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Merge branch 'master' of https://github.com/paboyle/Grid

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Peter Boyle 2015-03-29 21:38:53 +01:00
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5
AUTHORS
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@ -0,0 +1,5 @@
Peter Boyle
Azusa Yamaguchi
Intel Parallel Computing Centre @ Higgs Centre for Theoretical Physics
University of Edinburgh
Scotland, UK

86
INSTALL
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@ -102,9 +102,13 @@ for details on some of the pertinent environment variables.
You can give `configure' initial values for configuration parameters You can give `configure' initial values for configuration parameters
by setting variables in the command line or in the environment. Here by setting variables in the command line or in the environment. Here
is an example: is are examples:
./configure CC=c99 CFLAGS=-g LIBS=-lposix ./configure CXX=clang++ CXXFLAGS="-std=c++11 -O3 -mavx" --enable-simd=AVX1
./configure CXX=clang++ CXXFLAGS="-std=c++11 -O3 -mavx2" --enable-simd=AVX2
./configure CXX=icpc CXXFLAGS="-std=c++11 -O3 -mmic" --enable-simd=AVX512 --host=none
*Note Defining Variables::, for more details. *Note Defining Variables::, for more details.
@ -124,19 +128,6 @@ architecture at a time in the source code directory. After you have
installed the package for one architecture, use `make distclean' before installed the package for one architecture, use `make distclean' before
reconfiguring for another architecture. reconfiguring for another architecture.
On MacOS X 10.5 and later systems, you can create libraries and
executables that work on multiple system types--known as "fat" or
"universal" binaries--by specifying multiple `-arch' options to the
compiler but only a single `-arch' option to the preprocessor. Like
this:
./configure CC="gcc -arch i386 -arch x86_64 -arch ppc -arch ppc64" \
CXX="g++ -arch i386 -arch x86_64 -arch ppc -arch ppc64" \
CPP="gcc -E" CXXCPP="g++ -E"
This is not guaranteed to produce working output in all cases, you
may have to build one architecture at a time and combine the results
using the `lipo' tool if you have problems.
Installation Names Installation Names
================== ==================
@ -218,70 +209,9 @@ overridden with `make V=0'.
Particular systems Particular systems
================== ==================
On HP-UX, the default C compiler is not ANSI C compatible. If GNU Cross compiling for native execution on XeonPhi requires
CC is not installed, it is recommended to use the following options in
order to use an ANSI C compiler:
./configure CC="cc -Ae -D_XOPEN_SOURCE=500" --build=none
and if that doesn't work, install pre-built binaries of GCC for HP-UX.
HP-UX `make' updates targets which have the same time stamps as
their prerequisites, which makes it generally unusable when shipped
generated files such as `configure' are involved. Use GNU `make'
instead.
On OSF/1 a.k.a. Tru64, some versions of the default C compiler cannot
parse its `<wchar.h>' header file. The option `-nodtk' can be used as
a workaround. If GNU CC is not installed, it is therefore recommended
to try
./configure CC="cc"
and if that doesn't work, try
./configure CC="cc -nodtk"
On Solaris, don't put `/usr/ucb' early in your `PATH'. This
directory contains several dysfunctional programs; working variants of
these programs are available in `/usr/bin'. So, if you need `/usr/ucb'
in your `PATH', put it _after_ `/usr/bin'.
On Haiku, software installed for all users goes in `/boot/common',
not `/usr/local'. It is recommended to use the following options:
./configure --prefix=/boot/common
Specifying the System Type
==========================
There may be some features `configure' cannot figure out
automatically, but needs to determine by the type of machine the package
will run on. Usually, assuming the package is built to be run on the
_same_ architectures, `configure' can figure that out, but if it prints
a message saying it cannot guess the machine type, give it the
`--build=TYPE' option. TYPE can either be a short name for the system
type, such as `sun4', or a canonical name which has the form:
CPU-COMPANY-SYSTEM
where SYSTEM can have one of these forms:
OS
KERNEL-OS
See the file `config.sub' for the possible values of each field. If
`config.sub' isn't included in this package, then this package doesn't
need to know the machine type.
If you are _building_ compiler tools for cross-compiling, you should
use the option `--target=TYPE' to select the type of system they will
produce code for.
If you want to _use_ a cross compiler, that generates code for a
platform different from the build platform, you should specify the
"host" platform (i.e., that on which the generated programs will
eventually be run) with `--host=TYPE'.
Sharing Defaults Sharing Defaults
================ ================

42
README
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@ -0,0 +1,42 @@
This library provides data parallel C++ container classes with internal memory layout
that is transformed to map efficiently to SIMD architectures. CSHIFT facilities
are provided, similar to HPF and cmfortran, and user control is given over the mapping of
array indices to both MPI tasks and SIMD processing elements.
* Identically shaped arrays then be processed with perfect data parallelisation.
* Such identically shapped arrays are called conformable arrays.
The transformation is based on the observation that Cartesian array processing involves
identical processing to be performed on different regions of the Cartesian array.
The library will (eventually) both geometrically decompose into MPI tasks and across SIMD lanes.
Data parallel array operations can then be specified with a SINGLE data parallel paradigm, but
optimally use MPI, OpenMP and SIMD parallelism under the hood. This is a significant simplification
for most programmers.
The layout transformations are parametrised by the SIMD vector length. This adapts according to the architecture.
Presently SSE2 (128 bit) AVX, AVX2 (256 bit) and IMCI and AVX512 (512 bit) targets are supported.
These are presented as
vRealF, vRealD, vComplexF, vComplexD
internal vector data types. These may be useful in themselves for other programmers.
The corresponding scalar types are named
RealF, RealD, ComplexF, ComplexD
MPI parallelism is UNIMPLEMENTED and for now only OpenMP and SIMD parallelism is present in the library.
You can give `configure' initial values for configuration parameters
by setting variables in the command line or in the environment. Here
is are examples:
./configure CXX=clang++ CXXFLAGS="-std=c++11 -O3 -mavx" --enable-simd=AVX1
./configure CXX=clang++ CXXFLAGS="-std=c++11 -O3 -mavx2" --enable-simd=AVX2
./configure CXX=icpc CXXFLAGS="-std=c++11 -O3 -mmic" --enable-simd=AVX512 --host=none

43
README.md
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@ -1,2 +1,45 @@
# Grid # Grid
Data parallel C++ mathematical object library Data parallel C++ mathematical object library
This library provides data parallel C++ container classes with internal memory layout
that is transformed to map efficiently to SIMD architectures. CSHIFT facilities
are provided, similar to HPF and cmfortran, and user control is given over the mapping of
array indices to both MPI tasks and SIMD processing elements.
* Identically shaped arrays then be processed with perfect data parallelisation.
* Such identically shapped arrays are called conformable arrays.
The transformation is based on the observation that Cartesian array processing involves
identical processing to be performed on different regions of the Cartesian array.
The library will (eventually) both geometrically decompose into MPI tasks and across SIMD lanes.
Data parallel array operations can then be specified with a SINGLE data parallel paradigm, but
optimally use MPI, OpenMP and SIMD parallelism under the hood. This is a significant simplification
for most programmers.
The layout transformations are parametrised by the SIMD vector length. This adapts according to the architecture.
Presently SSE2 (128 bit) AVX, AVX2 (256 bit) and IMCI and AVX512 (512 bit) targets are supported.
These are presented as
vRealF, vRealD, vComplexF, vComplexD
internal vector data types. These may be useful in themselves for other programmers.
The corresponding scalar types are named
RealF, RealD, ComplexF, ComplexD
MPI parallelism is UNIMPLEMENTED and for now only OpenMP and SIMD parallelism is present in the library.
You can give `configure' initial values for configuration parameters
by setting variables in the command line or in the environment. Here
is are examples:
./configure CXX=clang++ CXXFLAGS="-std=c++11 -O3 -mavx" --enable-simd=AVX1
./configure CXX=clang++ CXXFLAGS="-std=c++11 -O3 -mavx2" --enable-simd=AVX2
./configure CXX=icpc CXXFLAGS="-std=c++11 -O3 -mmic" --enable-simd=AVX512 --host=none