "MemoryManager::Init() Using cudaMallocManaged"<<std::endl;
#endif
#ifdef GRID_HIP
std::cout << GridLogMessage<< "MemoryManager::Init() Using hipMallocManaged"<<std::endl;
#endif
#ifdef GRID_SYCL
std::cout << GridLogMessage<< "MemoryManager::Init() Using SYCL malloc_shared"<<std::endl;
#endif
#else
std::cout << GridLogMessage<< "MemoryManager::Init() Non unified: Caching accelerator data in dedicated memory"<<std::endl;
#ifdef GRID_CUDA
std::cout << GridLogMessage<< "MemoryManager::Init() Using cudaMalloc"<<std::endl;
#endif
#ifdef GRID_HIP
std::cout << GridLogMessage<< "MemoryManager::Init() Using hipMalloc"<<std::endl;
#endif
#ifdef GRID_SYCL
std::cout << GridLogMessage<< "MemoryManager::Init() Using SYCL malloc_device"<<std::endl;
#endif
#endif
}
void *MemoryManager::Insert(void *ptr,size_t bytes,int type)
{
#ifdef ALLOCATION_CACHE
int cache;
if (bytes < GRID_ALLOC_SMALL_LIMIT) cache = type + 2;
else if (bytes >= GRID_ALLOC_HUGE_LIMIT) cache = type + 1;
else cache = type;
return Insert(ptr,bytes,Entries[cache],Ncache[cache],Victim[cache],CacheBytes[cache]);
#else
return ptr;
#endif
}
void *MemoryManager::Insert(void *ptr,size_t bytes,AllocationCacheEntry *entries,int ncache,int &victim, uint64_t &cacheBytes)
{
#ifdef GRID_OMP
assert(omp_in_parallel()==0);
#endif
if (ncache == 0) return ptr;
void * ret = NULL;
int v = -1;
for(int e=0;e<ncache;e++) {
if ( entries[e].valid==0 ) {
v=e;
break;
}
}
if ( v==-1 ) {
v=victim;
victim = (victim+1)%ncache;
}
if ( entries[v].valid ) {
ret = entries[v].address;
cacheBytes -= entries[v].bytes;
entries[v].valid = 0;
entries[v].address = NULL;
entries[v].bytes = 0;
}
entries[v].address=ptr;
entries[v].bytes =bytes;
entries[v].valid =1;
cacheBytes += bytes;
return ret;
}
void *MemoryManager::Lookup(size_t bytes,int type)
{
#ifdef ALLOCATION_CACHE
int cache;
if (bytes < GRID_ALLOC_SMALL_LIMIT) cache = type + 2;
else if (bytes >= GRID_ALLOC_HUGE_LIMIT) cache = type + 1;
else cache = type;
return Lookup(bytes,Entries[cache],Ncache[cache],CacheBytes[cache]);
#else
return NULL;
#endif
}
void *MemoryManager::Lookup(size_t bytes,AllocationCacheEntry *entries,int ncache,uint64_t & cacheBytes)
{
#ifdef GRID_OMP
assert(omp_in_parallel()==0);
#endif
for(int e=0;e<ncache;e++){
if ( entries[e].valid && ( entries[e].bytes == bytes ) ) {
entries[e].valid = 0;
cacheBytes -= entries[e].bytes;
return entries[e].address;
}
}
return NULL;
}
NAMESPACE_END(Grid);
-227
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@@ -1,227 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/MemoryManager.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
#include <list>
#include <unordered_map>
NAMESPACE_BEGIN(Grid);
// Move control to configure.ac and Config.h?
#define GRID_ALLOC_SMALL_LIMIT (4096)
#define GRID_ALLOC_HUGE_LIMIT (2147483648)
#define STRINGIFY(x) #x
#define TOSTRING(x) STRINGIFY(x)
#define FILE_LINE __FILE__ ":" TOSTRING(__LINE__)
#define AUDIT(a) MemoryManager::Audit(FILE_LINE)
/*Pinning pages is costly*/
////////////////////////////////////////////////////////////////////////////
// Advise the LatticeAccelerator class
////////////////////////////////////////////////////////////////////////////
enum ViewAdvise {
AdviseDefault = 0x0, // Regular data
AdviseInfrequentUse = 0x1 // Advise that the data is used infrequently. This can
// significantly influence performance of bulk storage.
// AdviseTransient = 0x2, // Data will mostly be read. On some architectures
// enables read-only copies of memory to be kept on
// host and device.
// AdviseAcceleratorWriteDiscard = 0x4 // Field will be written in entirety on device
};
////////////////////////////////////////////////////////////////////////////
// View Access Mode
////////////////////////////////////////////////////////////////////////////
enum ViewMode {
AcceleratorRead = 0x01,
AcceleratorWrite = 0x02,
AcceleratorWriteDiscard = 0x04,
CpuRead = 0x08,
CpuWrite = 0x10,
CpuWriteDiscard = 0x10 // same for now
};
struct MemoryStatus {
uint64_t DeviceBytes;
uint64_t DeviceLRUBytes;
uint64_t DeviceMaxBytes;
uint64_t HostToDeviceBytes;
uint64_t DeviceToHostBytes;
uint64_t HostToDeviceXfer;
uint64_t DeviceToHostXfer;
uint64_t DeviceEvictions;
uint64_t DeviceDestroy;
uint64_t DeviceAllocCacheBytes;
uint64_t HostAllocCacheBytes;
};
class MemoryManager {
private:
////////////////////////////////////////////////////////////
// For caching recently freed allocations
////////////////////////////////////////////////////////////
typedef struct {
void *address;
size_t bytes;
int valid;
} AllocationCacheEntry;
static const int NallocCacheMax=128;
static const int NallocType=9;
static AllocationCacheEntry Entries[NallocType][NallocCacheMax];
static int Victim[NallocType];
static int Ncache[NallocType];
static uint64_t CacheBytes[NallocType];
/////////////////////////////////////////////////
// Free pool
/////////////////////////////////////////////////
static void *Insert(void *ptr,size_t bytes,int type) ;
static void *Lookup(size_t bytes,int type) ;
static void *Insert(void *ptr,size_t bytes,AllocationCacheEntry *entries,int ncache,int &victim,uint64_t &cbytes) ;
static void *Lookup(size_t bytes,AllocationCacheEntry *entries,int ncache,uint64_t &cbytes) ;
public:
static void PrintBytes(void);
static void Audit(std::string s);
static void Init(void);
static void InitMessage(void);
static void *AcceleratorAllocate(size_t bytes);
static void AcceleratorFree (void *ptr,size_t bytes);
static void *SharedAllocate(size_t bytes);
static void SharedFree (void *ptr,size_t bytes);
static void *CpuAllocate(size_t bytes);
static void CpuFree (void *ptr,size_t bytes);
////////////////////////////////////////////////////////
// Footprint tracking
////////////////////////////////////////////////////////
static uint64_t DeviceBytes;
static uint64_t DeviceLRUBytes;
static uint64_t DeviceMaxBytes;
static uint64_t HostToDeviceBytes;
static uint64_t DeviceToHostBytes;
static uint64_t HostToDeviceXfer;
static uint64_t DeviceToHostXfer;
static uint64_t DeviceEvictions;
static uint64_t DeviceDestroy;
static uint64_t DeviceCacheBytes();
static uint64_t HostCacheBytes();
static MemoryStatus GetFootprint(void) {
MemoryStatus stat;
stat.DeviceBytes = DeviceBytes;
stat.DeviceLRUBytes = DeviceLRUBytes;
stat.DeviceMaxBytes = DeviceMaxBytes;
stat.HostToDeviceBytes = HostToDeviceBytes;
stat.DeviceToHostBytes = DeviceToHostBytes;
stat.HostToDeviceXfer = HostToDeviceXfer;
stat.DeviceToHostXfer = DeviceToHostXfer;
stat.DeviceEvictions = DeviceEvictions;
stat.DeviceDestroy = DeviceDestroy;
stat.DeviceAllocCacheBytes = DeviceCacheBytes();
stat.HostAllocCacheBytes = HostCacheBytes();
return stat;
};
private:
#ifndef GRID_UVM
//////////////////////////////////////////////////////////////////////
// Data tables for ViewCache
//////////////////////////////////////////////////////////////////////
typedef std::list<uint64_t> LRU_t;
typedef typename LRU_t::iterator LRUiterator;
typedef struct {
int LRU_valid;
LRUiterator LRU_entry;
uint64_t CpuPtr;
uint64_t AccPtr;
size_t bytes;
uint32_t transient;
uint32_t state;
uint32_t accLock;
uint32_t cpuLock;
} AcceleratorViewEntry;
typedef std::unordered_map<uint64_t,AcceleratorViewEntry> AccViewTable_t;
typedef typename AccViewTable_t::iterator AccViewTableIterator ;
static AccViewTable_t AccViewTable;
static LRU_t LRU;
/////////////////////////////////////////////////
// Device motion
/////////////////////////////////////////////////
static void Create(uint64_t CpuPtr,size_t bytes,ViewMode mode,ViewAdvise hint);
static void EvictVictims(uint64_t bytes); // Frees up <bytes>
static void Evict(AcceleratorViewEntry &AccCache);
static void Flush(AcceleratorViewEntry &AccCache);
static void Clone(AcceleratorViewEntry &AccCache);
static void AccDiscard(AcceleratorViewEntry &AccCache);
static void CpuDiscard(AcceleratorViewEntry &AccCache);
// static void LRUupdate(AcceleratorViewEntry &AccCache);
static void LRUinsert(AcceleratorViewEntry &AccCache);
static void LRUremove(AcceleratorViewEntry &AccCache);
// manage entries in the table
static int EntryPresent(uint64_t CpuPtr);
static void EntryCreate(uint64_t CpuPtr,size_t bytes,ViewMode mode,ViewAdvise hint);
static void EntryErase (uint64_t CpuPtr);
static AccViewTableIterator EntryLookup(uint64_t CpuPtr);
static void EntrySet (uint64_t CpuPtr,AcceleratorViewEntry &entry);
static void AcceleratorViewClose(uint64_t AccPtr);
static uint64_t AcceleratorViewOpen(uint64_t CpuPtr,size_t bytes,ViewMode mode,ViewAdvise hint);
static void CpuViewClose(uint64_t Ptr);
static uint64_t CpuViewOpen(uint64_t CpuPtr,size_t bytes,ViewMode mode,ViewAdvise hint);
#endif
public:
static void DisplayMallinfo(void);
static void NotifyDeletion(void * CpuPtr);
static void Print(void);
static void PrintAll(void);
static void PrintState( void* CpuPtr);
static int isOpen (void* CpuPtr);
static void ViewClose(void* CpuPtr,ViewMode mode);
static void *ViewOpen (void* CpuPtr,size_t bytes,ViewMode mode,ViewAdvise hint);
};
NAMESPACE_END(Grid);
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#include <Grid/GridCore.h>
#ifndef GRID_UVM
#warning "Using explicit device memory copies"
NAMESPACE_BEGIN(Grid);
#define MAXLINE 512
static char print_buffer [ MAXLINE ];
#define mprintf(...) snprintf (print_buffer,MAXLINE, __VA_ARGS__ ); std::cout << GridLogMemory << print_buffer;
#define dprintf(...) snprintf (print_buffer,MAXLINE, __VA_ARGS__ ); std::cout << GridLogDebug << print_buffer;
//#define dprintf(...)
////////////////////////////////////////////////////////////
// For caching copies of data on device
////////////////////////////////////////////////////////////
MemoryManager::AccViewTable_t MemoryManager::AccViewTable;
MemoryManager::LRU_t MemoryManager::LRU;
////////////////////////////////////////////////////////
// Footprint tracking
////////////////////////////////////////////////////////
uint64_t MemoryManager::DeviceBytes;
uint64_t MemoryManager::DeviceLRUBytes;
uint64_t MemoryManager::DeviceMaxBytes = 1024*1024*128;
uint64_t MemoryManager::HostToDeviceBytes;
uint64_t MemoryManager::DeviceToHostBytes;
uint64_t MemoryManager::HostToDeviceXfer;
uint64_t MemoryManager::DeviceToHostXfer;
uint64_t MemoryManager::DeviceEvictions;
uint64_t MemoryManager::DeviceDestroy;
////////////////////////////////////
// Priority ordering for unlocked entries
// Empty
// CpuDirty
// Consistent
// AccDirty
////////////////////////////////////
#define Empty (0x0) /*Entry unoccupied */
#define CpuDirty (0x1) /*CPU copy is golden, Acc buffer MAY not be allocated*/
#define Consistent (0x2) /*ACC copy AND CPU copy are valid */
#define AccDirty (0x4) /*ACC copy is golden */
#define EvictNext (0x8) /*Priority for eviction*/
/////////////////////////////////////////////////
// Mechanics of data table maintenance
/////////////////////////////////////////////////
int MemoryManager::EntryPresent(uint64_t CpuPtr)
{
if(AccViewTable.empty()) return 0;
auto count = AccViewTable.count(CpuPtr); assert((count==0)||(count==1));
return count;
}
void MemoryManager::EntryCreate(uint64_t CpuPtr,size_t bytes,ViewMode mode,ViewAdvise hint)
{
assert(!EntryPresent(CpuPtr));
AcceleratorViewEntry AccCache;
AccCache.CpuPtr = CpuPtr;
AccCache.AccPtr = (uint64_t)NULL;
AccCache.bytes = bytes;
AccCache.state = CpuDirty;
AccCache.LRU_valid=0;
AccCache.transient=0;
AccCache.accLock=0;
AccCache.cpuLock=0;
AccViewTable[CpuPtr] = AccCache;
}
MemoryManager::AccViewTableIterator MemoryManager::EntryLookup(uint64_t CpuPtr)
{
assert(EntryPresent(CpuPtr));
auto AccCacheIterator = AccViewTable.find(CpuPtr);
assert(AccCacheIterator!=AccViewTable.end());
return AccCacheIterator;
}
void MemoryManager::EntryErase(uint64_t CpuPtr)
{
auto AccCache = EntryLookup(CpuPtr);
AccViewTable.erase(CpuPtr);
}
void MemoryManager::LRUinsert(AcceleratorViewEntry &AccCache)
{
assert(AccCache.LRU_valid==0);
if (AccCache.transient) {
LRU.push_back(AccCache.CpuPtr);
AccCache.LRU_entry = --LRU.end();
} else {
LRU.push_front(AccCache.CpuPtr);
AccCache.LRU_entry = LRU.begin();
}
AccCache.LRU_valid = 1;
DeviceLRUBytes+=AccCache.bytes;
}
void MemoryManager::LRUremove(AcceleratorViewEntry &AccCache)
{
assert(AccCache.LRU_valid==1);
LRU.erase(AccCache.LRU_entry);
AccCache.LRU_valid = 0;
DeviceLRUBytes-=AccCache.bytes;
}
/////////////////////////////////////////////////
// Accelerator cache motion & consistency logic
/////////////////////////////////////////////////
void MemoryManager::AccDiscard(AcceleratorViewEntry &AccCache)
{
///////////////////////////////////////////////////////////
// Remove from Accelerator, remove entry, without flush
// Cannot be locked. If allocated Must be in LRU pool.
///////////////////////////////////////////////////////////
assert(AccCache.state!=Empty);
dprintf("MemoryManager: Discard(%lx) %lx\n",(uint64_t)AccCache.CpuPtr,(uint64_t)AccCache.AccPtr);
assert(AccCache.accLock==0);
assert(AccCache.cpuLock==0);
assert(AccCache.CpuPtr!=(uint64_t)NULL);
if(AccCache.AccPtr) {
AcceleratorFree((void *)AccCache.AccPtr,AccCache.bytes);
DeviceDestroy++;
DeviceBytes -=AccCache.bytes;
LRUremove(AccCache);
AccCache.AccPtr=(uint64_t) NULL;
dprintf("MemoryManager: Free(%lx) LRU %ld Total %ld\n",(uint64_t)AccCache.AccPtr,DeviceLRUBytes,DeviceBytes);
}
uint64_t CpuPtr = AccCache.CpuPtr;
EntryErase(CpuPtr);
}
void MemoryManager::Evict(AcceleratorViewEntry &AccCache)
{
///////////////////////////////////////////////////////////////////////////
// Make CPU consistent, remove from Accelerator, remove from LRU, LEAVE CPU only entry
// Cannot be acclocked. If allocated must be in LRU pool.
//
// Nov 2022... Felix issue: Allocating two CpuPtrs, can have an entry in LRU-q with CPUlock.
// and require to evict the AccPtr copy. Eviction was a mistake in CpuViewOpen
// but there is a weakness where CpuLock entries are attempted for erase
// Take these OUT LRU queue when CPU locked?
// Cannot take out the table as cpuLock data is important.
///////////////////////////////////////////////////////////////////////////
assert(AccCache.state!=Empty);
mprintf("MemoryManager: Evict CpuPtr %lx AccPtr %lx cpuLock %ld accLock %ld\n",
(uint64_t)AccCache.CpuPtr,(uint64_t)AccCache.AccPtr,
(uint64_t)AccCache.cpuLock,(uint64_t)AccCache.accLock);
if (AccCache.accLock!=0) return;
if (AccCache.cpuLock!=0) return;
if(AccCache.state==AccDirty) {
Flush(AccCache);
}
if(AccCache.AccPtr) {
AcceleratorFree((void *)AccCache.AccPtr,AccCache.bytes);
LRUremove(AccCache);
AccCache.AccPtr=(uint64_t)NULL;
AccCache.state=CpuDirty; // CPU primary now
DeviceBytes -=AccCache.bytes;
dprintf("MemoryManager: Free(AccPtr %lx) footprint now %ld \n",(uint64_t)AccCache.AccPtr,DeviceBytes);
}
// uint64_t CpuPtr = AccCache.CpuPtr;
DeviceEvictions++;
// EntryErase(CpuPtr);
}
void MemoryManager::Flush(AcceleratorViewEntry &AccCache)
{
assert(AccCache.state==AccDirty);
assert(AccCache.cpuLock==0);
assert(AccCache.accLock==0);
assert(AccCache.AccPtr!=(uint64_t)NULL);
assert(AccCache.CpuPtr!=(uint64_t)NULL);
acceleratorCopyFromDevice((void *)AccCache.AccPtr,(void *)AccCache.CpuPtr,AccCache.bytes);
mprintf("MemoryManager: acceleratorCopyFromDevice Flush AccPtr %lx -> CpuPtr %lx\n",(uint64_t)AccCache.AccPtr,(uint64_t)AccCache.CpuPtr); fflush(stdout);
DeviceToHostBytes+=AccCache.bytes;
DeviceToHostXfer++;
AccCache.state=Consistent;
}
void MemoryManager::Clone(AcceleratorViewEntry &AccCache)
{
assert(AccCache.state==CpuDirty);
assert(AccCache.cpuLock==0);
assert(AccCache.accLock==0);
assert(AccCache.CpuPtr!=(uint64_t)NULL);
if(AccCache.AccPtr==(uint64_t)NULL){
AccCache.AccPtr=(uint64_t)AcceleratorAllocate(AccCache.bytes);
DeviceBytes+=AccCache.bytes;
}
mprintf("MemoryManager: acceleratorCopyToDevice Clone AccPtr %lx <- CpuPtr %lx\n",(uint64_t)AccCache.AccPtr,(uint64_t)AccCache.CpuPtr); fflush(stdout);
acceleratorCopyToDevice((void *)AccCache.CpuPtr,(void *)AccCache.AccPtr,AccCache.bytes);
HostToDeviceBytes+=AccCache.bytes;
HostToDeviceXfer++;
AccCache.state=Consistent;
}
void MemoryManager::CpuDiscard(AcceleratorViewEntry &AccCache)
{
assert(AccCache.state!=Empty);
assert(AccCache.cpuLock==0);
assert(AccCache.accLock==0);
assert(AccCache.CpuPtr!=(uint64_t)NULL);
if(AccCache.AccPtr==(uint64_t)NULL){
AccCache.AccPtr=(uint64_t)AcceleratorAllocate(AccCache.bytes);
DeviceBytes+=AccCache.bytes;
}
AccCache.state=AccDirty;
}
/////////////////////////////////////////////////////////////////////////////////
// View management
/////////////////////////////////////////////////////////////////////////////////
void MemoryManager::ViewClose(void* Ptr,ViewMode mode)
{
if( (mode==AcceleratorRead)||(mode==AcceleratorWrite)||(mode==AcceleratorWriteDiscard) ){
dprintf("AcceleratorViewClose %lx\n",(uint64_t)Ptr);
AcceleratorViewClose((uint64_t)Ptr);
} else if( (mode==CpuRead)||(mode==CpuWrite)){
CpuViewClose((uint64_t)Ptr);
} else {
assert(0);
}
}
void *MemoryManager::ViewOpen(void* _CpuPtr,size_t bytes,ViewMode mode,ViewAdvise hint)
{
uint64_t CpuPtr = (uint64_t)_CpuPtr;
if( (mode==AcceleratorRead)||(mode==AcceleratorWrite)||(mode==AcceleratorWriteDiscard) ){
dprintf("AcceleratorViewOpen %lx\n",(uint64_t)CpuPtr);
return (void *) AcceleratorViewOpen(CpuPtr,bytes,mode,hint);
} else if( (mode==CpuRead)||(mode==CpuWrite)){
return (void *)CpuViewOpen(CpuPtr,bytes,mode,hint);
} else {
assert(0);
return NULL;
}
}
void MemoryManager::EvictVictims(uint64_t bytes)
{
assert(bytes<DeviceMaxBytes);
while(bytes+DeviceLRUBytes > DeviceMaxBytes){
if ( DeviceLRUBytes > 0){
assert(LRU.size()>0);
uint64_t victim = LRU.back(); // From the LRU
auto AccCacheIterator = EntryLookup(victim);
auto & AccCache = AccCacheIterator->second;
Evict(AccCache);
} else {
return;
}
}
}
uint64_t MemoryManager::AcceleratorViewOpen(uint64_t CpuPtr,size_t bytes,ViewMode mode,ViewAdvise hint)
{
////////////////////////////////////////////////////////////////////////////
// Find if present, otherwise get or force an empty
////////////////////////////////////////////////////////////////////////////
if ( EntryPresent(CpuPtr)==0 ){
EntryCreate(CpuPtr,bytes,mode,hint);
}
auto AccCacheIterator = EntryLookup(CpuPtr);
auto & AccCache = AccCacheIterator->second;
if (!AccCache.AccPtr) {
EvictVictims(bytes);
}
assert((mode==AcceleratorRead)||(mode==AcceleratorWrite)||(mode==AcceleratorWriteDiscard));
assert(AccCache.cpuLock==0); // Programming error
if(AccCache.state!=Empty) {
dprintf("ViewOpen found entry %lx %lx : %ld %ld accLock %ld\n",
(uint64_t)AccCache.CpuPtr,
(uint64_t)CpuPtr,
(uint64_t)AccCache.bytes,
(uint64_t)bytes,
(uint64_t)AccCache.accLock);
assert(AccCache.CpuPtr == CpuPtr);
assert(AccCache.bytes ==bytes);
}
/*
* State transitions and actions
*
* Action State StateNext Flush Clone
*
* AccRead Empty Consistent - Y
* AccWrite Empty AccDirty - Y
* AccRead CpuDirty Consistent - Y
* AccWrite CpuDirty AccDirty - Y
* AccRead Consistent Consistent - -
* AccWrite Consistent AccDirty - -
* AccRead AccDirty AccDirty - -
* AccWrite AccDirty AccDirty - -
*/
if(AccCache.state==Empty) {
assert(AccCache.LRU_valid==0);
AccCache.CpuPtr = CpuPtr;
AccCache.AccPtr = (uint64_t)NULL;
AccCache.bytes = bytes;
AccCache.state = CpuDirty; // Cpu starts primary
if(mode==AcceleratorWriteDiscard){
CpuDiscard(AccCache);
AccCache.state = AccDirty; // Empty + AcceleratorWrite=> AccDirty
} else if(mode==AcceleratorWrite){
Clone(AccCache);
AccCache.state = AccDirty; // Empty + AcceleratorWrite=> AccDirty
} else {
Clone(AccCache);
AccCache.state = Consistent; // Empty + AccRead => Consistent
}
AccCache.accLock= 1;
dprintf("Copied Empty entry into device accLock= %d\n",AccCache.accLock);
} else if(AccCache.state==CpuDirty ){
if(mode==AcceleratorWriteDiscard) {
CpuDiscard(AccCache);
AccCache.state = AccDirty; // CpuDirty + AcceleratorWrite=> AccDirty
} else if(mode==AcceleratorWrite) {
Clone(AccCache);
AccCache.state = AccDirty; // CpuDirty + AcceleratorWrite=> AccDirty
} else {
Clone(AccCache);
AccCache.state = Consistent; // CpuDirty + AccRead => Consistent
}
AccCache.accLock++;
dprintf("CpuDirty entry into device ++accLock= %d\n",AccCache.accLock);
} else if(AccCache.state==Consistent) {
if((mode==AcceleratorWrite)||(mode==AcceleratorWriteDiscard))
AccCache.state = AccDirty; // Consistent + AcceleratorWrite=> AccDirty
else
AccCache.state = Consistent; // Consistent + AccRead => Consistent
AccCache.accLock++;
dprintf("Consistent entry into device ++accLock= %d\n",AccCache.accLock);
} else if(AccCache.state==AccDirty) {
if((mode==AcceleratorWrite)||(mode==AcceleratorWriteDiscard))
AccCache.state = AccDirty; // AccDirty + AcceleratorWrite=> AccDirty
else
AccCache.state = AccDirty; // AccDirty + AccRead => AccDirty
AccCache.accLock++;
dprintf("AccDirty entry ++accLock= %d\n",AccCache.accLock);
} else {
assert(0);
}
assert(AccCache.accLock>0);
// If view is opened on device must remove from LRU
if(AccCache.LRU_valid==1){
// must possibly remove from LRU as now locked on GPU
dprintf("AccCache entry removed from LRU \n");
LRUremove(AccCache);
}
int transient =hint;
AccCache.transient= transient? EvictNext : 0;
return AccCache.AccPtr;
}
////////////////////////////////////
// look up & decrement lock count
////////////////////////////////////
void MemoryManager::AcceleratorViewClose(uint64_t CpuPtr)
{
auto AccCacheIterator = EntryLookup(CpuPtr);
auto & AccCache = AccCacheIterator->second;
assert(AccCache.cpuLock==0);
assert(AccCache.accLock>0);
AccCache.accLock--;
// Move to LRU queue if not locked and close on device
if(AccCache.accLock==0) {
dprintf("AccleratorViewClose %lx AccLock decremented to %ld move to LRU queue\n",(uint64_t)CpuPtr,(uint64_t)AccCache.accLock);
LRUinsert(AccCache);
} else {
dprintf("AccleratorViewClose %lx AccLock decremented to %ld\n",(uint64_t)CpuPtr,(uint64_t)AccCache.accLock);
}
}
void MemoryManager::CpuViewClose(uint64_t CpuPtr)
{
auto AccCacheIterator = EntryLookup(CpuPtr);
auto & AccCache = AccCacheIterator->second;
assert(AccCache.cpuLock>0);
assert(AccCache.accLock==0);
AccCache.cpuLock--;
}
/*
* Action State StateNext Flush Clone
*
* CpuRead Empty CpuDirty - -
* CpuWrite Empty CpuDirty - -
* CpuRead CpuDirty CpuDirty - -
* CpuWrite CpuDirty CpuDirty - -
* CpuRead Consistent Consistent - -
* CpuWrite Consistent CpuDirty - -
* CpuRead AccDirty Consistent Y -
* CpuWrite AccDirty CpuDirty Y -
*/
uint64_t MemoryManager::CpuViewOpen(uint64_t CpuPtr,size_t bytes,ViewMode mode,ViewAdvise transient)
{
////////////////////////////////////////////////////////////////////////////
// Find if present, otherwise get or force an empty
////////////////////////////////////////////////////////////////////////////
if ( EntryPresent(CpuPtr)==0 ){
EntryCreate(CpuPtr,bytes,mode,transient);
}
auto AccCacheIterator = EntryLookup(CpuPtr);
auto & AccCache = AccCacheIterator->second;
// CPU doesn't need to free space
// if (!AccCache.AccPtr) {
// EvictVictims(bytes);
// }
assert((mode==CpuRead)||(mode==CpuWrite));
assert(AccCache.accLock==0); // Programming error
if(AccCache.state!=Empty) {
assert(AccCache.CpuPtr == CpuPtr);
assert(AccCache.bytes==bytes);
}
if(AccCache.state==Empty) {
AccCache.CpuPtr = CpuPtr;
AccCache.AccPtr = (uint64_t)NULL;
AccCache.bytes = bytes;
AccCache.state = CpuDirty; // Empty + CpuRead/CpuWrite => CpuDirty
AccCache.accLock= 0;
AccCache.cpuLock= 1;
} else if(AccCache.state==CpuDirty ){
// AccPtr dont care, deferred allocate
AccCache.state = CpuDirty; // CpuDirty +CpuRead/CpuWrite => CpuDirty
AccCache.cpuLock++;
} else if(AccCache.state==Consistent) {
assert(AccCache.AccPtr != (uint64_t)NULL);
if(mode==CpuWrite)
AccCache.state = CpuDirty; // Consistent +CpuWrite => CpuDirty
else
AccCache.state = Consistent; // Consistent +CpuRead => Consistent
AccCache.cpuLock++;
} else if(AccCache.state==AccDirty) {
assert(AccCache.AccPtr != (uint64_t)NULL);
Flush(AccCache);
if(mode==CpuWrite) AccCache.state = CpuDirty; // AccDirty +CpuWrite => CpuDirty, Flush
else AccCache.state = Consistent; // AccDirty +CpuRead => Consistent, Flush
AccCache.cpuLock++;
} else {
assert(0); // should be unreachable
}
AccCache.transient= transient? EvictNext : 0;
return AccCache.CpuPtr;
}
void MemoryManager::NotifyDeletion(void *_ptr)
{
// Look up in ViewCache
uint64_t ptr = (uint64_t)_ptr;
if(EntryPresent(ptr)) {
auto e = EntryLookup(ptr);
AccDiscard(e->second);
}
}
void MemoryManager::Print(void)
{
PrintBytes();
std::cout << GridLogMessage << "--------------------------------------------" << std::endl;
std::cout << GridLogMessage << "Memory Manager " << std::endl;
std::cout << GridLogMessage << "--------------------------------------------" << std::endl;
std::cout << GridLogMessage << DeviceBytes << " bytes allocated on device " << std::endl;
std::cout << GridLogMessage << DeviceLRUBytes<< " bytes evictable on device " << std::endl;
std::cout << GridLogMessage << DeviceMaxBytes<< " bytes max on device " << std::endl;
std::cout << GridLogMessage << HostToDeviceXfer << " transfers to device " << std::endl;
std::cout << GridLogMessage << DeviceToHostXfer << " transfers from device " << std::endl;
std::cout << GridLogMessage << HostToDeviceBytes<< " bytes transfered to device " << std::endl;
std::cout << GridLogMessage << DeviceToHostBytes<< " bytes transfered from device " << std::endl;
std::cout << GridLogMessage << DeviceEvictions << " Evictions from device " << std::endl;
std::cout << GridLogMessage << DeviceDestroy << " Destroyed vectors on device " << std::endl;
std::cout << GridLogMessage << AccViewTable.size()<< " vectors " << LRU.size()<<" evictable"<< std::endl;
acceleratorMem();
std::cout << GridLogMessage << "--------------------------------------------" << std::endl;
}
void MemoryManager::PrintAll(void)
{
Print();
std::cout << GridLogMessage << std::endl;
std::cout << GridLogMessage << "--------------------------------------------" << std::endl;
std::cout << GridLogMessage << "CpuAddr\t\tAccAddr\t\tState\t\tcpuLock\taccLock\tLRU_valid "<<std::endl;
std::cout << GridLogMessage << "--------------------------------------------" << std::endl;
for(auto it=AccViewTable.begin();it!=AccViewTable.end();it++){
auto &AccCache = it->second;
std::string str;
if ( AccCache.state==Empty ) str = std::string("Empty");
if ( AccCache.state==CpuDirty ) str = std::string("CpuDirty");
if ( AccCache.state==AccDirty ) str = std::string("AccDirty");
if ( AccCache.state==Consistent)str = std::string("Consistent");
std::cout << GridLogMessage << "0x"<<std::hex<<AccCache.CpuPtr<<std::dec
<< "\t0x"<<std::hex<<AccCache.AccPtr<<std::dec<<"\t" <<str
<< "\t" << AccCache.cpuLock
<< "\t" << AccCache.accLock
<< "\t" << AccCache.LRU_valid<<std::endl;
}
std::cout << GridLogMessage << "--------------------------------------------" << std::endl;
};
int MemoryManager::isOpen (void* _CpuPtr)
{
uint64_t CpuPtr = (uint64_t)_CpuPtr;
if ( EntryPresent(CpuPtr) ){
auto AccCacheIterator = EntryLookup(CpuPtr);
auto & AccCache = AccCacheIterator->second;
return AccCache.cpuLock+AccCache.accLock;
} else {
return 0;
}
}
void MemoryManager::Audit(std::string s)
{
uint64_t CpuBytes=0;
uint64_t AccBytes=0;
uint64_t LruBytes1=0;
uint64_t LruBytes2=0;
uint64_t LruCnt=0;
std::cout << " Memory Manager::Audit() from "<<s<<std::endl;
for(auto it=LRU.begin();it!=LRU.end();it++){
uint64_t cpuPtr = *it;
assert(EntryPresent(cpuPtr));
auto AccCacheIterator = EntryLookup(cpuPtr);
auto & AccCache = AccCacheIterator->second;
LruBytes2+=AccCache.bytes;
assert(AccCache.LRU_valid==1);
assert(AccCache.LRU_entry==it);
}
std::cout << " Memory Manager::Audit() LRU queue matches table entries "<<std::endl;
for(auto it=AccViewTable.begin();it!=AccViewTable.end();it++){
auto &AccCache = it->second;
std::string str;
if ( AccCache.state==Empty ) str = std::string("Empty");
if ( AccCache.state==CpuDirty ) str = std::string("CpuDirty");
if ( AccCache.state==AccDirty ) str = std::string("AccDirty");
if ( AccCache.state==Consistent)str = std::string("Consistent");
CpuBytes+=AccCache.bytes;
if( AccCache.AccPtr ) AccBytes+=AccCache.bytes;
if( AccCache.LRU_valid ) LruBytes1+=AccCache.bytes;
if( AccCache.LRU_valid ) LruCnt++;
if ( AccCache.cpuLock || AccCache.accLock ) {
assert(AccCache.LRU_valid==0);
std::cout << GridLogError << s<< "\n\t 0x"<<std::hex<<AccCache.CpuPtr<<std::dec
<< "\t0x"<<std::hex<<AccCache.AccPtr<<std::dec<<"\t" <<str
<< "\t cpuLock " << AccCache.cpuLock
<< "\t accLock " << AccCache.accLock
<< "\t LRUvalid " << AccCache.LRU_valid<<std::endl;
}
assert( AccCache.cpuLock== 0 ) ;
assert( AccCache.accLock== 0 ) ;
}
std::cout << " Memory Manager::Audit() no locked table entries "<<std::endl;
assert(LruBytes1==LruBytes2);
assert(LruBytes1==DeviceLRUBytes);
std::cout << " Memory Manager::Audit() evictable bytes matches sum over table "<<std::endl;
assert(AccBytes==DeviceBytes);
std::cout << " Memory Manager::Audit() device bytes matches sum over table "<<std::endl;
assert(LruCnt == LRU.size());
std::cout << " Memory Manager::Audit() LRU entry count matches "<<std::endl;
}
void MemoryManager::PrintState(void* _CpuPtr)
{
uint64_t CpuPtr = (uint64_t)_CpuPtr;
if ( EntryPresent(CpuPtr) ){
auto AccCacheIterator = EntryLookup(CpuPtr);
auto & AccCache = AccCacheIterator->second;
std::string str;
if ( AccCache.state==Empty ) str = std::string("Empty");
if ( AccCache.state==CpuDirty ) str = std::string("CpuDirty");
if ( AccCache.state==AccDirty ) str = std::string("AccDirty");
if ( AccCache.state==Consistent)str = std::string("Consistent");
if ( AccCache.state==EvictNext) str = std::string("EvictNext");
std::cout << GridLogMessage << "CpuAddr\t\tAccAddr\t\tState\t\tcpuLock\taccLock\tLRU_valid "<<std::endl;
std::cout << GridLogMessage << "\tx"<<std::hex<<AccCache.CpuPtr<<std::dec
<< "\tx"<<std::hex<<AccCache.AccPtr<<std::dec<<"\t" <<str
<< "\t" << AccCache.cpuLock
<< "\t" << AccCache.accLock
<< "\t" << AccCache.LRU_valid<<std::endl;
} else {
std::cout << GridLogMessage << "No Entry in AccCache table." << std::endl;
}
}
NAMESPACE_END(Grid);
#endif
-31
View File
@@ -1,31 +0,0 @@
#include <Grid/GridCore.h>
#ifdef GRID_UVM
NAMESPACE_BEGIN(Grid);
/////////////////////////////////////////////////////////////////////////////////
// View management is 1:1 address space mapping
/////////////////////////////////////////////////////////////////////////////////
uint64_t MemoryManager::DeviceBytes;
uint64_t MemoryManager::DeviceLRUBytes;
uint64_t MemoryManager::DeviceMaxBytes = 1024*1024*128;
uint64_t MemoryManager::HostToDeviceBytes;
uint64_t MemoryManager::DeviceToHostBytes;
uint64_t MemoryManager::HostToDeviceXfer;
uint64_t MemoryManager::DeviceToHostXfer;
uint64_t MemoryManager::DeviceEvictions;
uint64_t MemoryManager::DeviceDestroy;
void MemoryManager::Audit(std::string s){};
void MemoryManager::ViewClose(void* AccPtr,ViewMode mode){};
void *MemoryManager::ViewOpen(void* CpuPtr,size_t bytes,ViewMode mode,ViewAdvise hint){ return CpuPtr; };
int MemoryManager::isOpen (void* CpuPtr) { return 0;}
void MemoryManager::PrintState(void* CpuPtr)
{
std::cout << GridLogMessage << "Host<->Device memory movement not currently managed by Grid." << std::endl;
};
void MemoryManager::Print(void){};
void MemoryManager::PrintAll(void){};
void MemoryManager::NotifyDeletion(void *ptr){};
NAMESPACE_END(Grid);
#endif
-67
View File
@@ -1,67 +0,0 @@
#include <Grid/GridCore.h>
#include <fcntl.h>
NAMESPACE_BEGIN(Grid);
MemoryStats *MemoryProfiler::stats = nullptr;
bool MemoryProfiler::debug = false;
void check_huge_pages(void *Buf,uint64_t BYTES)
{
#ifdef __linux__
int fd = open("/proc/self/pagemap", O_RDONLY);
assert(fd >= 0);
const int page_size = 4096;
uint64_t virt_pfn = (uint64_t)Buf / page_size;
off_t offset = sizeof(uint64_t) * virt_pfn;
uint64_t npages = (BYTES + page_size-1) / page_size;
uint64_t pagedata[npages];
uint64_t ret = lseek(fd, offset, SEEK_SET);
assert(ret == offset);
ret = ::read(fd, pagedata, sizeof(uint64_t)*npages);
assert(ret == sizeof(uint64_t) * npages);
int nhugepages = npages / 512;
int n4ktotal, nnothuge;
n4ktotal = 0;
nnothuge = 0;
for (int i = 0; i < nhugepages; ++i) {
uint64_t baseaddr = (pagedata[i*512] & 0x7fffffffffffffULL) * page_size;
for (int j = 0; j < 512; ++j) {
uint64_t pageaddr = (pagedata[i*512+j] & 0x7fffffffffffffULL) * page_size;
++n4ktotal;
if (pageaddr != baseaddr + j * page_size)
++nnothuge;
}
}
int rank = CartesianCommunicator::RankWorld();
printf("rank %d Allocated %d 4k pages, %d not in huge pages\n", rank, n4ktotal, nnothuge);
#endif
}
std::string sizeString(const size_t bytes)
{
constexpr unsigned int bufSize = 256;
const char *suffixes[7] = {"", "K", "M", "G", "T", "P", "E"};
char buf[256];
size_t s = 0;
double count = bytes;
while (count >= 1024 && s < 7)
{
s++;
count /= 1024;
}
if (count - floor(count) == 0.0)
{
snprintf(buf, bufSize, "%d %sB", (int)count, suffixes[s]);
}
else
{
snprintf(buf, bufSize, "%.1f %sB", count, suffixes[s]);
}
return std::string(buf);
}
NAMESPACE_END(Grid);
-95
View File
@@ -1,95 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/MemoryStats.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
std::string sizeString(size_t bytes);
struct MemoryStats
{
size_t totalAllocated{0}, maxAllocated{0},
currentlyAllocated{0}, totalFreed{0};
};
class MemoryProfiler
{
public:
static MemoryStats *stats;
static bool debug;
};
#define memString(bytes) std::to_string(bytes) + " (" + sizeString(bytes) + ")"
#define profilerDebugPrint \
if (MemoryProfiler::stats) \
{ \
auto s = MemoryProfiler::stats; \
std::cout << GridLogDebug << "[Memory debug] Stats " << MemoryProfiler::stats << std::endl; \
std::cout << GridLogDebug << "[Memory debug] total : " << memString(s->totalAllocated) \
<< std::endl; \
std::cout << GridLogDebug << "[Memory debug] max : " << memString(s->maxAllocated) \
<< std::endl; \
std::cout << GridLogDebug << "[Memory debug] current: " << memString(s->currentlyAllocated) \
<< std::endl; \
std::cout << GridLogDebug << "[Memory debug] freed : " << memString(s->totalFreed) \
<< std::endl; \
}
#define profilerAllocate(bytes) \
if (MemoryProfiler::stats) \
{ \
auto s = MemoryProfiler::stats; \
s->totalAllocated += (bytes); \
s->currentlyAllocated += (bytes); \
s->maxAllocated = std::max(s->maxAllocated, s->currentlyAllocated); \
} \
if (MemoryProfiler::debug) \
{ \
std::cout << GridLogDebug << "[Memory debug] allocating " << memString(bytes) << std::endl; \
profilerDebugPrint; \
}
#define profilerFree(bytes) \
if (MemoryProfiler::stats) \
{ \
auto s = MemoryProfiler::stats; \
s->totalFreed += (bytes); \
s->currentlyAllocated -= (bytes); \
} \
if (MemoryProfiler::debug) \
{ \
std::cout << GridLogDebug << "[Memory debug] freeing " << memString(bytes) << std::endl; \
profilerDebugPrint; \
}
void check_huge_pages(void *Buf,uint64_t BYTES);
NAMESPACE_END(Grid);
-35
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@@ -1,35 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/Cartesian.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CARTESIAN_H
#define GRID_CARTESIAN_H
#include <Grid/cartesian/Cartesian_base.h>
#include <Grid/cartesian/Cartesian_full.h>
#include <Grid/cartesian/Cartesian_red_black.h>
#endif
-292
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@@ -1,292 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/cartesian/Cartesian_base.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: paboyle <paboyle@ph.ed.ac.uk>
Author: Guido Cossu <guido.cossu@ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CARTESIAN_BASE_H
#define GRID_CARTESIAN_BASE_H
NAMESPACE_BEGIN(Grid);
//////////////////////////////////////////////////////////////////////
// Commicator provides information on the processor grid
//////////////////////////////////////////////////////////////////////
// unsigned long _ndimension;
// Coordinate _processors; // processor grid
// int _processor; // linear processor rank
// Coordinate _processor_coor; // linear processor rank
//////////////////////////////////////////////////////////////////////
class GridBase : public CartesianCommunicator , public GridThread {
public:
int dummy;
// Give Lattice access
template<class object> friend class Lattice;
GridBase(const Coordinate & processor_grid) : CartesianCommunicator(processor_grid) { LocallyPeriodic=0;};
GridBase(const Coordinate & processor_grid,
const CartesianCommunicator &parent,
int &split_rank)
: CartesianCommunicator(processor_grid,parent,split_rank) {LocallyPeriodic=0;};
GridBase(const Coordinate & processor_grid,
const CartesianCommunicator &parent)
: CartesianCommunicator(processor_grid,parent,dummy) {LocallyPeriodic=0;};
virtual ~GridBase() = default;
// Physics Grid information.
Coordinate _simd_layout;// Which dimensions get relayed out over simd lanes.
Coordinate _fdimensions;// (full) Global dimensions of array prior to cb removal
Coordinate _gdimensions;// Global dimensions of array after cb removal
Coordinate _ldimensions;// local dimensions of array with processor images removed
Coordinate _rdimensions;// Reduced local dimensions with simd lane images and processor images removed
Coordinate _ostride; // Outer stride for each dimension
Coordinate _istride; // Inner stride i.e. within simd lane
int _osites; // _isites*_osites = product(dimensions).
int _isites;
int64_t _fsites; // _isites*_osites = product(dimensions).
int64_t _gsites;
Coordinate _slice_block;// subslice information
Coordinate _slice_stride;
Coordinate _slice_nblock;
Coordinate _lstart; // local start of array in gcoors _processor_coor[d]*_ldimensions[d]
Coordinate _lend ; // local end of array in gcoors _processor_coor[d]*_ldimensions[d]+_ldimensions_[d]-1
bool _isCheckerBoarded;
int LocallyPeriodic;
Coordinate _checker_dim_mask;
int _checker_dim;
public:
////////////////////////////////////////////////////////////////
// Checkerboarding interface is virtual and overridden by
// GridCartesian / GridRedBlackCartesian
////////////////////////////////////////////////////////////////
virtual int CheckerBoarded(int dim) =0;
virtual int CheckerBoard(const Coordinate &site)=0;
virtual int CheckerBoardDestination(int source_cb,int shift,int dim)=0;
virtual int CheckerBoardShift(int source_cb,int dim,int shift,int osite)=0;
virtual int CheckerBoardShiftForCB(int source_cb,int dim,int shift,int cb)=0;
virtual int CheckerBoardFromOindex (int Oindex)=0;
virtual int CheckerBoardFromOindexTable (int Oindex)=0;
//////////////////////////////////////////////////////////////////////////////////////////////
// Local layout calculations
//////////////////////////////////////////////////////////////////////////////////////////////
// These routines are key. Subdivide the linearised cartesian index into
// "inner" index identifying which simd lane of object<vFcomplex> is associated with coord
// "outer" index identifying which element of _odata in class "Lattice" is associated with coord.
//
// Compared to, say, Blitz++ we simply need to store BOTH an inner stride and an outer
// stride per dimension. The cost of evaluating the indexing information is doubled for an n-dimensional
// coordinate. Note, however, for data parallel operations the "inner" indexing cost is not paid and all
// lanes are operated upon simultaneously.
virtual int oIndex(Coordinate &coor)
{
int idx=0;
// Works with either global or local coordinates
for(int d=0;d<_ndimension;d++) idx+=_ostride[d]*(coor[d]%_rdimensions[d]);
return idx;
}
virtual int iIndex(Coordinate &lcoor)
{
int idx=0;
for(int d=0;d<_ndimension;d++) idx+=_istride[d]*(lcoor[d]/_rdimensions[d]);
return idx;
}
inline int oIndexReduced(Coordinate &ocoor)
{
int idx=0;
// ocoor is already reduced so can eliminate the modulo operation
// for fast indexing and inline the routine
for(int d=0;d<_ndimension;d++) idx+=_ostride[d]*ocoor[d];
return idx;
}
inline void oCoorFromOindex (Coordinate& coor,int Oindex){
Lexicographic::CoorFromIndex(coor,Oindex,_rdimensions);
}
inline void InOutCoorToLocalCoor (Coordinate &ocoor, Coordinate &icoor, Coordinate &lcoor) {
lcoor.resize(_ndimension);
for (int d = 0; d < _ndimension; d++)
lcoor[d] = ocoor[d] + _rdimensions[d] * icoor[d];
}
//////////////////////////////////////////////////////////
// SIMD lane addressing
//////////////////////////////////////////////////////////
inline void iCoorFromIindex(Coordinate &coor,int lane)
{
Lexicographic::CoorFromIndex(coor,lane,_simd_layout);
}
inline int PermuteDim(int dimension){
return _simd_layout[dimension]>1;
}
inline int PermuteType(int dimension){
int permute_type=0;
//
// Best way to encode this would be to present a mask
// for which simd dimensions are rotated, and the rotation
// size. If there is only one simd dimension rotated, this is just
// a permute.
//
// Cases: PermuteType == 1,2,4,8
// Distance should be either 0,1,2..
//
if ( _simd_layout[dimension] > 2 ) {
for(int d=0;d<_ndimension;d++){
if ( d != dimension ) assert ( (_simd_layout[d]==1) );
}
permute_type = RotateBit; // How to specify distance; this is not just direction.
return permute_type;
}
for(int d=_ndimension-1;d>dimension;d--){
if (_simd_layout[d]>1 ) permute_type++;
}
return permute_type;
}
////////////////////////////////////////////////////////////////
// Array sizing queries
////////////////////////////////////////////////////////////////
inline int iSites(void) const { return _isites; };
inline int Nsimd(void) const { return _isites; };// Synonymous with iSites
inline int oSites(void) const { return _osites; };
inline int lSites(void) const { return _isites*_osites; };
inline int64_t gSites(void) const { return (int64_t)_isites*(int64_t)_osites*(int64_t)_Nprocessors; };
inline int Nd (void) const { return _ndimension;};
inline const Coordinate LocalStarts(void) { return _lstart; };
inline const Coordinate &FullDimensions(void) { return _fdimensions;};
inline const Coordinate &GlobalDimensions(void) { return _gdimensions;};
inline const Coordinate &LocalDimensions(void) { return _ldimensions;};
inline const Coordinate &VirtualLocalDimensions(void) { return _ldimensions;};
////////////////////////////////////////////////////////////////
// Utility to print the full decomposition details
////////////////////////////////////////////////////////////////
void show_decomposition(){
std::cout << GridLogMessage << "\tFull Dimensions : " << _fdimensions << std::endl;
std::cout << GridLogMessage << "\tSIMD layout : " << _simd_layout << std::endl;
std::cout << GridLogMessage << "\tGlobal Dimensions : " << _gdimensions << std::endl;
std::cout << GridLogMessage << "\tLocal Dimensions : " << _ldimensions << std::endl;
std::cout << GridLogMessage << "\tReduced Dimensions : " << _rdimensions << std::endl;
std::cout << GridLogMessage << "\tOuter strides : " << _ostride << std::endl;
std::cout << GridLogMessage << "\tInner strides : " << _istride << std::endl;
std::cout << GridLogMessage << "\tiSites : " << _isites << std::endl;
std::cout << GridLogMessage << "\toSites : " << _osites << std::endl;
std::cout << GridLogMessage << "\tlSites : " << lSites() << std::endl;
std::cout << GridLogMessage << "\tgSites : " << gSites() << std::endl;
std::cout << GridLogMessage << "\tNd : " << _ndimension << std::endl;
}
////////////////////////////////////////////////////////////////
// Global addressing
////////////////////////////////////////////////////////////////
void GlobalIndexToGlobalCoor(int64_t gidx,Coordinate &gcoor){
assert(gidx< gSites());
Lexicographic::CoorFromIndex(gcoor,gidx,_gdimensions);
}
void LocalIndexToLocalCoor(int lidx,Coordinate &lcoor){
assert(lidx<lSites());
Lexicographic::CoorFromIndex(lcoor,lidx,_ldimensions);
}
void GlobalCoorToGlobalIndex(const Coordinate & gcoor,int64_t & gidx){
gidx=0;
int mult=1;
for(int mu=0;mu<_ndimension;mu++) {
gidx+=mult*gcoor[mu];
mult*=_gdimensions[mu];
}
}
void GlobalCoorToProcessorCoorLocalCoor(Coordinate &pcoor,Coordinate &lcoor,const Coordinate &gcoor)
{
pcoor.resize(_ndimension);
lcoor.resize(_ndimension);
for(int mu=0;mu<_ndimension;mu++){
int _fld = _fdimensions[mu]/_processors[mu];
pcoor[mu] = gcoor[mu]/_fld;
lcoor[mu] = gcoor[mu]%_fld;
}
}
void GlobalCoorToRankIndex(int &rank, int &o_idx, int &i_idx ,const Coordinate &gcoor)
{
Coordinate pcoor;
Coordinate lcoor;
GlobalCoorToProcessorCoorLocalCoor(pcoor,lcoor,gcoor);
rank = RankFromProcessorCoor(pcoor);
/*
Coordinate cblcoor(lcoor);
for(int d=0;d<cblcoor.size();d++){
if( this->CheckerBoarded(d) ) {
cblcoor[d] = lcoor[d]/2;
}
}
*/
i_idx= iIndex(lcoor);
o_idx= oIndex(lcoor);
}
void RankIndexToGlobalCoor(int rank, int o_idx, int i_idx , Coordinate &gcoor)
{
gcoor.resize(_ndimension);
Coordinate coor(_ndimension);
ProcessorCoorFromRank(rank,coor);
for(int mu=0;mu<_ndimension;mu++) gcoor[mu] = _ldimensions[mu]*coor[mu];
iCoorFromIindex(coor,i_idx);
for(int mu=0;mu<_ndimension;mu++) gcoor[mu] += _rdimensions[mu]*coor[mu];
oCoorFromOindex (coor,o_idx);
for(int mu=0;mu<_ndimension;mu++) gcoor[mu] += coor[mu];
}
void RankIndexCbToFullGlobalCoor(int rank, int o_idx, int i_idx, int cb,Coordinate &fcoor)
{
RankIndexToGlobalCoor(rank,o_idx,i_idx ,fcoor);
if(CheckerBoarded(0)){
fcoor[0] = fcoor[0]*2+cb;
}
}
void ProcessorCoorLocalCoorToGlobalCoor(Coordinate &Pcoor,Coordinate &Lcoor,Coordinate &gcoor)
{
gcoor.resize(_ndimension);
for(int mu=0;mu<_ndimension;mu++) gcoor[mu] = Pcoor[mu]*_ldimensions[mu]+Lcoor[mu];
}
};
NAMESPACE_END(Grid);
#endif
-179
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/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/cartesian/Cartesian_full.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CARTESIAN_FULL_H
#define GRID_CARTESIAN_FULL_H
NAMESPACE_BEGIN(Grid);
/////////////////////////////////////////////////////////////////////////////////////////
// Grid Support.
/////////////////////////////////////////////////////////////////////////////////////////
class GridCartesian: public GridBase {
public:
int dummy;
// Coordinate _checker_dim_mask;
virtual int CheckerBoardFromOindexTable (int Oindex) {
return 0;
}
virtual int CheckerBoardFromOindex (int Oindex)
{
return 0;
}
virtual int CheckerBoarded(int dim) {
return 0;
}
virtual int CheckerBoard(const Coordinate &site){
return 0;
}
virtual int CheckerBoardDestination(int cb,int shift,int dim){
return 0;
}
virtual int CheckerBoardShiftForCB(int source_cb,int dim,int shift, int ocb){
return shift;
}
virtual int CheckerBoardShift(int source_cb,int dim,int shift, int osite){
return shift;
}
/////////////////////////////////////////////////////////////////////////
// Constructor takes a parent grid and possibly subdivides communicator.
/////////////////////////////////////////////////////////////////////////
GridCartesian(const Coordinate &dimensions,
const Coordinate &simd_layout,
const Coordinate &processor_grid,
const GridCartesian &parent) : GridBase(processor_grid,parent,dummy)
{
Init(dimensions,simd_layout,processor_grid);
}
GridCartesian(const Coordinate &dimensions,
const Coordinate &simd_layout,
const Coordinate &processor_grid,
const GridCartesian &parent,int &split_rank) : GridBase(processor_grid,parent,split_rank)
{
Init(dimensions,simd_layout,processor_grid);
}
/////////////////////////////////////////////////////////////////////////
// Construct from comm world
/////////////////////////////////////////////////////////////////////////
GridCartesian(const Coordinate &dimensions,
const Coordinate &simd_layout,
const Coordinate &processor_grid) : GridBase(processor_grid)
{
Init(dimensions,simd_layout,processor_grid);
}
virtual ~GridCartesian() = default;
void Init(const Coordinate &dimensions,
const Coordinate &simd_layout,
const Coordinate &processor_grid)
{
///////////////////////
// Grid information
///////////////////////
_isCheckerBoarded = false;
_ndimension = dimensions.size();
_fdimensions.resize(_ndimension);
_gdimensions.resize(_ndimension);
_ldimensions.resize(_ndimension);
_rdimensions.resize(_ndimension);
_simd_layout.resize(_ndimension);
_checker_dim_mask.resize(_ndimension);;
_checker_dim = -1;
_lstart.resize(_ndimension);
_lend.resize(_ndimension);
_ostride.resize(_ndimension);
_istride.resize(_ndimension);
_fsites = _gsites = _osites = _isites = 1;
for (int d = 0; d < _ndimension; d++)
{
_checker_dim_mask[d]=0;
_fdimensions[d] = dimensions[d]; // Global dimensions
_gdimensions[d] = _fdimensions[d]; // Global dimensions
_simd_layout[d] = simd_layout[d];
_fsites = _fsites * _fdimensions[d];
_gsites = _gsites * _gdimensions[d];
// Use a reduced simd grid
_ldimensions[d] = _gdimensions[d] / _processors[d]; //local dimensions
//std::cout << _ldimensions[d] << " " << _gdimensions[d] << " " << _processors[d] << std::endl;
assert(_ldimensions[d] * _processors[d] == _gdimensions[d]);
_rdimensions[d] = _ldimensions[d] / _simd_layout[d]; //overdecomposition
assert(_rdimensions[d] * _simd_layout[d] == _ldimensions[d]);
_lstart[d] = _processor_coor[d] * _ldimensions[d];
_lend[d] = _processor_coor[d] * _ldimensions[d] + _ldimensions[d] - 1;
_osites *= _rdimensions[d];
_isites *= _simd_layout[d];
// Addressing support
if (d == 0)
{
_ostride[d] = 1;
_istride[d] = 1;
}
else
{
_ostride[d] = _ostride[d - 1] * _rdimensions[d - 1];
_istride[d] = _istride[d - 1] * _simd_layout[d - 1];
}
}
///////////////////////
// subplane information
///////////////////////
_slice_block.resize(_ndimension);
_slice_stride.resize(_ndimension);
_slice_nblock.resize(_ndimension);
int block = 1;
int nblock = 1;
for (int d = 0; d < _ndimension; d++)
nblock *= _rdimensions[d];
for (int d = 0; d < _ndimension; d++)
{
nblock /= _rdimensions[d];
_slice_block[d] = block;
_slice_stride[d] = _ostride[d] * _rdimensions[d];
_slice_nblock[d] = nblock;
block = block * _rdimensions[d];
}
};
};
NAMESPACE_END(Grid);
#endif
-306
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@@ -1,306 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/cartesian/Cartesian_red_black.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CARTESIAN_RED_BLACK_H
#define GRID_CARTESIAN_RED_BLACK_H
NAMESPACE_BEGIN(Grid);
static const int CbRed =0;
static const int CbBlack=1;
static const int Even =CbRed;
static const int Odd =CbBlack;
accelerator_inline int RedBlackCheckerBoardFromOindex (int oindex,const Coordinate &rdim,const Coordinate &chk_dim_msk)
{
int nd=rdim.size();
Coordinate coor(nd);
Lexicographic::CoorFromIndex(coor,oindex,rdim);
int linear=0;
for(int d=0;d<nd;d++){
if(chk_dim_msk[d])
linear=linear+coor[d];
}
return (linear&0x1);
}
// Specialise this for red black grids storing half the data like a chess board.
class GridRedBlackCartesian : public GridBase
{
public:
// Coordinate _checker_dim_mask;
// int _checker_dim;
std::vector<int> _checker_board;
virtual int isCheckerBoarded(void) const { return 1; };
virtual int CheckerBoarded(int dim){
if( dim==_checker_dim) return 1;
else return 0;
}
virtual int CheckerBoard(const Coordinate &site){
int linear=0;
assert(site.size()==_ndimension);
for(int d=0;d<_ndimension;d++){
if(_checker_dim_mask[d])
linear=linear+site[d];
}
return (linear&0x1);
}
// Depending on the cb of site, we toggle source cb.
// for block #b, element #e = (b, e)
// we need
virtual int CheckerBoardShiftForCB(int source_cb,int dim,int shift,int ocb){
if(dim != _checker_dim) return shift;
int fulldim =_fdimensions[dim];
shift = (shift+fulldim)%fulldim;
// Probably faster with table lookup;
// or by looping over x,y,z and multiply rather than computing checkerboard.
if ( (source_cb+ocb)&1 ) {
return (shift)/2;
} else {
return (shift+1)/2;
}
}
virtual int CheckerBoardFromOindexTable (int Oindex) {
return _checker_board[Oindex];
}
virtual int CheckerBoardFromOindex (int Oindex)
{
Coordinate ocoor;
oCoorFromOindex(ocoor,Oindex);
return CheckerBoard(ocoor);
}
virtual int CheckerBoardShift(int source_cb,int dim,int shift,int osite){
if(dim != _checker_dim) return shift;
int ocb=CheckerBoardFromOindex(osite);
return CheckerBoardShiftForCB(source_cb,dim,shift,ocb);
}
virtual int CheckerBoardDestination(int source_cb,int shift,int dim){
if ( _checker_dim_mask[dim] ) {
// If _fdimensions[checker_dim] is odd, then shifting by 1 in other dims
// does NOT cause a parity hop.
int add=(dim==_checker_dim) ? 0 : _fdimensions[_checker_dim];
if ( (shift+add) &0x1) {
return 1-source_cb;
} else {
return source_cb;
}
} else {
return source_cb;
}
};
////////////////////////////////////////////////////////////
// Create Redblack from original grid; require full grid pointer ?
////////////////////////////////////////////////////////////
GridRedBlackCartesian(const GridBase *base) : GridBase(base->_processors,*base)
{
int dims = base->_ndimension;
Coordinate checker_dim_mask(dims,1);
int checker_dim = 0;
Init(base->_fdimensions,base->_simd_layout,base->_processors,checker_dim_mask,checker_dim);
};
////////////////////////////////////////////////////////////
// Create redblack from original grid, with non-trivial checker dim mask
////////////////////////////////////////////////////////////
GridRedBlackCartesian(const GridBase *base,
const Coordinate &checker_dim_mask,
int checker_dim
) : GridBase(base->_processors,*base)
{
Init(base->_fdimensions,base->_simd_layout,base->_processors,checker_dim_mask,checker_dim) ;
}
virtual ~GridRedBlackCartesian() = default;
void Init(const Coordinate &dimensions,
const Coordinate &simd_layout,
const Coordinate &processor_grid,
const Coordinate &checker_dim_mask,
int checker_dim)
{
_isCheckerBoarded = true;
_checker_dim = checker_dim;
assert(checker_dim_mask[checker_dim] == 1);
_ndimension = dimensions.size();
assert(checker_dim_mask.size() == _ndimension);
assert(processor_grid.size() == _ndimension);
assert(simd_layout.size() == _ndimension);
_fdimensions.resize(_ndimension);
_gdimensions.resize(_ndimension);
_ldimensions.resize(_ndimension);
_rdimensions.resize(_ndimension);
_simd_layout.resize(_ndimension);
_lstart.resize(_ndimension);
_lend.resize(_ndimension);
_ostride.resize(_ndimension);
_istride.resize(_ndimension);
_fsites = _gsites = _osites = _isites = 1;
_checker_dim_mask = checker_dim_mask;
for (int d = 0; d < _ndimension; d++)
{
_fdimensions[d] = dimensions[d];
_gdimensions[d] = _fdimensions[d];
_fsites = _fsites * _fdimensions[d];
_gsites = _gsites * _gdimensions[d];
if (d == _checker_dim)
{
assert((_gdimensions[d] & 0x1) == 0);
_gdimensions[d] = _gdimensions[d] / 2; // Remove a checkerboard
_gsites /= 2;
}
_ldimensions[d] = _gdimensions[d] / _processors[d];
assert(_ldimensions[d] * _processors[d] == _gdimensions[d]);
_lstart[d] = _processor_coor[d] * _ldimensions[d];
_lend[d] = _processor_coor[d] * _ldimensions[d] + _ldimensions[d] - 1;
// Use a reduced simd grid
_simd_layout[d] = simd_layout[d];
_rdimensions[d] = _ldimensions[d] / _simd_layout[d]; // this is not checking if this is integer
assert(_rdimensions[d] * _simd_layout[d] == _ldimensions[d]);
assert(_rdimensions[d] > 0);
// all elements of a simd vector must have same checkerboard.
// If Ls vectorised, this must still be the case; e.g. dwf rb5d
if (_simd_layout[d] > 1)
{
if (checker_dim_mask[d])
{
assert((_rdimensions[d] & 0x1) == 0);
}
}
_osites *= _rdimensions[d];
_isites *= _simd_layout[d];
// Addressing support
if (d == 0)
{
_ostride[d] = 1;
_istride[d] = 1;
}
else
{
_ostride[d] = _ostride[d - 1] * _rdimensions[d - 1];
_istride[d] = _istride[d - 1] * _simd_layout[d - 1];
}
}
////////////////////////////////////////////////////////////////////////////////////////////
// subplane information
////////////////////////////////////////////////////////////////////////////////////////////
_slice_block.resize(_ndimension);
_slice_stride.resize(_ndimension);
_slice_nblock.resize(_ndimension);
int block = 1;
int nblock = 1;
for (int d = 0; d < _ndimension; d++)
nblock *= _rdimensions[d];
for (int d = 0; d < _ndimension; d++)
{
nblock /= _rdimensions[d];
_slice_block[d] = block;
_slice_stride[d] = _ostride[d] * _rdimensions[d];
_slice_nblock[d] = nblock;
block = block * _rdimensions[d];
}
////////////////////////////////////////////////
// Create a checkerboard lookup table
////////////////////////////////////////////////
int rvol = 1;
for (int d = 0; d < _ndimension; d++)
{
rvol = rvol * _rdimensions[d];
}
_checker_board.resize(rvol);
for (int osite = 0; osite < _osites; osite++)
{
_checker_board[osite] = CheckerBoardFromOindex(osite);
}
};
protected:
virtual int oIndex(Coordinate &coor)
{
int idx = 0;
for (int d = 0; d < _ndimension; d++)
{
if (d == _checker_dim)
{
idx += _ostride[d] * ((coor[d] / 2) % _rdimensions[d]);
}
else
{
idx += _ostride[d] * (coor[d] % _rdimensions[d]);
}
}
return idx;
};
virtual int iIndex(Coordinate &lcoor)
{
int idx = 0;
for (int d = 0; d < _ndimension; d++)
{
if (d == _checker_dim)
{
idx += _istride[d] * (lcoor[d] / (2 * _rdimensions[d]));
}
else
{
idx += _istride[d] * (lcoor[d] / _rdimensions[d]);
}
}
return idx;
}
};
NAMESPACE_END(Grid);
#endif
-35
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@@ -1,35 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/Communicator.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_COMMUNICATOR_H
#define GRID_COMMUNICATOR_H
#include <Grid/util/Coordinate.h>
#include <Grid/communicator/SharedMemory.h>
#include <Grid/communicator/Communicator_base.h>
#endif
-79
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@@ -1,79 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/communicator/Communicator_none.cc
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#include <Grid/GridCore.h>
#include <fcntl.h>
#include <unistd.h>
#include <limits.h>
#include <sys/mman.h>
NAMESPACE_BEGIN(Grid);
bool Stencil_force_mpi = true;
///////////////////////////////////////////////////////////////
// Info that is setup once and indept of cartesian layout
///////////////////////////////////////////////////////////////
CartesianCommunicator::CommunicatorPolicy_t
CartesianCommunicator::CommunicatorPolicy= CartesianCommunicator::CommunicatorPolicyConcurrent;
int CartesianCommunicator::nCommThreads = -1;
/////////////////////////////////
// Grid information queries
/////////////////////////////////
int CartesianCommunicator::Dimensions(void) { return _ndimension; };
int CartesianCommunicator::IsBoss(void) { return _processor==0; };
int CartesianCommunicator::BossRank(void) { return 0; };
int CartesianCommunicator::ThisRank(void) { return _processor; };
const Coordinate & CartesianCommunicator::ThisProcessorCoor(void) { return _processor_coor; };
const Coordinate & CartesianCommunicator::ProcessorGrid(void) { return _processors; };
int CartesianCommunicator::ProcessorCount(void) { return _Nprocessors; };
////////////////////////////////////////////////////////////////////////////////
// very VERY rarely (Log, serial RNG) we need world without a grid
////////////////////////////////////////////////////////////////////////////////
void CartesianCommunicator::GlobalSum(ComplexF &c)
{
GlobalSumVector((float *)&c,2);
}
void CartesianCommunicator::GlobalSumVector(ComplexF *c,int N)
{
GlobalSumVector((float *)c,2*N);
}
void CartesianCommunicator::GlobalSum(ComplexD &c)
{
GlobalSumVector((double *)&c,2);
}
void CartesianCommunicator::GlobalSumVector(ComplexD *c,int N)
{
GlobalSumVector((double *)c,2*N);
}
NAMESPACE_END(Grid);
-236
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@@ -1,236 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/communicator/Communicator_base.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_COMMUNICATOR_BASE_H
#define GRID_COMMUNICATOR_BASE_H
///////////////////////////////////
// Processor layout information
///////////////////////////////////
#include <Grid/communicator/SharedMemory.h>
NAMESPACE_BEGIN(Grid);
extern bool Stencil_force_mpi ;
class CartesianCommunicator : public SharedMemory {
public:
////////////////////////////////////////////
// Policies
////////////////////////////////////////////
enum CommunicatorPolicy_t { CommunicatorPolicyConcurrent, CommunicatorPolicySequential };
static CommunicatorPolicy_t CommunicatorPolicy;
static void SetCommunicatorPolicy(CommunicatorPolicy_t policy ) { CommunicatorPolicy = policy; }
static int nCommThreads;
////////////////////////////////////////////
// Communicator should know nothing of the physics grid, only processor grid.
////////////////////////////////////////////
int _Nprocessors; // How many in all
int _processor; // linear processor rank
unsigned long _ndimension;
Coordinate _shm_processors; // Which dimensions get relayed out over processors lanes.
Coordinate _processors; // Which dimensions get relayed out over processors lanes.
Coordinate _processor_coor; // linear processor coordinate
static Grid_MPI_Comm communicator_world;
Grid_MPI_Comm communicator;
std::vector<Grid_MPI_Comm> communicator_halo;
////////////////////////////////////////////////
// Must call in Grid startup
////////////////////////////////////////////////
static void Init(int *argc, char ***argv);
////////////////////////////////////////////////
// Constructors to sub-divide a parent communicator
// and default to comm world
////////////////////////////////////////////////
CartesianCommunicator(const Coordinate &processors,const CartesianCommunicator &parent,int &srank);
CartesianCommunicator(const Coordinate &pdimensions_in);
virtual ~CartesianCommunicator();
private:
////////////////////////////////////////////////
// Private initialise from an MPI communicator
// Can use after an MPI_Comm_split, but hidden from user so private
////////////////////////////////////////////////
void InitFromMPICommunicator(const Coordinate &processors, Grid_MPI_Comm communicator_base);
public:
////////////////////////////////////////////////////////////////////////////////////////
// Wraps MPI_Cart routines, or implements equivalent on other impls
////////////////////////////////////////////////////////////////////////////////////////
void ShiftedRanks(int dim,int shift,int & source, int & dest);
int RankFromProcessorCoor(Coordinate &coor);
void ProcessorCoorFromRank(int rank,Coordinate &coor);
int Dimensions(void) ;
int IsBoss(void) ;
int BossRank(void) ;
int ThisRank(void) ;
const Coordinate & ThisProcessorCoor(void) ;
const Coordinate & ShmGrid(void) { return _shm_processors; } ;
const Coordinate & ProcessorGrid(void) ;
int ProcessorCount(void) ;
////////////////////////////////////////////////////////////////////////////////
// very VERY rarely (Log, serial RNG) we need world without a grid
////////////////////////////////////////////////////////////////////////////////
static int RankWorld(void) ;
static void BroadcastWorld(int root,void* data, int bytes);
static void BarrierWorld(void);
////////////////////////////////////////////////////////////
// Reduction
////////////////////////////////////////////////////////////
void GlobalMax(RealD &);
void GlobalMax(RealF &);
void GlobalSum(RealF &);
void GlobalSumVector(RealF *,int N);
void GlobalSum(RealD &);
void GlobalSumVector(RealD *,int N);
void GlobalSum(uint32_t &);
void GlobalSum(uint64_t &);
void GlobalSumVector(uint64_t*,int N);
void GlobalSum(ComplexF &c);
void GlobalSumVector(ComplexF *c,int N);
void GlobalSum(ComplexD &c);
void GlobalSumVector(ComplexD *c,int N);
void GlobalXOR(uint32_t &);
void GlobalXOR(uint64_t &);
template<class obj> void GlobalSumP2P(obj &o)
{
std::vector<obj> column;
obj accum = o;
int source,dest;
for(int d=0;d<_ndimension;d++){
column.resize(_processors[d]);
column[0] = accum;
std::vector<CommsRequest_t> list;
for(int p=1;p<_processors[d];p++){
ShiftedRanks(d,p,source,dest);
SendToRecvFromBegin(list,
&column[0],
dest,
&column[p],
source,
sizeof(obj),d*100+p);
}
CommsComplete(list);
for(int p=1;p<_processors[d];p++){
accum = accum + column[p];
}
}
Broadcast(0,accum);
o=accum;
}
template<class obj> void GlobalSum(obj &o){
typedef typename obj::scalar_type scalar_type;
int words = sizeof(obj)/sizeof(scalar_type);
scalar_type * ptr = (scalar_type *)& o; // Safe alias
GlobalSumVector(ptr,words);
}
////////////////////////////////////////////////////////////
// Face exchange, buffer swap in translational invariant way
////////////////////////////////////////////////////////////
void CommsComplete(std::vector<CommsRequest_t> &list);
void SendToRecvFromBegin(std::vector<CommsRequest_t> &list,
void *xmit,
int dest,
void *recv,
int from,
int bytes,int dir);
void SendToRecvFrom(void *xmit,
int xmit_to_rank,
void *recv,
int recv_from_rank,
int bytes);
double StencilSendToRecvFrom(void *xmit,
int xmit_to_rank,int do_xmit,
void *recv,
int recv_from_rank,int do_recv,
int bytes,int dir);
double StencilSendToRecvFromBegin(std::vector<CommsRequest_t> &list,
void *xmit,
int xmit_to_rank,int do_xmit,
void *recv,
int recv_from_rank,int do_recv,
int xbytes,int rbytes,int dir);
void StencilSendToRecvFromComplete(std::vector<CommsRequest_t> &waitall,int i);
void StencilBarrier(void);
////////////////////////////////////////////////////////////
// Barrier
////////////////////////////////////////////////////////////
void Barrier(void);
////////////////////////////////////////////////////////////
// Broadcast a buffer and composite larger
////////////////////////////////////////////////////////////
void Broadcast(int root,void* data, int bytes);
////////////////////////////////////////////////////////////
// All2All down one dimension
////////////////////////////////////////////////////////////
template<class T> void AllToAll(int dim,std::vector<T> &in, std::vector<T> &out){
assert(dim>=0);
assert(dim<_ndimension);
assert(in.size()==out.size());
int numnode = _processors[dim];
uint64_t bytes=sizeof(T);
uint64_t words=in.size()/numnode;
assert(numnode * words == in.size());
assert(words < (1ULL<<31));
AllToAll(dim,(void *)&in[0],(void *)&out[0],words,bytes);
}
void AllToAll(int dim ,void *in,void *out,uint64_t words,uint64_t bytes);
void AllToAll(void *in,void *out,uint64_t words ,uint64_t bytes);
template<class obj> void Broadcast(int root,obj &data)
{
Broadcast(root,(void *)&data,sizeof(data));
}
};
NAMESPACE_END(Grid);
#endif
-533
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@@ -1,533 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/communicator/Communicator_mpi.cc
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#include <Grid/GridCore.h>
#include <Grid/communicator/SharedMemory.h>
NAMESPACE_BEGIN(Grid);
Grid_MPI_Comm CartesianCommunicator::communicator_world;
////////////////////////////////////////////
// First initialise of comms system
////////////////////////////////////////////
void CartesianCommunicator::Init(int *argc, char ***argv)
{
int flag;
int provided;
MPI_Initialized(&flag); // needed to coexist with other libs apparently
if ( !flag ) {
#ifndef GRID_COMMS_THREADS
nCommThreads=1;
// wrong results here too
// For now: comms-overlap leads to wrong results in Benchmark_wilson even on single node MPI runs
// other comms schemes are ok
MPI_Init_thread(argc,argv,MPI_THREAD_SERIALIZED,&provided);
#else
MPI_Init_thread(argc,argv,MPI_THREAD_MULTIPLE,&provided);
#endif
//If only 1 comms thread we require any threading mode other than SINGLE, but for multiple comms threads we need MULTIPLE
if( (nCommThreads == 1) && (provided == MPI_THREAD_SINGLE) ) {
assert(0);
}
if( (nCommThreads > 1) && (provided != MPI_THREAD_MULTIPLE) ) {
assert(0);
}
}
// Never clean up as done once.
MPI_Comm_dup (MPI_COMM_WORLD,&communicator_world);
Grid_quiesce_nodes();
GlobalSharedMemory::Init(communicator_world);
GlobalSharedMemory::SharedMemoryAllocate(
GlobalSharedMemory::MAX_MPI_SHM_BYTES,
GlobalSharedMemory::Hugepages);
Grid_unquiesce_nodes();
}
///////////////////////////////////////////////////////////////////////////
// Use cartesian communicators now even in MPI3
///////////////////////////////////////////////////////////////////////////
void CartesianCommunicator::ShiftedRanks(int dim,int shift,int &source,int &dest)
{
int ierr=MPI_Cart_shift(communicator,dim,shift,&source,&dest);
assert(ierr==0);
}
int CartesianCommunicator::RankFromProcessorCoor(Coordinate &coor)
{
int rank;
int ierr=MPI_Cart_rank (communicator, &coor[0], &rank);
assert(ierr==0);
return rank;
}
void CartesianCommunicator::ProcessorCoorFromRank(int rank, Coordinate &coor)
{
coor.resize(_ndimension);
int ierr=MPI_Cart_coords (communicator, rank, _ndimension,&coor[0]);
assert(ierr==0);
}
////////////////////////////////////////////////////////////////////////////////////////////////////////
// Initialises from communicator_world
////////////////////////////////////////////////////////////////////////////////////////////////////////
CartesianCommunicator::CartesianCommunicator(const Coordinate &processors)
{
MPI_Comm optimal_comm;
////////////////////////////////////////////////////
// Remap using the shared memory optimising routine
// The remap creates a comm which must be freed
////////////////////////////////////////////////////
GlobalSharedMemory::OptimalCommunicator (processors,optimal_comm,_shm_processors);
InitFromMPICommunicator(processors,optimal_comm);
SetCommunicator(optimal_comm);
///////////////////////////////////////////////////
// Free the temp communicator
///////////////////////////////////////////////////
MPI_Comm_free(&optimal_comm);
}
//////////////////////////////////
// Try to subdivide communicator
//////////////////////////////////
CartesianCommunicator::CartesianCommunicator(const Coordinate &processors,const CartesianCommunicator &parent,int &srank)
{
_ndimension = processors.size(); assert(_ndimension>=1);
int parent_ndimension = parent._ndimension; assert(_ndimension >= parent._ndimension);
Coordinate parent_processor_coor(_ndimension,0);
Coordinate parent_processors (_ndimension,1);
Coordinate shm_processors (_ndimension,1);
// Can make 5d grid from 4d etc...
int pad = _ndimension-parent_ndimension;
for(int d=0;d<parent_ndimension;d++){
parent_processor_coor[pad+d]=parent._processor_coor[d];
parent_processors [pad+d]=parent._processors[d];
shm_processors [pad+d]=parent._shm_processors[d];
}
//////////////////////////////////////////////////////////////////////////////////////////////////////
// split the communicator
//////////////////////////////////////////////////////////////////////////////////////////////////////
// int Nparent = parent._processors ;
int Nparent;
MPI_Comm_size(parent.communicator,&Nparent);
int childsize=1;
for(int d=0;d<processors.size();d++) {
childsize *= processors[d];
}
int Nchild = Nparent/childsize;
assert (childsize * Nchild == Nparent);
Coordinate ccoor(_ndimension); // coor within subcommunicator
Coordinate scoor(_ndimension); // coor of split within parent
Coordinate ssize(_ndimension); // coor of split within parent
for(int d=0;d<_ndimension;d++){
ccoor[d] = parent_processor_coor[d] % processors[d];
scoor[d] = parent_processor_coor[d] / processors[d];
ssize[d] = parent_processors[d] / processors[d];
if ( processors[d] < shm_processors[d] ) shm_processors[d] = processors[d]; // subnode splitting.
}
// rank within subcomm ; srank is rank of subcomm within blocks of subcomms
int crank;
// Mpi uses the reverse Lexico convention to us; so reversed routines called
Lexicographic::IndexFromCoorReversed(ccoor,crank,processors); // processors is the split grid dimensions
Lexicographic::IndexFromCoorReversed(scoor,srank,ssize); // ssize is the number of split grids
MPI_Comm comm_split;
if ( Nchild > 1 ) {
////////////////////////////////////////////////////////////////
// Split the communicator
////////////////////////////////////////////////////////////////
int ierr= MPI_Comm_split(parent.communicator,srank,crank,&comm_split);
assert(ierr==0);
} else {
srank = 0;
int ierr = MPI_Comm_dup (parent.communicator,&comm_split);
assert(ierr==0);
}
//////////////////////////////////////////////////////////////////////////////////////////////////////
// Set up from the new split communicator
//////////////////////////////////////////////////////////////////////////////////////////////////////
InitFromMPICommunicator(processors,comm_split);
//////////////////////////////////////////////////////////////////////////////////////////////////////
// Take the right SHM buffers
//////////////////////////////////////////////////////////////////////////////////////////////////////
SetCommunicator(comm_split);
///////////////////////////////////////////////
// Free the temp communicator
///////////////////////////////////////////////
MPI_Comm_free(&comm_split);
if(0){
std::cout << " ndim " <<_ndimension<<" " << parent._ndimension << std::endl;
for(int d=0;d<processors.size();d++){
std::cout << d<< " " << _processor_coor[d] <<" " << ccoor[d]<<std::endl;
}
}
for(int d=0;d<processors.size();d++){
assert(_processor_coor[d] == ccoor[d] );
}
}
void CartesianCommunicator::InitFromMPICommunicator(const Coordinate &processors, MPI_Comm communicator_base)
{
////////////////////////////////////////////////////
// Creates communicator, and the communicator_halo
////////////////////////////////////////////////////
_ndimension = processors.size();
_processor_coor.resize(_ndimension);
/////////////////////////////////
// Count the requested nodes
/////////////////////////////////
_Nprocessors=1;
_processors = processors;
for(int i=0;i<_ndimension;i++){
_Nprocessors*=_processors[i];
}
Coordinate periodic(_ndimension,1);
MPI_Cart_create(communicator_base, _ndimension,&_processors[0],&periodic[0],0,&communicator);
MPI_Comm_rank(communicator,&_processor);
MPI_Cart_coords(communicator,_processor,_ndimension,&_processor_coor[0]);
if ( 0 && (communicator_base != communicator_world) ) {
std::cout << "InitFromMPICommunicator Cartesian communicator created with a non-world communicator"<<std::endl;
std::cout << " new communicator rank "<<_processor<< " coor ["<<_ndimension<<"] ";
for(int d=0;d<_processors.size();d++){
std::cout << _processor_coor[d]<<" ";
}
std::cout << std::endl;
}
int Size;
MPI_Comm_size(communicator,&Size);
communicator_halo.resize (2*_ndimension);
for(int i=0;i<_ndimension*2;i++){
MPI_Comm_dup(communicator,&communicator_halo[i]);
}
assert(Size==_Nprocessors);
}
CartesianCommunicator::~CartesianCommunicator()
{
int MPI_is_finalised;
MPI_Finalized(&MPI_is_finalised);
if (communicator && !MPI_is_finalised) {
MPI_Comm_free(&communicator);
for(int i=0;i<communicator_halo.size();i++){
MPI_Comm_free(&communicator_halo[i]);
}
}
}
void CartesianCommunicator::GlobalSum(uint32_t &u){
int ierr=MPI_Allreduce(MPI_IN_PLACE,&u,1,MPI_UINT32_T,MPI_SUM,communicator);
assert(ierr==0);
}
void CartesianCommunicator::GlobalSum(uint64_t &u){
int ierr=MPI_Allreduce(MPI_IN_PLACE,&u,1,MPI_UINT64_T,MPI_SUM,communicator);
assert(ierr==0);
}
void CartesianCommunicator::GlobalSumVector(uint64_t* u,int N){
int ierr=MPI_Allreduce(MPI_IN_PLACE,u,N,MPI_UINT64_T,MPI_SUM,communicator);
assert(ierr==0);
}
void CartesianCommunicator::GlobalXOR(uint32_t &u){
int ierr=MPI_Allreduce(MPI_IN_PLACE,&u,1,MPI_UINT32_T,MPI_BXOR,communicator);
assert(ierr==0);
}
void CartesianCommunicator::GlobalXOR(uint64_t &u){
int ierr=MPI_Allreduce(MPI_IN_PLACE,&u,1,MPI_UINT64_T,MPI_BXOR,communicator);
assert(ierr==0);
}
void CartesianCommunicator::GlobalMax(float &f)
{
int ierr=MPI_Allreduce(MPI_IN_PLACE,&f,1,MPI_FLOAT,MPI_MAX,communicator);
assert(ierr==0);
}
void CartesianCommunicator::GlobalMax(double &d)
{
int ierr = MPI_Allreduce(MPI_IN_PLACE,&d,1,MPI_DOUBLE,MPI_MAX,communicator);
assert(ierr==0);
}
void CartesianCommunicator::GlobalSum(float &f){
int ierr=MPI_Allreduce(MPI_IN_PLACE,&f,1,MPI_FLOAT,MPI_SUM,communicator);
assert(ierr==0);
}
void CartesianCommunicator::GlobalSumVector(float *f,int N)
{
int ierr=MPI_Allreduce(MPI_IN_PLACE,f,N,MPI_FLOAT,MPI_SUM,communicator);
assert(ierr==0);
}
void CartesianCommunicator::GlobalSum(double &d)
{
int ierr = MPI_Allreduce(MPI_IN_PLACE,&d,1,MPI_DOUBLE,MPI_SUM,communicator);
assert(ierr==0);
}
void CartesianCommunicator::GlobalSumVector(double *d,int N)
{
int ierr = MPI_Allreduce(MPI_IN_PLACE,d,N,MPI_DOUBLE,MPI_SUM,communicator);
assert(ierr==0);
}
void CartesianCommunicator::SendToRecvFromBegin(std::vector<CommsRequest_t> &list,
void *xmit,
int dest,
void *recv,
int from,
int bytes,int dir)
{
MPI_Request xrq;
MPI_Request rrq;
assert(dest != _processor);
assert(from != _processor);
int tag;
tag= dir+from*32;
int ierr=MPI_Irecv(recv, bytes, MPI_CHAR,from,tag,communicator,&rrq);
assert(ierr==0);
list.push_back(rrq);
tag= dir+_processor*32;
ierr =MPI_Isend(xmit, bytes, MPI_CHAR,dest,tag,communicator,&xrq);
assert(ierr==0);
list.push_back(xrq);
}
void CartesianCommunicator::CommsComplete(std::vector<CommsRequest_t> &list)
{
int nreq=list.size();
if (nreq==0) return;
std::vector<MPI_Status> status(nreq);
int ierr = MPI_Waitall(nreq,&list[0],&status[0]);
assert(ierr==0);
list.resize(0);
}
// Basic Halo comms primitive
void CartesianCommunicator::SendToRecvFrom(void *xmit,
int dest,
void *recv,
int from,
int bytes)
{
std::vector<CommsRequest_t> reqs(0);
unsigned long xcrc = crc32(0L, Z_NULL, 0);
unsigned long rcrc = crc32(0L, Z_NULL, 0);
int myrank = _processor;
int ierr;
// Enforce no UVM in comms, device or host OK
assert(acceleratorIsCommunicable(xmit));
assert(acceleratorIsCommunicable(recv));
// Give the CPU to MPI immediately; can use threads to overlap optionally
// printf("proc %d SendToRecvFrom %d bytes Sendrecv \n",_processor,bytes);
ierr=MPI_Sendrecv(xmit,bytes,MPI_CHAR,dest,myrank,
recv,bytes,MPI_CHAR,from, from,
communicator,MPI_STATUS_IGNORE);
assert(ierr==0);
// xcrc = crc32(xcrc,(unsigned char *)xmit,bytes);
// rcrc = crc32(rcrc,(unsigned char *)recv,bytes);
// printf("proc %d SendToRecvFrom %d bytes xcrc %lx rcrc %lx\n",_processor,bytes,xcrc,rcrc); fflush
}
// Basic Halo comms primitive
double CartesianCommunicator::StencilSendToRecvFrom( void *xmit,
int dest, int dox,
void *recv,
int from, int dor,
int bytes,int dir)
{
std::vector<CommsRequest_t> list;
double offbytes = StencilSendToRecvFromBegin(list,xmit,dest,dox,recv,from,dor,bytes,bytes,dir);
StencilSendToRecvFromComplete(list,dir);
return offbytes;
}
#undef NVLINK_GET // Define to use get instead of put DMA
double CartesianCommunicator::StencilSendToRecvFromBegin(std::vector<CommsRequest_t> &list,
void *xmit,
int dest,int dox,
void *recv,
int from,int dor,
int xbytes,int rbytes,int dir)
{
int ncomm =communicator_halo.size();
int commdir=dir%ncomm;
MPI_Request xrq;
MPI_Request rrq;
int ierr;
int gdest = ShmRanks[dest];
int gfrom = ShmRanks[from];
int gme = ShmRanks[_processor];
assert(dest != _processor);
assert(from != _processor);
assert(gme == ShmRank);
double off_node_bytes=0.0;
int tag;
if ( dor ) {
if ( (gfrom ==MPI_UNDEFINED) || Stencil_force_mpi ) {
tag= dir+from*32;
ierr=MPI_Irecv(recv, rbytes, MPI_CHAR,from,tag,communicator_halo[commdir],&rrq);
assert(ierr==0);
list.push_back(rrq);
off_node_bytes+=rbytes;
}
#ifdef NVLINK_GET
void *shm = (void *) this->ShmBufferTranslate(from,xmit);
assert(shm!=NULL);
acceleratorCopyDeviceToDeviceAsynch(shm,recv,rbytes);
#endif
}
if (dox) {
// rcrc = crc32(rcrc,(unsigned char *)recv,bytes);
if ( (gdest == MPI_UNDEFINED) || Stencil_force_mpi ) {
tag= dir+_processor*32;
ierr =MPI_Isend(xmit, xbytes, MPI_CHAR,dest,tag,communicator_halo[commdir],&xrq);
assert(ierr==0);
list.push_back(xrq);
off_node_bytes+=xbytes;
} else {
#ifndef NVLINK_GET
void *shm = (void *) this->ShmBufferTranslate(dest,recv);
assert(shm!=NULL);
acceleratorCopyDeviceToDeviceAsynch(xmit,shm,xbytes);
#endif
}
}
return off_node_bytes;
}
void CartesianCommunicator::StencilSendToRecvFromComplete(std::vector<CommsRequest_t> &list,int dir)
{
int nreq=list.size();
acceleratorCopySynchronise();
if (nreq==0) return;
std::vector<MPI_Status> status(nreq);
int ierr = MPI_Waitall(nreq,&list[0],&status[0]);
assert(ierr==0);
list.resize(0);
}
void CartesianCommunicator::StencilBarrier(void)
{
MPI_Barrier (ShmComm);
}
//void CartesianCommunicator::SendToRecvFromComplete(std::vector<CommsRequest_t> &list)
//{
//}
void CartesianCommunicator::Barrier(void)
{
int ierr = MPI_Barrier(communicator);
assert(ierr==0);
}
void CartesianCommunicator::Broadcast(int root,void* data, int bytes)
{
int ierr=MPI_Bcast(data,
bytes,
MPI_BYTE,
root,
communicator);
assert(ierr==0);
}
int CartesianCommunicator::RankWorld(void){
int r;
MPI_Comm_rank(communicator_world,&r);
return r;
}
void CartesianCommunicator::BarrierWorld(void){
int ierr = MPI_Barrier(communicator_world);
assert(ierr==0);
}
void CartesianCommunicator::BroadcastWorld(int root,void* data, int bytes)
{
int ierr= MPI_Bcast(data,
bytes,
MPI_BYTE,
root,
communicator_world);
assert(ierr==0);
}
void CartesianCommunicator::AllToAll(int dim,void *in,void *out,uint64_t words,uint64_t bytes)
{
Coordinate row(_ndimension,1);
assert(dim>=0 && dim<_ndimension);
// Split the communicator
row[dim] = _processors[dim];
int me;
CartesianCommunicator Comm(row,*this,me);
Comm.AllToAll(in,out,words,bytes);
}
void CartesianCommunicator::AllToAll(void *in,void *out,uint64_t words,uint64_t bytes)
{
// MPI is a pain and uses "int" arguments
// 64*64*64*128*16 == 500Million elements of data.
// When 24*4 bytes multiples get 50x 10^9 >>> 2x10^9 Y2K bug.
// (Turns up on 32^3 x 64 Gparity too)
MPI_Datatype object;
int iwords;
int ibytes;
iwords = words;
ibytes = bytes;
assert(words == iwords); // safe to cast to int ?
assert(bytes == ibytes); // safe to cast to int ?
MPI_Type_contiguous(ibytes,MPI_BYTE,&object);
MPI_Type_commit(&object);
MPI_Alltoall(in,iwords,object,out,iwords,object,communicator);
MPI_Type_free(&object);
}
NAMESPACE_END(Grid);

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