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Author SHA1 Message Date
Ed Bennett
3fa6827e43
Merge 32e6d58356 into 89c0519f83 2024-03-13 10:55:32 +00:00
89c0519f83 Repro test 2024-03-12 16:11:33 +00:00
2704b82084 Merge branch 'develop' of https://github.com/paboyle/Grid into develop 2024-03-12 15:16:24 +00:00
cf8632bbac Britney test option 2024-03-12 15:15:35 +00:00
d224297972 PBS scripts 2024-03-12 15:15:16 +00:00
Peter Boyle
a4d11a630f
Merge pull request #458 from paboyle/fix/HOST_NAME_MAX
fallback to _POSIX_HOST_NAME_MAX if HOST_NAME_MAX is not defined
2024-03-07 07:50:25 -05:00
2b4399f8b1 more HOST_NAME_MAX fix 2024-03-07 15:26:01 +09:00
f17b8de907 fallback to _POSIX_HOST_NAME_MAX if HOST_NAME_MAX is not defined 2024-03-07 15:22:08 +09:00
Peter Boyle
7e5bd46dd3 Booster update 2024-03-06 19:03:45 +01:00
Peter Boyle
228bbb9d81 Benchmark results 2024-03-06 19:03:35 +01:00
b812a7b4c6 Staggered launch script 2024-03-06 01:32:40 +00:00
891a366f73 Repro CG script 2024-03-06 01:22:55 +00:00
10116b3be8 Force device copyable and tell SYCL to shut it. 2024-03-06 01:13:27 +00:00
a46a0f0882 force device copyable and don't take crap from SYCL 2024-03-06 01:12:49 +00:00
a26a8a38f4 Merge branch 'develop' of https://github.com/paboyle/Grid into develop 2024-03-06 00:05:00 +00:00
7435315d50 More blasted shell variables 2024-03-06 00:03:59 +00:00
9b5f741e85 Reproducing CG can be more useful now 2024-03-06 00:03:16 +00:00
517822fdd2 SPR HBM benchmarking right and also PVC batched GEMM 2024-03-06 00:02:27 +00:00
1b93a9be88 Print out the hostname 2024-03-06 00:01:58 +00:00
783a66b348 Deterministic reduction please 2024-03-06 00:01:37 +00:00
976c3e9b59 Hack for flight logging CG inner products.
Can be made to work, but could put in some more serious infrastructure
for repro testing and blame attribution (Britney test) if necessary
2024-03-05 23:59:57 +00:00
f8ca971dae Use of a bare PRECISION macro is not namespace safe and collides with
SYCL
2024-03-05 23:59:13 +00:00
21bc8c24df OneMKL batched blas starting 2024-03-05 23:58:20 +00:00
30228214f7 SYCL conflict with Eigen 2024-03-05 23:56:10 +00:00
Peter Boyle
2ae980ae43
Update sourceme.sh 2024-03-05 13:39:18 -05:00
Peter Boyle
6153dec2e4
Update setup.sh 2024-03-05 13:38:32 -05:00
Peter Boyle
c805f86343 USQCD benchmark 2024-03-01 00:05:04 -05:00
Peter Boyle
04ca065281 Only one rank opens 2024-02-29 20:09:11 -05:00
Peter Boyle
88d8fa43d7 Benchmark development 2024-02-29 20:01:44 -05:00
Peter Boyle
3c49762875 Propagate in the blas routine 2024-02-29 15:33:06 -05:00
Peter Boyle
436bf1d9d3
Merge pull request #455 from clarkedavida/hisq_fat_links
Hisq fat links
2024-02-29 15:29:39 -05:00
david clarke
f70df6e195 changed NO_SHIFT and BACKWARD_CONST from define to enum 2024-02-29 12:29:30 -07:00
Peter Boyle
fce3852dff
Merge pull request #451 from paboyle/feature/eigen-3.4.0-update
updating Eigen to 3.4.0
2024-02-28 18:03:37 -05:00
Peter Boyle
ee1b8bbdbd
Merge pull request #454 from edbennett/adjoint-broke
fix HMC for non-fundamental representations
2024-02-28 14:05:27 -05:00
Peter Boyle
3f1636637d
Merge pull request #453 from dbollweg/feature/sliceSum_gpu
Feature/slice sum gpu
2024-02-28 14:04:43 -05:00
Peter Boyle
2e570f5300
Merge pull request #457 from lehner/feature/gpt
Import GPT-related updates
2024-02-28 13:59:04 -05:00
Christoph Lehner
9f89486df5 remove unnecessary code path 2024-02-28 19:56:23 +01:00
Christoph Lehner
22b43b86cb Make GPT test suite work with SYCL 2024-02-28 12:57:17 +01:00
dbollweg
3c9012676a CUDA cub refuses to reduce vSpinColourMatrix, breaking up into smaller parts like already done for HIP case. 2024-02-27 12:41:45 -05:00
Dennis Bollweg
b507fe209c Added SpinColourMatrix case to sliceSum Test 2024-02-27 11:28:32 -05:00
Dennis Bollweg
6cd2d8fcd5 Replace cuda/hip memcpy with Grid functions 2024-02-26 09:55:07 -05:00
david clarke
b02d022993 fixed race condition (thx michael) 2024-02-23 17:14:28 -07:00
david clarke
94581e3c7a accelerator_for is broken 2024-02-23 15:58:33 -07:00
david clarke
88b52cc045 Merge branch 'develop' into hisq_fat_links 2024-02-23 14:47:15 -07:00
dbollweg
0a816b5509 Merge branch 'feature/sliceSum_gpu' of https://github.com/dbollweg/Grid into feature/sliceSum_gpu 2024-02-22 21:43:06 -05:00
dbollweg
1c8b807c2e free malloc'd memory 2024-02-22 21:42:44 -05:00
Christoph Lehner
66391f84f2 Merge branch 'feature/gpt' of ../Grid into develop 2024-02-21 19:05:00 +01:00
Ed Bennett
97f7a9ecb3 fix HMC for non-fundamental representations 2024-02-21 08:27:55 +00:00
Dennis Bollweg
15878f7613 sliceSumReduction_cub_large now also faster than CPU on Frontier 2024-02-16 13:55:21 -05:00
dbollweg
e0d5e3c6c7
Merge branch 'paboyle:develop' into feature/sliceSum_gpu 2024-02-16 13:16:37 -05:00
dbollweg
6f3455900e Adding sliceSumReduction_cub_small/large since hipcub cannot deal with arb. large vobjs 2024-02-16 13:15:02 -05:00
david clarke
56827d6ad6 accelerator_inline bug 2024-02-14 13:56:57 -07:00
e4a641b64e removing old Eigen tensor patch 2024-02-13 10:37:14 +01:00
8849f187f1 updating Eigen to 3.4.0 2024-02-13 10:30:22 +01:00
david clarke
db420525b3 fix Simd::Nsimd typo 2024-02-12 15:03:53 -07:00
dbollweg
b5659d106e more test cases 2024-02-09 13:37:14 -05:00
dbollweg
4b43307402 Undo include path changes for level zero api header 2024-02-09 13:07:56 -05:00
dbollweg
09af8c25a2
Merge branch 'paboyle:develop' into feature/sliceSum_gpu 2024-02-09 13:02:59 -05:00
dbollweg
9514035b87 refactor slicesum: slicesum uses GPU version by default now 2024-02-09 13:02:28 -05:00
david clarke
2da09ae99b acceleration compiles and doesn't break scalar mode 2024-02-06 18:40:13 -07:00
david clarke
a38fb0e04a first effort toward accelerators 2024-02-06 18:24:55 -07:00
dbollweg
1514b4f137 slicesum_sycl passes test 2024-02-06 19:08:44 -05:00
david clarke
0a6e2f42c5 small amount of cleanup 2024-02-06 16:32:07 -07:00
dbollweg
ab2de131bd work towards sliceSum for sycl backend 2024-02-06 13:24:45 -05:00
Dennis Bollweg
5af8da76d7 Fix cuda compilation of Lattice_slicesum_gpu.h 2024-02-01 18:02:30 -05:00
Dennis Bollweg
b8b9dc952d Async memcpy's and cleanup 2024-02-01 17:55:35 -05:00
Dennis Bollweg
79a6ed32d8 Use accelerator_for2d and DeviceSegmentedRecude to avoid kernel launch latencies 2024-02-01 16:41:03 -05:00
dbollweg
caa5f97723 Add sliceSum gpu using cub/hipcub 2024-01-31 16:50:06 -05:00
david clarke
4924b3209e projectU3 yields a unitary matrix 2024-01-23 14:43:58 -07:00
david clarke
00f24f8765 already found some bugs in projection, still needs testing 2024-01-22 05:50:16 -07:00
david clarke
f5b3d582b0 first attempt at U3 projection 2024-01-22 02:49:40 -07:00
david clarke
981c93d67a update Test_fatLinks to accept Naik 2024-01-21 21:09:19 -07:00
david clarke
c020b78e02 Merge branch 'develop' into hisq_fat_links 2024-01-21 20:21:08 -07:00
david clarke
9cd4128833 fix naik bug 2023-11-03 14:11:38 -06:00
david clarke
c8b17c9526 Naik to CShift 2023-11-02 12:43:22 -06:00
david clarke
2ae2a81e85 attempt to fix Naik 2023-10-31 13:54:55 -06:00
david clarke
69c869d345 fixed stupid typo 2023-10-30 17:41:52 -06:00
david clarke
df9b958c40 naik now returns separately 2023-10-30 17:40:53 -06:00
david clarke
3d3376d1a3 LePage works, trying Naik 2023-10-27 16:26:31 -06:00
Christoph Lehner
f2648e94b9 getHostPointer added to Lattice 2023-10-23 13:47:41 +02:00
david clarke
21ed6ac0f4 added floating-point support 2023-10-20 13:54:26 -06:00
david clarke
7bb8ab7000 improve smearing templating 2023-10-20 08:41:02 -06:00
david clarke
2c824c2641 Merge branch 'develop' into hisq_fat_links 2023-10-17 16:03:59 -06:00
david clarke
391fd9cc6a try lepage term 2023-10-17 14:57:15 -06:00
david clarke
bf4369f72d clean up HISQSmear with decltypes 2023-10-12 12:41:06 -06:00
david clarke
36600899e2 working 7-link; Grid_log; generalShift 2023-10-12 11:11:39 -06:00
david clarke
b9c70d156b Merge branch 'develop' into hisq_fat_links 2023-10-10 22:44:17 -06:00
david clarke
eb89579fe7 Merge remote-tracking branch 'origin/develop' into develop 2023-10-10 22:43:51 -06:00
david clarke
0cfd13d18b 7-link working 2023-10-10 22:41:52 -06:00
Christoph Lehner
e6ed516052 merged 2023-10-08 09:00:37 +02:00
Christoph Lehner
e2a3dae1f2 Option for multiple simultaneous CartesianStencils 2023-10-08 08:58:44 +02:00
david clarke
63d9b8e8a3 Merge remote-tracking branch 'origin/develop' into hisq_fat_links 2023-09-16 23:20:31 -06:00
david clarke
d247031c98 try 7-link 2023-09-16 23:18:16 -06:00
david clarke
affff3865f Merge branch 'develop' into hisq_fat_links 2023-08-11 23:08:04 -06:00
david clarke
9c22655b5a Merge remote-tracking branch 'origin/develop' into develop 2023-08-11 23:06:42 -06:00
david clarke
99d879ea7f 5-link first attempt 2023-08-11 22:56:30 -06:00
david clarke
9d263d9a7d fix bug in HISQSmearing; move benchmark b/c i don't understand how makefiles work 2023-06-28 10:05:34 -06:00
david clarke
9015c229dc add benchmark to see whether matrix multiplication is slower than read from object 2023-06-27 21:28:26 -06:00
david clarke
a7eabaad56 rudimentary appendShift convenience method, which allows the user to append an arbitrary shift in one line 2023-06-26 23:59:28 -06:00
david clarke
eeb4703b84 develop wrappers to make the stencils easier to construct 2023-06-26 17:45:35 -06:00
david clarke
a07421b3d3 Merge branch 'develop' into hisq_fat_links 2023-06-26 13:51:32 -06:00
david clarke
cda53b4068 Merge remote-tracking branch 'origin/develop' into develop 2023-06-26 13:51:06 -06:00
david clarke
df99f227c1 include missing staple orientations; invert path direction, which was backwards 2023-06-22 14:57:10 -06:00
david clarke
d536c67b9d add HISQSmearing to Smearing.h 2023-06-20 16:04:48 -06:00
david clarke
f44f005dad rename _lvl1 --> _linkTreatment 2023-06-20 15:48:27 -06:00
david clarke
26b2caf570 add template parameter to Smear_HISQ_fat for MILC interfacing 2023-06-20 15:37:54 -06:00
david clarke
8bb078db25 Merge branch 'develop' into hisq_fat_links 2023-06-20 13:05:00 -06:00
david clarke
b61ba40023 Merge remote-tracking branch 'origin/develop' into develop 2023-06-20 13:04:53 -06:00
Christoph Lehner
452bf2e907 Accelerator basisRotate also on HIP 2023-06-20 20:36:24 +03:00
david clarke
14d352ea4f added smearParams struct 2023-06-12 16:55:44 -06:00
david clarke
1cf9ec1cce now compiles 2023-06-09 16:27:45 -06:00
david clarke
4b994a1bc7 trouble with compilation 2023-06-08 17:37:25 -06:00
david clarke
e506d6d369 Merge branch 'develop' into hisq_fat_links 2023-06-07 21:16:20 -06:00
david clarke
ab56ad8d7a fix 3-link stencil 2023-06-07 21:14:58 -06:00
Christoph Lehner
e8c29e2fe5
Merge pull request #31 from paboyle/develop
Sync
2023-05-28 16:13:12 +02:00
david clarke
3825329f8e Merge branch 'develop' into hisq_fat_links 2023-05-24 15:37:25 -06:00
david clarke
c7bdf2c0e4 3-link test at least gives an answer 2023-05-21 04:33:20 -06:00
Christoph Lehner
da9cbfc7cc
Suppress BuildSurfaceList verbosity in Stencil.h 2023-05-19 20:22:20 +02:00
Christoph Lehner
6b9f07c1ed
Merge pull request #30 from paboyle/develop
Merge upstream
2023-05-19 20:20:58 +02:00
david clarke
bf91778550 verbose plaquette example; fat link test frame 2023-05-17 15:15:54 -06:00
Christoph Lehner
5f75735dab Add M and Mdag to WilsonTMFermion 2023-04-06 18:25:05 +02:00
Ed Bennett
32e6d58356 use accelerator for setCheckerboard in RHMC 2021-12-22 23:43:43 +00:00
52 changed files with 3746 additions and 281 deletions

4
.gitignore vendored
View File

@ -1,3 +1,7 @@
# Doxygen stuff
html/*
latex/*
# Compiled Object files #
#########################
*.slo

View File

@ -34,7 +34,7 @@
#pragma push_macro("__SYCL_DEVICE_ONLY__")
#undef __SYCL_DEVICE_ONLY__
#define EIGEN_DONT_VECTORIZE
//#undef EIGEN_USE_SYCL
#undef EIGEN_USE_SYCL
#define __SYCL__REDEFINE__
#endif

View File

@ -293,7 +293,7 @@ static void sncndnFK(INTERNAL_PRECISION u, INTERNAL_PRECISION k,
* 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(PRECISION epsilon, int n, int type) {
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;
@ -375,12 +375,12 @@ zolotarev_data* zolotarev(PRECISION epsilon, int n, int type) {
construct_partfrac(d);
construct_contfrac(d);
/* Converting everything to PRECISION for external use only */
/* Converting everything to ZOLO_PRECISION for external use only */
zd = (zolotarev_data*) malloc(sizeof(zolotarev_data));
zd -> A = (PRECISION) d -> A;
zd -> Delta = (PRECISION) d -> Delta;
zd -> epsilon = (PRECISION) d -> epsilon;
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;
@ -390,24 +390,24 @@ zolotarev_data* zolotarev(PRECISION epsilon, int n, int type) {
zd -> deg_num = d -> deg_num;
zd -> deg_denom = d -> deg_denom;
zd -> a = (PRECISION*) malloc(zd -> dn * sizeof(PRECISION));
for (m = 0; m < zd -> dn; m++) zd -> a[m] = (PRECISION) d -> a[m];
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 = (PRECISION*) malloc(zd -> dd * sizeof(PRECISION));
for (m = 0; m < zd -> dd; m++) zd -> ap[m] = (PRECISION) d -> ap[m];
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 = (PRECISION*) malloc(zd -> da * sizeof(PRECISION));
for (m = 0; m < zd -> da; m++) zd -> alpha[m] = (PRECISION) d -> alpha[m];
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 = (PRECISION*) malloc(zd -> db * sizeof(PRECISION));
for (m = 0; m < zd -> db; m++) zd -> beta[m] = (PRECISION) d -> beta[m];
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 = (PRECISION*) malloc(zd -> n * sizeof(PRECISION));
for (m = 0; m < zd -> n; m++) zd -> gamma[m] = (PRECISION) d -> gamma[m];
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);
@ -426,7 +426,7 @@ void zolotarev_free(zolotarev_data *zdata)
}
zolotarev_data* higham(PRECISION epsilon, int n) {
zolotarev_data* higham(ZOLO_PRECISION epsilon, int n) {
INTERNAL_PRECISION A, M, c, cp, z, z0, t, epssq;
int m, czero;
zolotarev_data *zd;
@ -481,9 +481,9 @@ zolotarev_data* higham(PRECISION epsilon, int n) {
/* Converting everything to PRECISION for external use only */
zd = (zolotarev_data*) malloc(sizeof(zolotarev_data));
zd -> A = (PRECISION) d -> A;
zd -> Delta = (PRECISION) d -> Delta;
zd -> epsilon = (PRECISION) d -> epsilon;
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;
@ -493,24 +493,24 @@ zolotarev_data* higham(PRECISION epsilon, int n) {
zd -> deg_num = d -> deg_num;
zd -> deg_denom = d -> deg_denom;
zd -> a = (PRECISION*) malloc(zd -> dn * sizeof(PRECISION));
for (m = 0; m < zd -> dn; m++) zd -> a[m] = (PRECISION) d -> a[m];
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 = (PRECISION*) malloc(zd -> dd * sizeof(PRECISION));
for (m = 0; m < zd -> dd; m++) zd -> ap[m] = (PRECISION) d -> ap[m];
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 = (PRECISION*) malloc(zd -> da * sizeof(PRECISION));
for (m = 0; m < zd -> da; m++) zd -> alpha[m] = (PRECISION) d -> alpha[m];
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 = (PRECISION*) malloc(zd -> db * sizeof(PRECISION));
for (m = 0; m < zd -> db; m++) zd -> beta[m] = (PRECISION) d -> beta[m];
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 = (PRECISION*) malloc(zd -> n * sizeof(PRECISION));
for (m = 0; m < zd -> n; m++) zd -> gamma[m] = (PRECISION) d -> gamma[m];
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);
@ -523,17 +523,17 @@ NAMESPACE_END(Grid);
#ifdef TEST
#undef ZERO
#define ZERO ((PRECISION) 0)
#define ZERO ((ZOLO_PRECISION) 0)
#undef ONE
#define ONE ((PRECISION) 1)
#define ONE ((ZOLO_PRECISION) 1)
#undef TWO
#define TWO ((PRECISION) 2)
#define TWO ((ZOLO_PRECISION) 2)
/* Evaluate the rational approximation R(x) using the factored form */
static PRECISION zolotarev_eval(PRECISION x, zolotarev_data* rdata) {
static ZOLO_PRECISION zolotarev_eval(ZOLO_PRECISION x, zolotarev_data* rdata) {
int m;
PRECISION R;
ZOLO_PRECISION R;
if (rdata -> type == 0) {
R = rdata -> A * x;
@ -551,9 +551,9 @@ static PRECISION zolotarev_eval(PRECISION x, zolotarev_data* rdata) {
/* Evaluate the rational approximation R(x) using the partial fraction form */
static PRECISION zolotarev_partfrac_eval(PRECISION x, zolotarev_data* rdata) {
static ZOLO_PRECISION zolotarev_partfrac_eval(ZOLO_PRECISION x, zolotarev_data* rdata) {
int m;
PRECISION R = rdata -> alpha[rdata -> da - 1];
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);
@ -568,18 +568,18 @@ static PRECISION zolotarev_partfrac_eval(PRECISION x, zolotarev_data* rdata) {
* 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 PRECISION zolotarev_contfrac_eval(PRECISION x, zolotarev_data* rdata) {
static ZOLO_PRECISION zolotarev_contfrac_eval(ZOLO_PRECISION x, zolotarev_data* rdata) {
int m;
PRECISION R = rdata -> beta[0] * x;
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 PRECISION zolotarev_cayley_eval(PRECISION x, zolotarev_data* rdata) {
static ZOLO_PRECISION zolotarev_cayley_eval(ZOLO_PRECISION x, zolotarev_data* rdata) {
int m;
PRECISION T;
ZOLO_PRECISION T;
T = rdata -> type == 0 ? ONE : -ONE;
for (m = 0; m < rdata -> n; m++)
@ -607,7 +607,7 @@ 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;
PRECISION y;
ZOLO_PRECISION y;
FILE *plot_function, *plot_error,
*plot_partfrac, *plot_contfrac, *plot_cayley;
@ -626,13 +626,13 @@ int main(int argc, char** argv) {
}
rdata = type == 2
? higham((PRECISION) eps, n)
: zolotarev((PRECISION) eps, n, type);
? 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)
"\tPRECISION = " STRINGIFY(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",
@ -681,15 +681,15 @@ int main(int argc, char** argv) {
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((PRECISION) x, rdata);
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((PRECISION) x, rdata) - y)
ypferr = (float)((zolotarev_partfrac_eval((ZOLO_PRECISION) x, rdata) - y)
/ rdata -> Delta);
ycferr = (float)((zolotarev_contfrac_eval((PRECISION) x, rdata) - y)
ycferr = (float)((zolotarev_contfrac_eval((ZOLO_PRECISION) x, rdata) - y)
/ rdata -> Delta);
ycaylerr = (float)((zolotarev_cayley_eval((PRECISION) x, rdata) - y)
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));

View File

@ -9,10 +9,10 @@ NAMESPACE_BEGIN(Approx);
#define HVERSION Header Time-stamp: <14-OCT-2004 09:26:51.00 adk@MISSCONTRARY>
#ifndef ZOLOTAREV_INTERNAL
#ifndef PRECISION
#define PRECISION double
#ifndef ZOLO_PRECISION
#define ZOLO_PRECISION double
#endif
#define ZPRECISION PRECISION
#define ZPRECISION ZOLO_PRECISION
#define ZOLOTAREV_DATA zolotarev_data
#endif
@ -77,8 +77,8 @@ typedef struct {
* zolotarev_data structure. The arguments must satisfy the constraints that
* epsilon > 0, n > 0, and type = 0 or 1. */
ZOLOTAREV_DATA* higham(PRECISION epsilon, int n) ;
ZOLOTAREV_DATA* zolotarev(PRECISION epsilon, int n, int type);
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
@ -86,3 +86,4 @@ void zolotarev_free(zolotarev_data *zdata);
NAMESPACE_END(Approx);
NAMESPACE_END(Grid);
#endif

View File

@ -0,0 +1,34 @@
/*************************************************************************************
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);

View File

@ -0,0 +1,727 @@
/*************************************************************************************
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::cpu_selector selector;
cl::sycl::device selectedDevice { selector };
gridblasHandle =new sycl::queue (selectedDevice);
#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);
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
//MKLs cblas_<T>gemm_batch & OneAPI
#warning "oneMKL implementation not built "
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
// Need a default/reference implementation
int sda = lda*k;
int sdb = ldb*k;
int sdc = ldc*n;
for (int p = 0; p < batchCount; ++p) {
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)
c_mn += Amk[p][mm + kk*lda ] * Bkn[p][kk + nn*ldb];
Cmn[p][mm + nn*ldc] = (alpha)*c_mn + (beta)*Cmn[p][mm + nn*ldc ];
}
}
}
#endif
// synchronise();
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();
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
//MKLs cblas_<T>gemm_batch & OneAPI
#warning "oneMKL implementation not built "
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
int sda = lda*k;
int sdb = ldb*k;
int sdc = ldc*n;
ComplexF alphaf(real(alpha),imag(alpha));
ComplexF betaf(real(beta),imag(beta));
// Need a default/reference implementation
for (int p = 0; p < batchCount; ++p) {
for (int mm = 0; mm < m; ++mm) {
for (int nn = 0; nn < n; ++nn) {
ComplexF c_mn(0.0);
for (int kk = 0; kk < k; ++kk)
c_mn += Amk[p][mm + kk*lda ] * Bkn[p][kk + nn*ldb];
Cmn[p][mm + nn*ldc] = (alphaf)*c_mn + (betaf)*Cmn[p][mm + nn*ldc ];
}
}
}
#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();
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
//MKLs cblas_<T>gemm_batch & OneAPI
#warning "oneMKL implementation not built "
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
int sda = lda*k;
int sdb = ldb*k;
int sdc = ldc*n;
// Need a default/reference implementation
for (int p = 0; p < batchCount; ++p) {
for (int mm = 0; mm < m; ++mm) {
for (int nn = 0; nn < n; ++nn) {
RealD c_mn(0.0);
for (int kk = 0; kk < k; ++kk)
c_mn += Amk[p][mm + kk*lda ] * Bkn[p][kk + nn*ldb];
Cmn[p][mm + nn*ldc] = (alpha)*c_mn + (beta)*Cmn[p][mm + nn*ldc ];
}
}
}
#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();
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 batchCount64=batchCount;
oneapi::mkl::blas::column_major::gemm_batch(*theGridAccelerator,
onemkl::transpose::N,
onemkl::transpose::N,
&m64,&n64,&k64,
(double *) &alpha_p[0],
(double **)&Amk[0], lda,
(double **)&Bkn[0], ldb,
(double *) &beta_p[0],
(double **)&Cmn[0], ldc,
1,&batchCount64);
*/
//MKLs cblas_<T>gemm_batch & OneAPI
#warning "oneMKL implementation not built "
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
int sda = lda*k;
int sdb = ldb*k;
int sdc = ldc*n;
// Need a default/reference implementation
for (int p = 0; p < batchCount; ++p) {
for (int mm = 0; mm < m; ++mm) {
for (int nn = 0; nn < n; ++nn) {
RealD c_mn(0.0);
for (int kk = 0; kk < k; ++kk)
c_mn += Amk[p][mm + kk*lda ] * Bkn[p][kk + nn*ldb];
Cmn[p][mm + nn*ldc] = (alpha)*c_mn + (beta)*Cmn[p][mm + nn*ldc ];
}
}
}
#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;
}
////////////////////////////////////////////////////////////////////////////////////////////////
// Strided case used by benchmark, but generally unused in Grid
// Keep a code example in double complex, but don't generate the single and real variants for now
////////////////////////////////////////////////////////////////////////////////////////////////
void gemmStridedBatched(int m,int n, int k,
ComplexD alpha,
ComplexD* Amk, // pointer list to matrices
ComplexD* Bkn,
ComplexD beta,
ComplexD* Cmn,
int batchCount)
{
// Use C-row major storage, so transpose calls
int lda = m; // m x k column major
int ldb = k; // k x n column major
int ldc = m; // m x b column major
int sda = m*k;
int sdb = k*n;
int sdc = m*n;
deviceVector<ComplexD> alpha_p(1);
deviceVector<ComplexD> beta_p(1);
acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(ComplexD));
acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(ComplexD));
// std::cout << "blasZgemmStridedBatched mnk "<<m<<","<<n<<","<<k<<" count "<<batchCount<<std::endl;
// std::cout << "blasZgemmStridedBatched ld "<<lda<<","<<ldb<<","<<ldc<<std::endl;
// std::cout << "blasZgemmStridedBatched sd "<<sda<<","<<sdb<<","<<sdc<<std::endl;
#ifdef GRID_HIP
auto err = hipblasZgemmStridedBatched(gridblasHandle,
HIPBLAS_OP_N,
HIPBLAS_OP_N,
m,n,k,
(hipblasDoubleComplex *) &alpha_p[0],
(hipblasDoubleComplex *) Amk, lda, sda,
(hipblasDoubleComplex *) Bkn, ldb, sdb,
(hipblasDoubleComplex *) &beta_p[0],
(hipblasDoubleComplex *) Cmn, ldc, sdc,
batchCount);
assert(err==HIPBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_CUDA
cublasZgemmStridedBatched(gridblasHandle,
CUBLAS_OP_N,
CUBLAS_OP_N,
m,n,k,
(cuDoubleComplex *) &alpha_p[0],
(cuDoubleComplex *) Amk, lda, sda,
(cuDoubleComplex *) Bkn, ldb, sdb,
(cuDoubleComplex *) &beta_p[0],
(cuDoubleComplex *) Cmn, ldc, sdc,
batchCount);
#endif
#if defined(GRID_SYCL) || defined(GRID_ONE_MKL)
oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
oneapi::mkl::transpose::N,
oneapi::mkl::transpose::N,
m,n,k,
alpha,
(const ComplexD *)Amk,lda,sda,
(const ComplexD *)Bkn,ldb,sdb,
beta,
(ComplexD *)Cmn,ldc,sdc,
batchCount);
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP) && !defined(GRID_ONE_MKL)
// Need a default/reference implementation
for (int p = 0; p < batchCount; ++p) {
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)
c_mn += Amk[mm + kk*lda + p*sda] * Bkn[kk + nn*ldb + p*sdb];
Cmn[mm + nn*ldc + p*sdc] = (alpha)*c_mn + (beta)*Cmn[mm + nn*ldc + p*sdc];
}
}
}
#endif
}
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<ComplexD> A(N_A); acceleratorMemSet(&A[0],0,N_A*sizeof(ComplexD));
deviceVector<ComplexD> B(N_B); acceleratorMemSet(&B[0],0,N_B*sizeof(ComplexD));
deviceVector<ComplexD> C(N_C); acceleratorMemSet(&C[0],0,N_C*sizeof(ComplexD));
ComplexD alpha(1.0);
ComplexD beta (1.0);
RealD flops = 8.0*M*N*K*BATCH;
int ncall=10;
RealD t0 = usecond();
for(int i=0;i<ncall;i++){
gemmStridedBatched(M,N,K,
alpha,
&A[0], // m x k
&B[0], // k x n
beta,
&C[0], // m x n
BATCH);
}
synchronise();
RealD t1 = usecond();
RealD bytes = 1.0*sizeof(ComplexD)*(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);

View File

@ -176,6 +176,7 @@ template<class T> using cshiftAllocator = std::allocator<T>;
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> >;
NAMESPACE_END(Grid);

View File

@ -35,6 +35,7 @@ Author: Peter Boyle <paboyle@ph.ed.ac.uk>
#include <Grid/lattice/Lattice_transpose.h>
#include <Grid/lattice/Lattice_local.h>
#include <Grid/lattice/Lattice_reduction.h>
#include <Grid/lattice/Lattice_crc.h>
#include <Grid/lattice/Lattice_peekpoke.h>
#include <Grid/lattice/Lattice_reality.h>
#include <Grid/lattice/Lattice_real_imag.h>
@ -46,5 +47,4 @@ Author: Peter Boyle <paboyle@ph.ed.ac.uk>
#include <Grid/lattice/Lattice_unary.h>
#include <Grid/lattice/Lattice_transfer.h>
#include <Grid/lattice/Lattice_basis.h>
#include <Grid/lattice/Lattice_crc.h>
#include <Grid/lattice/PaddedCell.h>

View File

@ -62,7 +62,7 @@ void basisRotate(VField &basis,Matrix& Qt,int j0, int j1, int k0,int k1,int Nm)
basis_v.push_back(basis[k].View(AcceleratorWrite));
}
#if ( (!defined(GRID_CUDA)) )
#if ( !(defined(GRID_CUDA) || defined(GRID_HIP) || defined(GRID_SYCL)) )
int max_threads = thread_max();
Vector < vobj > Bt(Nm * max_threads);
thread_region

View File

@ -42,13 +42,13 @@ template<class vobj> void DumpSliceNorm(std::string s,Lattice<vobj> &f,int mu=-1
}
}
template<class vobj> uint32_t crc(Lattice<vobj> & buf)
template<class vobj> uint32_t crc(const Lattice<vobj> & buf)
{
autoView( buf_v , buf, CpuRead);
return ::crc32(0L,(unsigned char *)&buf_v[0],(size_t)sizeof(vobj)*buf.oSites());
}
#define CRC(U) std::cout << "FingerPrint "<<__FILE__ <<" "<< __LINE__ <<" "<< #U <<" "<<crc(U)<<std::endl;
#define CRC(U) std::cerr << "FingerPrint "<<__FILE__ <<" "<< __LINE__ <<" "<< #U <<" "<<crc(U)<<std::endl;
NAMESPACE_END(Grid);

View File

@ -31,6 +31,7 @@ Author: Christoph Lehner <christoph@lhnr.de>
#if defined(GRID_SYCL)
#include <Grid/lattice/Lattice_reduction_sycl.h>
#endif
#include <Grid/lattice/Lattice_slicesum_core.h>
NAMESPACE_BEGIN(Grid);
@ -280,11 +281,14 @@ inline ComplexD rankInnerProduct(const Lattice<vobj> &left,const Lattice<vobj> &
return nrm;
}
template<class vobj>
inline ComplexD innerProduct(const Lattice<vobj> &left,const Lattice<vobj> &right) {
GridBase *grid = left.Grid();
ComplexD nrm = rankInnerProduct(left,right);
// GridNormLog(real(nrm)); // Could log before and after global sum to distinguish local and MPI
grid->GlobalSum(nrm);
// GridNormLog(real(nrm));
return nrm;
}
@ -448,19 +452,10 @@ template<class vobj> inline void sliceSum(const Lattice<vobj> &Data,std::vector<
int e1= grid->_slice_nblock[orthogdim];
int e2= grid->_slice_block [orthogdim];
int stride=grid->_slice_stride[orthogdim];
// sum over reduced dimension planes, breaking out orthog dir
// Parallel over orthog direction
autoView( Data_v, Data, CpuRead);
thread_for( r,rd, {
int so=r*grid->_ostride[orthogdim]; // base offset for start of plane
for(int n=0;n<e1;n++){
for(int b=0;b<e2;b++){
int ss= so+n*stride+b;
lvSum[r]=lvSum[r]+Data_v[ss];
}
}
});
int ostride=grid->_ostride[orthogdim];
//Reduce Data down to lvSum
sliceSumReduction(Data,lvSum,rd, e1,e2,stride,ostride,Nsimd);
// Sum across simd lanes in the plane, breaking out orthog dir.
Coordinate icoor(Nd);
@ -504,6 +499,7 @@ sliceSum(const Lattice<vobj> &Data,int orthogdim)
return result;
}
template<class vobj>
static void sliceInnerProductVector( std::vector<ComplexD> & result, const Lattice<vobj> &lhs,const Lattice<vobj> &rhs,int orthogdim)
{

View File

@ -411,7 +411,7 @@ public:
std::cout << GridLogMessage << "Seed SHA256: " << GridChecksum::sha256_string(seeds) << std::endl;
SeedFixedIntegers(seeds);
}
void SeedFixedIntegers(const std::vector<int> &seeds){
void SeedFixedIntegers(const std::vector<int> &seeds, int britney=0){
// Everyone generates the same seed_seq based on input seeds
CartesianCommunicator::BroadcastWorld(0,(void *)&seeds[0],sizeof(int)*seeds.size());
@ -428,7 +428,6 @@ public:
// MT implementation does not implement fast discard even though
// in principle this is possible
////////////////////////////////////////////////
#if 1
thread_for( lidx, _grid->lSites(), {
int gidx;
@ -449,29 +448,12 @@ public:
int l_idx=generator_idx(o_idx,i_idx);
_generators[l_idx] = master_engine;
Skip(_generators[l_idx],gidx); // Skip to next RNG sequence
});
#else
// Everybody loops over global volume.
thread_for( gidx, _grid->_gsites, {
// Where is it?
int rank;
int o_idx;
int i_idx;
Coordinate gcoor;
_grid->GlobalIndexToGlobalCoor(gidx,gcoor);
_grid->GlobalCoorToRankIndex(rank,o_idx,i_idx,gcoor);
// If this is one of mine we take it
if( rank == _grid->ThisRank() ){
int l_idx=generator_idx(o_idx,i_idx);
_generators[l_idx] = master_engine;
if ( britney ) {
Skip(_generators[l_idx],l_idx); // Skip to next RNG sequence
} else {
Skip(_generators[l_idx],gidx); // Skip to next RNG sequence
}
});
#endif
#else
////////////////////////////////////////////////////////////////
// Machine and thread decomposition dependent seeding is efficient

View File

@ -0,0 +1,213 @@
#pragma once
#include <type_traits>
#if defined(GRID_CUDA)
#include <cub/cub.cuh>
#define gpucub cub
#define gpuError_t cudaError_t
#define gpuSuccess cudaSuccess
#elif defined(GRID_HIP)
#include <hipcub/hipcub.hpp>
#define gpucub hipcub
#define gpuError_t hipError_t
#define gpuSuccess hipSuccess
#endif
NAMESPACE_BEGIN(Grid);
#if defined(GRID_CUDA) || defined(GRID_HIP)
template<class vobj> inline void sliceSumReduction_cub_small(const vobj *Data, Vector<vobj> &lvSum, const int rd, const int e1, const int e2, const int stride, const int ostride, const int Nsimd) {
size_t subvol_size = e1*e2;
commVector<vobj> reduction_buffer(rd*subvol_size);
auto rb_p = &reduction_buffer[0];
vobj zero_init;
zeroit(zero_init);
void *temp_storage_array = NULL;
size_t temp_storage_bytes = 0;
vobj *d_out;
int* d_offsets;
std::vector<int> offsets(rd+1,0);
for (int i = 0; i < offsets.size(); i++) {
offsets[i] = i*subvol_size;
}
//Allocate memory for output and offset arrays on device
d_out = static_cast<vobj*>(acceleratorAllocDevice(rd*sizeof(vobj)));
d_offsets = static_cast<int*>(acceleratorAllocDevice((rd+1)*sizeof(int)));
//copy offsets to device
acceleratorCopyToDeviceAsync(&offsets[0],d_offsets,sizeof(int)*(rd+1),computeStream);
gpuError_t gpuErr = gpucub::DeviceSegmentedReduce::Reduce(temp_storage_array, temp_storage_bytes, rb_p,d_out, rd, d_offsets, d_offsets+1, ::gpucub::Sum(), zero_init, computeStream);
if (gpuErr!=gpuSuccess) {
std::cout << GridLogError << "Lattice_slicesum_gpu.h: Encountered error during gpucub::DeviceSegmentedReduce::Reduce (setup)! Error: " << gpuErr <<std::endl;
exit(EXIT_FAILURE);
}
//allocate memory for temp_storage_array
temp_storage_array = acceleratorAllocDevice(temp_storage_bytes);
//prepare buffer for reduction
//use non-blocking accelerator_for to avoid syncs (ok because we submit to same computeStream)
//use 2d accelerator_for to avoid launch latencies found when serially looping over rd
accelerator_for2dNB( s,subvol_size, r,rd, Nsimd,{
int n = s / e2;
int b = s % e2;
int so=r*ostride; // base offset for start of plane
int ss= so+n*stride+b;
coalescedWrite(rb_p[r*subvol_size+s], coalescedRead(Data[ss]));
});
//issue segmented reductions in computeStream
gpuErr = gpucub::DeviceSegmentedReduce::Reduce(temp_storage_array, temp_storage_bytes, rb_p, d_out, rd, d_offsets, d_offsets+1,::gpucub::Sum(), zero_init, computeStream);
if (gpuErr!=gpuSuccess) {
std::cout << GridLogError << "Lattice_slicesum_gpu.h: Encountered error during gpucub::DeviceSegmentedReduce::Reduce! Error: " << gpuErr <<std::endl;
exit(EXIT_FAILURE);
}
acceleratorCopyFromDeviceAsync(d_out,&lvSum[0],rd*sizeof(vobj),computeStream);
//sync after copy
accelerator_barrier();
acceleratorFreeDevice(temp_storage_array);
acceleratorFreeDevice(d_out);
acceleratorFreeDevice(d_offsets);
}
template<class vobj> inline void sliceSumReduction_cub_large(const vobj *Data, Vector<vobj> &lvSum, const int rd, const int e1, const int e2, const int stride, const int ostride, const int Nsimd) {
typedef typename vobj::vector_type vector;
const int words = sizeof(vobj)/sizeof(vector);
const int osites = rd*e1*e2;
commVector<vector>buffer(osites);
vector *dat = (vector *)Data;
vector *buf = &buffer[0];
Vector<vector> lvSum_small(rd);
vector *lvSum_ptr = (vector *)&lvSum[0];
for (int w = 0; w < words; w++) {
accelerator_for(ss,osites,1,{
buf[ss] = dat[ss*words+w];
});
sliceSumReduction_cub_small(buf,lvSum_small,rd,e1,e2,stride, ostride,Nsimd);
for (int r = 0; r < rd; r++) {
lvSum_ptr[w+words*r]=lvSum_small[r];
}
}
}
template<class vobj> inline void sliceSumReduction_cub(const Lattice<vobj> &Data, Vector<vobj> &lvSum, const int rd, const int e1, const int e2, const int stride, const int ostride, const int Nsimd)
{
autoView(Data_v, Data, AcceleratorRead); //hipcub/cub cannot deal with large vobjs so we split into small/large case.
if constexpr (sizeof(vobj) <= 256) {
sliceSumReduction_cub_small(&Data_v[0], lvSum, rd, e1, e2, stride, ostride, Nsimd);
}
else {
sliceSumReduction_cub_large(&Data_v[0], lvSum, rd, e1, e2, stride, ostride, Nsimd);
}
}
#endif
#if defined(GRID_SYCL)
template<class vobj> inline void sliceSumReduction_sycl(const Lattice<vobj> &Data, Vector <vobj> &lvSum, const int &rd, const int &e1, const int &e2, const int &stride, const int &ostride, const int &Nsimd)
{
typedef typename vobj::scalar_object sobj;
size_t subvol_size = e1*e2;
vobj *mysum = (vobj *) malloc_shared(sizeof(vobj),*theGridAccelerator);
vobj vobj_zero;
zeroit(vobj_zero);
commVector<vobj> reduction_buffer(rd*subvol_size);
auto rb_p = &reduction_buffer[0];
autoView(Data_v, Data, AcceleratorRead);
//prepare reduction buffer
accelerator_for2d( s,subvol_size, r,rd, (size_t)Nsimd,{
int n = s / e2;
int b = s % e2;
int so=r*ostride; // base offset for start of plane
int ss= so+n*stride+b;
coalescedWrite(rb_p[r*subvol_size+s], coalescedRead(Data_v[ss]));
});
for (int r = 0; r < rd; r++) {
mysum[0] = vobj_zero; //dirty hack: cannot pass vobj_zero as identity to sycl::reduction as its not device_copyable
theGridAccelerator->submit([&](cl::sycl::handler &cgh) {
auto Reduction = cl::sycl::reduction(mysum,std::plus<>());
cgh.parallel_for(cl::sycl::range<1>{subvol_size},
Reduction,
[=](cl::sycl::id<1> item, auto &sum) {
auto s = item[0];
sum += rb_p[r*subvol_size+s];
});
});
theGridAccelerator->wait();
lvSum[r] = mysum[0];
}
free(mysum,*theGridAccelerator);
}
#endif
template<class vobj> inline void sliceSumReduction_cpu(const Lattice<vobj> &Data, Vector<vobj> &lvSum, const int &rd, const int &e1, const int &e2, const int &stride, const int &ostride, const int &Nsimd)
{
// sum over reduced dimension planes, breaking out orthog dir
// Parallel over orthog direction
autoView( Data_v, Data, CpuRead);
thread_for( r,rd, {
int so=r*ostride; // base offset for start of plane
for(int n=0;n<e1;n++){
for(int b=0;b<e2;b++){
int ss= so+n*stride+b;
lvSum[r]=lvSum[r]+Data_v[ss];
}
}
});
}
template<class vobj> inline void sliceSumReduction(const Lattice<vobj> &Data, Vector<vobj> &lvSum, const int &rd, const int &e1, const int &e2, const int &stride, const int &ostride, const int &Nsimd)
{
#if defined(GRID_CUDA) || defined(GRID_HIP)
sliceSumReduction_cub(Data, lvSum, rd, e1, e2, stride, ostride, Nsimd);
#elif defined(GRID_SYCL)
sliceSumReduction_sycl(Data, lvSum, rd, e1, e2, stride, ostride, Nsimd);
#else
sliceSumReduction_cpu(Data, lvSum, rd, e1, e2, stride, ostride, Nsimd);
#endif
}
NAMESPACE_END(Grid);

View File

@ -469,15 +469,13 @@ inline void blockSum(Lattice<vobj> &coarseData,const Lattice<vobj> &fineData)
Coordinate fine_rdimensions = fine->_rdimensions;
Coordinate coarse_rdimensions = coarse->_rdimensions;
vobj zz = Zero();
accelerator_for(sc,coarse->oSites(),1,{
// One thread per sub block
Coordinate coor_c(_ndimension);
Lexicographic::CoorFromIndex(coor_c,sc,coarse_rdimensions); // Block coordinate
vobj cd = zz;
vobj cd = Zero();
for(int sb=0;sb<blockVol;sb++){

View File

@ -45,6 +45,7 @@ public:
};
// Host only
GridBase * getGrid(void) const { return _grid; };
vobj* getHostPointer(void) const { return _odata; };
};
/////////////////////////////////////////////////////////////////////////////////////////

View File

@ -179,11 +179,11 @@ extern GridLogger GridLogSolver;
extern GridLogger GridLogError;
extern GridLogger GridLogWarning;
extern GridLogger GridLogMessage;
extern GridLogger GridLogDebug ;
extern GridLogger GridLogDebug;
extern GridLogger GridLogPerformance;
extern GridLogger GridLogDslash;
extern GridLogger GridLogIterative ;
extern GridLogger GridLogIntegrator ;
extern GridLogger GridLogIterative;
extern GridLogger GridLogIntegrator;
extern GridLogger GridLogHMC;
extern GridLogger GridLogMemory;
extern GridLogger GridLogTracing;
@ -191,6 +191,41 @@ extern Colours GridLogColours;
std::string demangle(const char* name) ;
template<typename... Args>
inline std::string sjoin(Args&&... args) noexcept {
std::ostringstream msg;
(msg << ... << args);
return msg.str();
}
/*! @brief make log messages work like python print */
template <typename... Args>
inline void Grid_log(Args&&... args) {
std::string msg = sjoin(std::forward<Args>(args)...);
std::cout << GridLogMessage << msg << std::endl;
}
/*! @brief make warning messages work like python print */
template <typename... Args>
inline void Grid_warn(Args&&... args) {
std::string msg = sjoin(std::forward<Args>(args)...);
std::cout << "\033[33m" << GridLogWarning << msg << "\033[0m" << std::endl;
}
/*! @brief make error messages work like python print */
template <typename... Args>
inline void Grid_error(Args&&... args) {
std::string msg = sjoin(std::forward<Args>(args)...);
std::cout << "\033[31m" << GridLogError << msg << "\033[0m" << std::endl;
}
/*! @brief make pass messages work like python print */
template <typename... Args>
inline void Grid_pass(Args&&... args) {
std::string msg = sjoin(std::forward<Args>(args)...);
std::cout << "\033[32m" << GridLogMessage << msg << "\033[0m" << std::endl;
}
#define _NBACKTRACE (256)
extern void * Grid_backtrace_buffer[_NBACKTRACE];

View File

@ -34,7 +34,7 @@ class GridTracer {
};
inline void tracePush(const char *name) { roctxRangePushA(name); }
inline void tracePop(const char *name) { roctxRangePop(); }
inline int traceStart(const char *name) { roctxRangeStart(name); }
inline int traceStart(const char *name) { return roctxRangeStart(name); }
inline void traceStop(int ID) { roctxRangeStop(ID); }
#endif

View File

@ -63,7 +63,9 @@ public:
virtual void MooeeDag(const FermionField &in, FermionField &out) ;
virtual void MooeeInv(const FermionField &in, FermionField &out) ;
virtual void MooeeInvDag(const FermionField &in, FermionField &out) ;
virtual void M(const FermionField &in, FermionField &out) ;
virtual void Mdag(const FermionField &in, FermionField &out) ;
private:
RealD mu; // TwistedMass parameter

View File

@ -280,20 +280,16 @@ void StaggeredKernels<Impl>::DhopImproved(StencilImpl &st, LebesgueOrder &lo,
if( interior && exterior ) {
if (Opt == OptGeneric ) { KERNEL_CALL(DhopSiteGeneric,1); return;}
#ifndef GRID_CUDA
if (Opt == OptHandUnroll ) { KERNEL_CALL(DhopSiteHand,1); return;}
#ifndef GRID_CUDA
if (Opt == OptInlineAsm ) { ASM_CALL(DhopSiteAsm); return;}
#endif
} else if( interior ) {
if (Opt == OptGeneric ) { KERNEL_CALL(DhopSiteGenericInt,1); return;}
#ifndef GRID_CUDA
if (Opt == OptHandUnroll ) { KERNEL_CALL(DhopSiteHandInt,1); return;}
#endif
} else if( exterior ) {
if (Opt == OptGeneric ) { KERNEL_CALL(DhopSiteGenericExt,1); return;}
#ifndef GRID_CUDA
if (Opt == OptHandUnroll ) { KERNEL_CALL(DhopSiteHandExt,1); return;}
#endif
}
assert(0 && " Kernel optimisation case not covered ");
}
@ -322,19 +318,13 @@ void StaggeredKernels<Impl>::DhopNaive(StencilImpl &st, LebesgueOrder &lo,
if( interior && exterior ) {
if (Opt == OptGeneric ) { KERNEL_CALL(DhopSiteGeneric,0); return;}
#ifndef GRID_CUDA
if (Opt == OptHandUnroll ) { KERNEL_CALL(DhopSiteHand,0); return;}
#endif
} else if( interior ) {
if (Opt == OptGeneric ) { KERNEL_CALL(DhopSiteGenericInt,0); return;}
#ifndef GRID_CUDA
if (Opt == OptHandUnroll ) { KERNEL_CALL(DhopSiteHandInt,0); return;}
#endif
} else if( exterior ) {
if (Opt == OptGeneric ) { KERNEL_CALL(DhopSiteGenericExt,0); return;}
#ifndef GRID_CUDA
if (Opt == OptHandUnroll ) { KERNEL_CALL(DhopSiteHandExt,0); return;}
#endif
}
}

View File

@ -93,5 +93,25 @@ void WilsonTMFermion<Impl>::MooeeInvDag(const FermionField &in, FermionField &ou
RealD b = tm /sq;
axpibg5x(out,in,a,b);
}
template<class Impl>
void WilsonTMFermion<Impl>::M(const FermionField &in, FermionField &out) {
out.Checkerboard() = in.Checkerboard();
this->Dhop(in, out, DaggerNo);
FermionField tmp(out.Grid());
RealD a = 4.0+this->mass;
RealD b = this->mu;
axpibg5x(tmp,in,a,b);
axpy(out, 1.0, tmp, out);
}
template<class Impl>
void WilsonTMFermion<Impl>::Mdag(const FermionField &in, FermionField &out) {
out.Checkerboard() = in.Checkerboard();
this->Dhop(in, out, DaggerYes);
FermionField tmp(out.Grid());
RealD a = 4.0+this->mass;
RealD b = -this->mu;
axpibg5x(tmp,in,a,b);
axpy(out, 1.0, tmp, out);
}
NAMESPACE_END(Grid);

View File

@ -86,8 +86,13 @@ public:
assert(ForceE.Checkerboard()==Even);
assert(ForceO.Checkerboard()==Odd);
#if defined(GRID_CUDA) || defined(GRID_HIP) || defined(GRID_SYCL)
acceleratorSetCheckerboard(Force,ForceE);
acceleratorSetCheckerboard(Force,ForceO);
#else
setCheckerboard(Force,ForceE);
setCheckerboard(Force,ForceO);
#endif
Force=-Force;
delete forcecb;
@ -130,8 +135,13 @@ public:
assert(ForceE.Checkerboard()==Even);
assert(ForceO.Checkerboard()==Odd);
#if defined(GRID_CUDA) || defined(GRID_HIP) || defined(GRID_SYCL)
acceleratorSetCheckerboard(Force,ForceE);
acceleratorSetCheckerboard(Force,ForceO);
#else
setCheckerboard(Force,ForceE);
setCheckerboard(Force,ForceO);
#endif
Force=-Force;
delete forcecb;

View File

@ -237,7 +237,7 @@ public:
for (int level = 0; level < as.size(); ++level) {
int multiplier = as.at(level).multiplier;
ActionLevel<Field> * Level = new ActionLevel<Field>(multiplier);
ActionLevel<Field, RepresentationPolicy> * Level = new ActionLevel<Field, RepresentationPolicy>(multiplier);
Level->push_back(new EmptyAction<Field>);
LevelForces.push_back(*Level);
// does it copy by value or reference??

View File

@ -0,0 +1,389 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/qcd/smearing/HISQSmearing.h
Copyright (C) 2023
Author: D. A. Clarke <clarke.davida@gmail.com>
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
*************************************************************************************/
/*
@file HISQSmearing.h
@brief Declares classes related to HISQ smearing
*/
#pragma once
#include <Grid/Grid.h>
#include <Grid/lattice/PaddedCell.h>
#include <Grid/stencil/GeneralLocalStencil.h>
NAMESPACE_BEGIN(Grid);
// TODO: find a way to fold this into the stencil header. need to access grid to get
// Nd, since you don't want to inherit from QCD.h
/*! @brief append arbitrary shift path to shifts */
template<typename... Args>
void appendShift(std::vector<Coordinate>& shifts, int dir, Args... args) {
Coordinate shift(Nd,0);
generalShift(shift, dir, args...);
// push_back creates an element at the end of shifts and
// assigns the data in the argument to it.
shifts.push_back(shift);
}
/*! @brief figure out the stencil index from mu and nu */
accelerator_inline int stencilIndex(int mu, int nu) {
// Nshifts depends on how you built the stencil
int Nshifts = 6;
return Nshifts*nu + Nd*Nshifts*mu;
}
/*! @brief structure holding the link treatment */
struct SmearingParameters{
SmearingParameters(){}
Real c_1; // 1 link
Real c_naik; // Naik term
Real c_3; // 3 link
Real c_5; // 5 link
Real c_7; // 7 link
Real c_lp; // 5 link Lepage
SmearingParameters(Real c1, Real cnaik, Real c3, Real c5, Real c7, Real clp)
: c_1(c1),
c_naik(cnaik),
c_3(c3),
c_5(c5),
c_7(c7),
c_lp(clp){}
};
/*! @brief create fat links from link variables */
template<class Gimpl>
class Smear_HISQ : public Gimpl {
private:
GridCartesian* const _grid;
SmearingParameters _linkTreatment;
public:
INHERIT_GIMPL_TYPES(Gimpl);
typedef typename Gimpl::GaugeField GF;
typedef typename Gimpl::GaugeLinkField LF;
typedef typename Gimpl::ComplexField CF;
// Don't allow default values here.
Smear_HISQ(GridCartesian* grid, Real c1, Real cnaik, Real c3, Real c5, Real c7, Real clp)
: _grid(grid),
_linkTreatment(c1,cnaik,c3,c5,c7,clp) {
assert(Nc == 3 && "HISQ smearing currently implemented only for Nc==3");
assert(Nd == 4 && "HISQ smearing only defined for Nd==4");
}
// Allow to pass a pointer to a C-style, double array for MILC convenience
Smear_HISQ(GridCartesian* grid, double* coeff)
: _grid(grid),
_linkTreatment(coeff[0],coeff[1],coeff[2],coeff[3],coeff[4],coeff[5]) {
assert(Nc == 3 && "HISQ smearing currently implemented only for Nc==3");
assert(Nd == 4 && "HISQ smearing only defined for Nd==4");
}
~Smear_HISQ() {}
// Intent: OUT--u_smr, u_naik
// IN--u_thin
void smear(GF& u_smr, GF& u_naik, GF& u_thin) const {
SmearingParameters lt = this->_linkTreatment;
auto grid = this->_grid;
// Create a padded cell of extra padding depth=1 and fill the padding.
int depth = 1;
PaddedCell Ghost(depth,grid);
GF Ughost = Ghost.Exchange(u_thin);
// This is where auxiliary N-link fields and the final smear will be stored.
GF Ughost_fat(Ughost.Grid());
GF Ughost_3link(Ughost.Grid());
GF Ughost_5linkA(Ughost.Grid());
GF Ughost_5linkB(Ughost.Grid());
// mu-nu plane stencil. We allow mu==nu to make indexing the stencil easier,
// but these entries will not be used.
std::vector<Coordinate> shifts;
for(int mu=0;mu<Nd;mu++)
for(int nu=0;nu<Nd;nu++) {
appendShift(shifts,mu);
appendShift(shifts,nu);
appendShift(shifts,shiftSignal::NO_SHIFT);
appendShift(shifts,mu,Back(nu));
appendShift(shifts,Back(nu));
appendShift(shifts,Back(mu));
}
// A GeneralLocalStencil has two indices: a site and stencil index
GeneralLocalStencil gStencil(Ughost.Grid(),shifts);
// This is where contributions from the smearing get added together
Ughost_fat=Zero();
// This loop handles 3-, 5-, and 7-link constructs, minus Lepage and Naik.
for(int mu=0;mu<Nd;mu++) {
// TODO: This approach is slightly memory inefficient. It uses 25% extra memory
Ughost_3link =Zero();
Ughost_5linkA=Zero();
Ughost_5linkB=Zero();
// Create the accessors
autoView(U_v , Ughost , AcceleratorRead);
autoView(U_fat_v , Ughost_fat , AcceleratorWrite);
autoView(U_3link_v , Ughost_3link , AcceleratorWrite);
autoView(U_5linkA_v, Ughost_5linkA, AcceleratorWrite);
autoView(U_5linkB_v, Ughost_5linkB, AcceleratorWrite);
// We infer some types that will be needed in the calculation.
typedef decltype(gStencil.GetEntry(0,0)) stencilElement;
typedef decltype(coalescedReadGeneralPermute(U_v[0](0),gStencil.GetEntry(0,0)->_permute,Nd)) U3matrix;
int Nsites = U_v.size();
auto gStencil_v = gStencil.View();
accelerator_for(site,Nsites,Simd::Nsimd(),{ // ----------- 3-link constructs
stencilElement SE0, SE1, SE2, SE3, SE4, SE5;
U3matrix U0, U1, U2, U3, U4, U5, W;
for(int nu=0;nu<Nd;nu++) {
if(nu==mu) continue;
int s = stencilIndex(mu,nu);
// The stencil gives us support points in the mu-nu plane that we will use to
// grab the links we need.
SE0 = gStencil_v.GetEntry(s+0,site); int x_p_mu = SE0->_offset;
SE1 = gStencil_v.GetEntry(s+1,site); int x_p_nu = SE1->_offset;
SE2 = gStencil_v.GetEntry(s+2,site); int x = SE2->_offset;
SE3 = gStencil_v.GetEntry(s+3,site); int x_p_mu_m_nu = SE3->_offset;
SE4 = gStencil_v.GetEntry(s+4,site); int x_m_nu = SE4->_offset;
SE5 = gStencil_v.GetEntry(s+5,site); int x_m_mu = SE5->_offset;
// When you're deciding whether to take an adjoint, the question is: how is the
// stored link oriented compared to the one you want? If I imagine myself travelling
// with the to-be-updated link, I have two possible, alternative 3-link paths I can
// take, one starting by going to the left, the other starting by going to the right.
U0 = coalescedReadGeneralPermute(U_v[x_p_mu ](nu),SE0->_permute,Nd);
U1 = coalescedReadGeneralPermute(U_v[x_p_nu ](mu),SE1->_permute,Nd);
U2 = coalescedReadGeneralPermute(U_v[x ](nu),SE2->_permute,Nd);
U3 = coalescedReadGeneralPermute(U_v[x_p_mu_m_nu](nu),SE3->_permute,Nd);
U4 = coalescedReadGeneralPermute(U_v[x_m_nu ](mu),SE4->_permute,Nd);
U5 = coalescedReadGeneralPermute(U_v[x_m_nu ](nu),SE4->_permute,Nd);
// "left" "right"
W = U2*U1*adj(U0) + adj(U5)*U4*U3;
// Save 3-link construct for later and add to smeared field.
coalescedWrite(U_3link_v[x](nu), W);
// The index operator (x) returns the coalesced read on GPU. The view [] index returns
// a reference to the vector object. The [x](mu) returns a reference to the densely
// packed (contiguous in memory) mu-th element of the vector object. On CPU,
// coalescedRead/Write is the identity mapping assigning vector object to vector object.
// But on GPU it's non-trivial and maps scalar object to vector object and vice versa.
coalescedWrite(U_fat_v[x](mu), U_fat_v(x)(mu) + lt.c_3*W);
}
})
accelerator_for(site,Nsites,Simd::Nsimd(),{ // ----------- 5-link
stencilElement SE0, SE1, SE2, SE3, SE4, SE5;
U3matrix U0, U1, U2, U3, U4, U5, W;
int sigmaIndex = 0;
for(int nu=0;nu<Nd;nu++) {
if(nu==mu) continue;
int s = stencilIndex(mu,nu);
for(int rho=0;rho<Nd;rho++) {
if (rho == mu || rho == nu) continue;
SE0 = gStencil_v.GetEntry(s+0,site); int x_p_mu = SE0->_offset;
SE1 = gStencil_v.GetEntry(s+1,site); int x_p_nu = SE1->_offset;
SE2 = gStencil_v.GetEntry(s+2,site); int x = SE2->_offset;
SE3 = gStencil_v.GetEntry(s+3,site); int x_p_mu_m_nu = SE3->_offset;
SE4 = gStencil_v.GetEntry(s+4,site); int x_m_nu = SE4->_offset;
U0 = coalescedReadGeneralPermute( U_v[x_p_mu ](nu ),SE0->_permute,Nd);
U1 = coalescedReadGeneralPermute(U_3link_v[x_p_nu ](rho),SE1->_permute,Nd);
U2 = coalescedReadGeneralPermute( U_v[x ](nu ),SE2->_permute,Nd);
U3 = coalescedReadGeneralPermute( U_v[x_p_mu_m_nu](nu ),SE3->_permute,Nd);
U4 = coalescedReadGeneralPermute(U_3link_v[x_m_nu ](rho),SE4->_permute,Nd);
U5 = coalescedReadGeneralPermute( U_v[x_m_nu ](nu ),SE4->_permute,Nd);
W = U2*U1*adj(U0) + adj(U5)*U4*U3;
if(sigmaIndex<3) {
coalescedWrite(U_5linkA_v[x](rho), W);
} else {
coalescedWrite(U_5linkB_v[x](rho), W);
}
coalescedWrite(U_fat_v[x](mu), U_fat_v(x)(mu) + lt.c_5*W);
sigmaIndex++;
}
}
})
accelerator_for(site,Nsites,Simd::Nsimd(),{ // ----------- 7-link
stencilElement SE0, SE1, SE2, SE3, SE4, SE5;
U3matrix U0, U1, U2, U3, U4, U5, W;
int sigmaIndex = 0;
for(int nu=0;nu<Nd;nu++) {
if(nu==mu) continue;
int s = stencilIndex(mu,nu);
for(int rho=0;rho<Nd;rho++) {
if (rho == mu || rho == nu) continue;
SE0 = gStencil_v.GetEntry(s+0,site); int x_p_mu = SE0->_offset;
SE1 = gStencil_v.GetEntry(s+1,site); int x_p_nu = SE1->_offset;
SE2 = gStencil_v.GetEntry(s+2,site); int x = SE2->_offset;
SE3 = gStencil_v.GetEntry(s+3,site); int x_p_mu_m_nu = SE3->_offset;
SE4 = gStencil_v.GetEntry(s+4,site); int x_m_nu = SE4->_offset;
U0 = coalescedReadGeneralPermute(U_v[x_p_mu](nu),SE0->_permute,Nd);
if(sigmaIndex<3) {
U1 = coalescedReadGeneralPermute(U_5linkB_v[x_p_nu](rho),SE1->_permute,Nd);
} else {
U1 = coalescedReadGeneralPermute(U_5linkA_v[x_p_nu](rho),SE1->_permute,Nd);
}
U2 = coalescedReadGeneralPermute(U_v[x](nu),SE2->_permute,Nd);
U3 = coalescedReadGeneralPermute(U_v[x_p_mu_m_nu](nu),SE3->_permute,Nd);
if(sigmaIndex<3) {
U4 = coalescedReadGeneralPermute(U_5linkB_v[x_m_nu](rho),SE4->_permute,Nd);
} else {
U4 = coalescedReadGeneralPermute(U_5linkA_v[x_m_nu](rho),SE4->_permute,Nd);
}
U5 = coalescedReadGeneralPermute(U_v[x_m_nu](nu),SE4->_permute,Nd);
W = U2*U1*adj(U0) + adj(U5)*U4*U3;
coalescedWrite(U_fat_v[x](mu), U_fat_v(x)(mu) + lt.c_7*W);
sigmaIndex++;
}
}
})
} // end mu loop
// c1, c3, c5, c7 construct contributions
u_smr = Ghost.Extract(Ughost_fat) + lt.c_1*u_thin;
// Load up U and V std::vectors to access thin and smeared links.
std::vector<LF> U(Nd, grid);
std::vector<LF> V(Nd, grid);
std::vector<LF> Vnaik(Nd, grid);
for (int mu = 0; mu < Nd; mu++) {
U[mu] = PeekIndex<LorentzIndex>(u_thin, mu);
V[mu] = PeekIndex<LorentzIndex>(u_smr, mu);
}
for(int mu=0;mu<Nd;mu++) {
// Naik
Vnaik[mu] = lt.c_naik*Gimpl::CovShiftForward(U[mu],mu,
Gimpl::CovShiftForward(U[mu],mu,
Gimpl::CovShiftIdentityForward(U[mu],mu)));
// LePage
for (int nu_h=1;nu_h<Nd;nu_h++) {
int nu=(mu+nu_h)%Nd;
// nu, nu, mu, Back(nu), Back(nu)
V[mu] = V[mu] + lt.c_lp*Gimpl::CovShiftForward(U[nu],nu,
Gimpl::CovShiftForward(U[nu],nu,
Gimpl::CovShiftForward(U[mu],mu,
Gimpl::CovShiftBackward(U[nu],nu,
Gimpl::CovShiftIdentityBackward(U[nu],nu)))))
// Back(nu), Back(nu), mu, nu, nu
+ lt.c_lp*Gimpl::CovShiftBackward(U[nu],nu,
Gimpl::CovShiftBackward(U[nu],nu,
Gimpl::CovShiftForward(U[mu],mu,
Gimpl::CovShiftForward(U[nu],nu,
Gimpl::CovShiftIdentityForward(U[nu],nu)))));
}
}
// Put V back into u_smr.
for (int mu = 0; mu < Nd; mu++) {
PokeIndex<LorentzIndex>(u_smr , V[mu] , mu);
PokeIndex<LorentzIndex>(u_naik, Vnaik[mu], mu);
}
};
// Intent: OUT--u_proj
// IN--u_mu
void projectU3(GF& u_proj, GF& u_mu) const {
auto grid = this->_grid;
LF V(grid), Q(grid), sqrtQinv(grid), id_3(grid), diff(grid);
CF c0(grid), c1(grid), c2(grid), g0(grid), g1(grid), g2(grid), S(grid), R(grid), theta(grid),
u(grid), v(grid), w(grid), den(grid), f0(grid), f1(grid), f2(grid);
// Follow MILC 10.1103/PhysRevD.82.074501, eqs (B2-B3) and (C1-C8)
for (int mu = 0; mu < Nd; mu++) {
V = PeekIndex<LorentzIndex>(u_mu, mu);
Q = adj(V)*V;
c0 = real(trace(Q));
c1 = (1/2.)*real(trace(Q*Q));
c2 = (1/3.)*real(trace(Q*Q*Q));
S = (1/3.)*c1-(1/18.)*c0*c0;
if (norm2(S)<1e-28) {
g0 = (1/3.)*c0; g1 = g0; g2 = g1;
} else {
R = (1/2.)*c2-(1/3. )*c0*c1+(1/27.)*c0*c0*c0;
theta = acos(R*pow(S,-1.5));
g0 = (1/3.)*c0+2.*sqrt(S)*cos((1/3.)*theta-2*M_PI/3.);
g1 = (1/3.)*c0+2.*sqrt(S)*cos((1/3.)*theta );
g2 = (1/3.)*c0+2.*sqrt(S)*cos((1/3.)*theta+2*M_PI/3.);
}
// if (fabs(Q.determinant()/(g0*g1*g2)-1.0) > 1e-5) { SVD }
u = sqrt(g0) + sqrt(g1) + sqrt(g2);
v = sqrt(g0*g1) + sqrt(g0*g2) + sqrt(g1*g2);
w = sqrt(g0*g1*g2);
den = w*(u*v-w);
f0 = (-w*(u*u+v)+u*v*v)/den;
f1 = (-w-u*u*u+2.*u*v)/den;
f2 = u/den;
id_3 = 1.;
sqrtQinv = f0*id_3 + f1*Q + f2*Q*Q;
PokeIndex<LorentzIndex>(u_proj, V*sqrtQinv, mu);
}
};
// void derivative(const GaugeField& Gauge) const {
// };
};
NAMESPACE_END(Grid);

View File

@ -5,4 +5,5 @@
#include <Grid/qcd/smearing/StoutSmearing.h>
#include <Grid/qcd/smearing/GaugeConfiguration.h>
#include <Grid/qcd/smearing/WilsonFlow.h>
#include <Grid/qcd/smearing/HISQSmearing.h>

View File

@ -1133,4 +1133,13 @@ static_assert(sizeof(SIMD_Ftype) == sizeof(SIMD_Itype), "SIMD vector lengths inc
NAMESPACE_END(Grid);
#ifdef GRID_SYCL
template<> struct sycl::is_device_copyable<Grid::vComplexF> : public std::true_type {};
template<> struct sycl::is_device_copyable<Grid::vComplexD> : public std::true_type {};
template<> struct sycl::is_device_copyable<Grid::vRealF > : public std::true_type {};
template<> struct sycl::is_device_copyable<Grid::vRealD > : public std::true_type {};
template<> struct sycl::is_device_copyable<Grid::vInteger > : public std::true_type {};
#endif
#endif

View File

@ -137,5 +137,55 @@ public:
};
////////////////////////////////////////////////
// Some machinery to streamline making a stencil
////////////////////////////////////////////////
class shiftSignal {
public:
enum {
BACKWARD_CONST = 16,
NO_SHIFT = -1
};
};
// TODO: put a check somewhere that BACKWARD_CONST > Nd!
/*! @brief signals that you want to go backwards in direction dir */
inline int Back(const int dir) {
// generalShift will use BACKWARD_CONST to determine whether we step forward or
// backward. Trick inspired by SIMULATeQCD.
return dir + shiftSignal::BACKWARD_CONST;
}
/*! @brief shift one unit in direction dir */
template<typename... Args>
void generalShift(Coordinate& shift, int dir) {
if (dir >= shiftSignal::BACKWARD_CONST) {
dir -= shiftSignal::BACKWARD_CONST;
shift[dir]+=-1;
} else if (dir == shiftSignal::NO_SHIFT) {
; // do nothing
} else {
shift[dir]+=1;
}
}
/*! @brief follow a path of directions, shifting one unit in each direction */
template<typename... Args>
void generalShift(Coordinate& shift, int dir, Args... args) {
if (dir >= shiftSignal::BACKWARD_CONST) {
dir -= shiftSignal::BACKWARD_CONST;
shift[dir]+=-1;
} else if (dir == shiftSignal::NO_SHIFT) {
; // do nothing
} else {
shift[dir]+=1;
}
generalShift(shift, args...);
}
NAMESPACE_END(Grid);

View File

@ -706,7 +706,7 @@ public:
}
}
}
std::cout << GridLogDebug << "BuildSurfaceList size is "<<surface_list.size()<<std::endl;
//std::cout << "BuildSurfaceList size is "<<surface_list.size()<<std::endl;
}
/// Introduce a block structure and switch off comms on boundaries
void DirichletBlock(const Coordinate &dirichlet_block)
@ -761,7 +761,8 @@ public:
int checkerboard,
const std::vector<int> &directions,
const std::vector<int> &distances,
Parameters p=Parameters())
Parameters p=Parameters(),
bool preserve_shm=false)
{
face_table_computed=0;
_grid = grid;
@ -855,7 +856,9 @@ public:
/////////////////////////////////////////////////////////////////////////////////
const int Nsimd = grid->Nsimd();
_grid->ShmBufferFreeAll();
// Allow for multiple stencils to exist simultaneously
if (!preserve_shm)
_grid->ShmBufferFreeAll();
int maxl=2;
u_simd_send_buf.resize(maxl);

View File

@ -404,3 +404,12 @@ NAMESPACE_BEGIN(Grid);
};
NAMESPACE_END(Grid);
#ifdef GRID_SYCL
template<typename T> struct
sycl::is_device_copyable<T, typename std::enable_if<
Grid::isGridTensor<T>::value && (!std::is_trivially_copyable<T>::value),
void>::type>
: public std::true_type {};
#endif

View File

@ -225,6 +225,8 @@ inline void acceleratorFreeShared(void *ptr){ cudaFree(ptr);};
inline void acceleratorFreeDevice(void *ptr){ cudaFree(ptr);};
inline void acceleratorCopyToDevice(void *from,void *to,size_t bytes) { cudaMemcpy(to,from,bytes, cudaMemcpyHostToDevice);}
inline void acceleratorCopyFromDevice(void *from,void *to,size_t bytes){ cudaMemcpy(to,from,bytes, cudaMemcpyDeviceToHost);}
inline void acceleratorCopyToDeviceAsync(void *from, void *to, size_t bytes, cudaStream_t stream = copyStream) { cudaMemcpyAsync(to,from,bytes, cudaMemcpyHostToDevice, stream);}
inline void acceleratorCopyFromDeviceAsync(void *from, void *to, size_t bytes, cudaStream_t stream = copyStream) { cudaMemcpyAsync(to,from,bytes, cudaMemcpyDeviceToHost, stream);}
inline void acceleratorMemSet(void *base,int value,size_t bytes) { cudaMemset(base,value,bytes);}
inline void acceleratorCopyDeviceToDeviceAsynch(void *from,void *to,size_t bytes) // Asynch
{
@ -253,17 +255,13 @@ inline int acceleratorIsCommunicable(void *ptr)
#define GRID_SYCL_LEVEL_ZERO_IPC
NAMESPACE_END(Grid);
#if 0
#include <CL/sycl.hpp>
#include <CL/sycl/usm.hpp>
#include <level_zero/ze_api.h>
#include <CL/sycl/backend/level_zero.hpp>
#else
// Force deterministic reductions
#define SYCL_REDUCTION_DETERMINISTIC
#include <sycl/CL/sycl.hpp>
#include <sycl/usm.hpp>
#include <level_zero/ze_api.h>
#include <sycl/ext/oneapi/backend/level_zero.hpp>
#endif
NAMESPACE_BEGIN(Grid);
@ -287,23 +285,24 @@ accelerator_inline int acceleratorSIMTlane(int Nsimd) {
#define accelerator_for2dNB( iter1, num1, iter2, num2, nsimd, ... ) \
theGridAccelerator->submit([&](cl::sycl::handler &cgh) { \
unsigned long nt=acceleratorThreads(); \
unsigned long unum1 = num1; \
unsigned long unum2 = num2; \
if(nt < 8)nt=8; \
cl::sycl::range<3> local {nt,1,nsimd}; \
cl::sycl::range<3> global{unum1,unum2,nsimd}; \
cgh.parallel_for( \
cl::sycl::nd_range<3>(global,local), \
[=] (cl::sycl::nd_item<3> item) /*mutable*/ \
[[intel::reqd_sub_group_size(16)]] \
{ \
auto iter1 = item.get_global_id(0); \
auto iter2 = item.get_global_id(1); \
auto lane = item.get_global_id(2); \
{ __VA_ARGS__ }; \
}); \
});
unsigned long nt=acceleratorThreads(); \
if(nt < 8)nt=8; \
unsigned long unum1 = num1; \
unsigned long unum2 = num2; \
unsigned long unum1_divisible_by_nt = ((unum1 + nt - 1) / nt) * nt; \
cl::sycl::range<3> local {nt,1,nsimd}; \
cl::sycl::range<3> global{unum1_divisible_by_nt,unum2,nsimd}; \
cgh.parallel_for( \
cl::sycl::nd_range<3>(global,local), \
[=] (cl::sycl::nd_item<3> item) /*mutable*/ \
[[intel::reqd_sub_group_size(16)]] \
{ \
auto iter1 = item.get_global_id(0); \
auto iter2 = item.get_global_id(1); \
auto lane = item.get_global_id(2); \
{ if (iter1 < unum1){ __VA_ARGS__ } }; \
}); \
});
#define accelerator_barrier(dummy) { theGridAccelerator->wait(); }
@ -442,6 +441,8 @@ inline void acceleratorFreeShared(void *ptr){ auto r=hipFree(ptr);};
inline void acceleratorFreeDevice(void *ptr){ auto r=hipFree(ptr);};
inline void acceleratorCopyToDevice(void *from,void *to,size_t bytes) { auto r=hipMemcpy(to,from,bytes, hipMemcpyHostToDevice);}
inline void acceleratorCopyFromDevice(void *from,void *to,size_t bytes){ auto r=hipMemcpy(to,from,bytes, hipMemcpyDeviceToHost);}
inline void acceleratorCopyToDeviceAsync(void *from, void *to, size_t bytes, hipStream_t stream = copyStream) { auto r = hipMemcpyAsync(to,from,bytes, hipMemcpyHostToDevice, stream);}
inline void acceleratorCopyFromDeviceAsync(void *from, void *to, size_t bytes, hipStream_t stream = copyStream) { auto r = hipMemcpyAsync(to,from,bytes, hipMemcpyDeviceToHost, stream);}
//inline void acceleratorCopyDeviceToDeviceAsynch(void *from,void *to,size_t bytes) { hipMemcpy(to,from,bytes, hipMemcpyDeviceToDevice);}
//inline void acceleratorCopySynchronise(void) { }
inline void acceleratorMemSet(void *base,int value,size_t bytes) { auto r=hipMemset(base,value,bytes);}

View File

@ -77,6 +77,10 @@ feenableexcept (unsigned int excepts)
}
#endif
#ifndef HOST_NAME_MAX
#define HOST_NAME_MAX _POSIX_HOST_NAME_MAX
#endif
NAMESPACE_BEGIN(Grid);
//////////////////////////////////////////////////////
@ -86,11 +90,83 @@ NAMESPACE_BEGIN(Grid);
static Coordinate Grid_default_latt;
static Coordinate Grid_default_mpi;
///////////////////////////////////////////////////////
// Grid Norm logging for repro testing
///////////////////////////////////////////////////////
int GridNormLoggingMode;
int32_t GridNormLoggingCounter;
std::vector<double> GridNormLogVector;
void SetGridNormLoggingMode(GridNormLoggingMode_t mode)
{
switch ( mode ) {
case GridNormLoggingModePrint:
SetGridNormLoggingModePrint();
break;
case GridNormLoggingModeRecord:
SetGridNormLoggingModeRecord();
break;
case GridNormLoggingModeVerify:
SetGridNormLoggingModeVerify();
break;
case GridNormLoggingModeNone:
GridNormLoggingMode = mode;
GridNormLoggingCounter=0;
GridNormLogVector.resize(0);
break;
default:
assert(0);
}
}
void SetGridNormLoggingModePrint(void)
{
GridNormLoggingCounter = 0;
GridNormLogVector.resize(0);
GridNormLoggingMode = GridNormLoggingModePrint;
}
void SetGridNormLoggingModeRecord(void)
{
GridNormLoggingCounter = 0;
GridNormLogVector.resize(0);
GridNormLoggingMode = GridNormLoggingModeRecord;
}
void SetGridNormLoggingModeVerify(void)
{
GridNormLoggingCounter = 0;
GridNormLoggingMode = GridNormLoggingModeVerify;
}
void GridNormLog(double value)
{
if(GridNormLoggingMode == GridNormLoggingModePrint) {
std::cerr<<"GridNormLog : "<< GridNormLoggingCounter <<" " << std::hexfloat << value <<std::endl;
GridNormLoggingCounter++;
}
if(GridNormLoggingMode == GridNormLoggingModeRecord) {
GridNormLogVector.push_back(value);
GridNormLoggingCounter++;
}
if(GridNormLoggingMode == GridNormLoggingModeVerify) {
assert(GridNormLoggingCounter < GridNormLogVector.size());
if ( value != GridNormLogVector[GridNormLoggingCounter] ) {
fprintf(stderr,"%s Oops, I did it again! Reproduce failure for norm %d/%zu %.16e %.16e\n",GridHostname(),GridNormLoggingCounter,GridNormLogVector.size(),
value, GridNormLogVector[GridNormLoggingCounter]); fflush(stderr);
}
GridNormLoggingCounter++;
}
}
int GridThread::_threads =1;
int GridThread::_hyperthreads=1;
int GridThread::_cores=1;
char hostname[HOST_NAME_MAX+1];
char *GridHostname(void)
{
return hostname;
}
const Coordinate &GridDefaultLatt(void) {return Grid_default_latt;};
const Coordinate &GridDefaultMpi(void) {return Grid_default_mpi;};
const Coordinate GridDefaultSimd(int dims,int nsimd)
@ -393,6 +469,8 @@ void Grid_init(int *argc,char ***argv)
std::cout << GridLogMessage << "MPI is initialised and logging filters activated "<<std::endl;
std::cout << GridLogMessage << "================================================ "<<std::endl;
gethostname(hostname, HOST_NAME_MAX+1);
std::cout << GridLogMessage << "This rank is running on host "<< hostname<<std::endl;
/////////////////////////////////////////////////////////
// Reporting

View File

@ -34,6 +34,8 @@ NAMESPACE_BEGIN(Grid);
void Grid_init(int *argc,char ***argv);
void Grid_finalize(void);
char * GridHostname(void);
// internal, controled with --handle
void Grid_sa_signal_handler(int sig,siginfo_t *si,void * ptr);
void Grid_debug_handler_init(void);
@ -68,5 +70,20 @@ void GridParseLayout(char **argv,int argc,
void printHash(void);
enum GridNormLoggingMode_t {
GridNormLoggingModeNone,
GridNormLoggingModePrint,
GridNormLoggingModeRecord,
GridNormLoggingModeVerify
};
extern int GridNormLoggingMode;
extern int32_t GridNormLoggingCounter;
extern std::vector<double> GridNormLogVector;
void SetGridNormLoggingModePrint(void);
void SetGridNormLoggingModeRecord(void);
void SetGridNormLoggingModeVerify(void);
void SetGridNormLoggingMode(GridNormLoggingMode_t mode);
void GridNormLog(double value);
NAMESPACE_END(Grid);

View File

@ -0,0 +1,968 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./benchmarks/Benchmark_usqcd.cc
Copyright (C) 2015
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 */
#include <Grid/Grid.h>
#include <Grid/algorithms/blas/BatchedBlas.h>
using namespace Grid;
std::vector<int> L_list;
std::vector<int> Ls_list;
std::vector<double> mflop_list;
double mflop_ref;
double mflop_ref_err;
int NN_global;
FILE * FP;
struct time_statistics{
double mean;
double err;
double min;
double max;
void statistics(std::vector<double> v){
double sum = std::accumulate(v.begin(), v.end(), 0.0);
mean = sum / v.size();
std::vector<double> diff(v.size());
std::transform(v.begin(), v.end(), diff.begin(), [=](double x) { return x - mean; });
double sq_sum = std::inner_product(diff.begin(), diff.end(), diff.begin(), 0.0);
err = std::sqrt(sq_sum / (v.size()*(v.size() - 1)));
auto result = std::minmax_element(v.begin(), v.end());
min = *result.first;
max = *result.second;
}
};
void comms_header(){
std::cout <<GridLogMessage << " L "<<"\t"<<" Ls "<<"\t"
<<"bytes\t MB/s uni \t\t MB/s bidi "<<std::endl;
};
struct controls {
int Opt;
int CommsOverlap;
Grid::CartesianCommunicator::CommunicatorPolicy_t CommsAsynch;
};
class Benchmark {
public:
static void Decomposition (void ) {
int threads = GridThread::GetThreads();
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << "= Grid is setup to use "<<threads<<" threads"<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage<<"Grid Default Decomposition patterns\n";
std::cout<<GridLogMessage<<"\tOpenMP threads : "<<GridThread::GetThreads()<<std::endl;
std::cout<<GridLogMessage<<"\tMPI tasks : "<<GridCmdVectorIntToString(GridDefaultMpi())<<std::endl;
std::cout<<GridLogMessage<<"\tvReal : "<<sizeof(vReal )*8 <<"bits ; " <<GridCmdVectorIntToString(GridDefaultSimd(4,vReal::Nsimd()))<<std::endl;
std::cout<<GridLogMessage<<"\tvRealF : "<<sizeof(vRealF)*8 <<"bits ; " <<GridCmdVectorIntToString(GridDefaultSimd(4,vRealF::Nsimd()))<<std::endl;
std::cout<<GridLogMessage<<"\tvRealD : "<<sizeof(vRealD)*8 <<"bits ; " <<GridCmdVectorIntToString(GridDefaultSimd(4,vRealD::Nsimd()))<<std::endl;
std::cout<<GridLogMessage<<"\tvComplex : "<<sizeof(vComplex )*8 <<"bits ; " <<GridCmdVectorIntToString(GridDefaultSimd(4,vComplex::Nsimd()))<<std::endl;
std::cout<<GridLogMessage<<"\tvComplexF : "<<sizeof(vComplexF)*8 <<"bits ; " <<GridCmdVectorIntToString(GridDefaultSimd(4,vComplexF::Nsimd()))<<std::endl;
std::cout<<GridLogMessage<<"\tvComplexD : "<<sizeof(vComplexD)*8 <<"bits ; " <<GridCmdVectorIntToString(GridDefaultSimd(4,vComplexD::Nsimd()))<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
}
static void Comms(void)
{
int Nloop=200;
int nmu=0;
int maxlat=32;
Coordinate simd_layout = GridDefaultSimd(Nd,vComplexD::Nsimd());
Coordinate mpi_layout = GridDefaultMpi();
for(int mu=0;mu<Nd;mu++) if (mpi_layout[mu]>1) nmu++;
std::vector<double> t_time(Nloop);
time_statistics timestat;
std::cout<<GridLogMessage << "===================================================================================================="<<std::endl;
std::cout<<GridLogMessage << "= Benchmarking threaded STENCIL halo exchange in "<<nmu<<" dimensions"<<std::endl;
std::cout<<GridLogMessage << "===================================================================================================="<<std::endl;
comms_header();
fprintf(FP,"Communications\n\n");
fprintf(FP,"Packet bytes, direction, GB/s per node\n");
for(int lat=16;lat<=maxlat;lat+=8){
// for(int Ls=8;Ls<=8;Ls*=2){
{ int Ls=12;
Coordinate latt_size ({lat*mpi_layout[0],
lat*mpi_layout[1],
lat*mpi_layout[2],
lat*mpi_layout[3]});
GridCartesian Grid(latt_size,simd_layout,mpi_layout);
RealD Nrank = Grid._Nprocessors;
RealD Nnode = Grid.NodeCount();
RealD ppn = Nrank/Nnode;
std::vector<HalfSpinColourVectorD *> xbuf(8);
std::vector<HalfSpinColourVectorD *> rbuf(8);
//Grid.ShmBufferFreeAll();
uint64_t bytes=lat*lat*lat*Ls*sizeof(HalfSpinColourVectorD);
for(int d=0;d<8;d++){
xbuf[d] = (HalfSpinColourVectorD *)acceleratorAllocDevice(bytes);
rbuf[d] = (HalfSpinColourVectorD *)acceleratorAllocDevice(bytes);
// bzero((void *)xbuf[d],lat*lat*lat*Ls*sizeof(HalfSpinColourVectorD));
// bzero((void *)rbuf[d],lat*lat*lat*Ls*sizeof(HalfSpinColourVectorD));
}
// int ncomm;
double dbytes;
for(int dir=0;dir<8;dir++) {
int mu =dir % 4;
if (mpi_layout[mu]>1 ) {
std::vector<double> times(Nloop);
for(int i=0;i<Nloop;i++){
dbytes=0;
double start=usecond();
int xmit_to_rank;
int recv_from_rank;
if ( dir == mu ) {
int comm_proc=1;
Grid.ShiftedRanks(mu,comm_proc,xmit_to_rank,recv_from_rank);
} else {
int comm_proc = mpi_layout[mu]-1;
Grid.ShiftedRanks(mu,comm_proc,xmit_to_rank,recv_from_rank);
}
Grid.SendToRecvFrom((void *)&xbuf[dir][0], xmit_to_rank,
(void *)&rbuf[dir][0], recv_from_rank,
bytes);
dbytes+=bytes;
double stop=usecond();
t_time[i] = stop-start; // microseconds
}
timestat.statistics(t_time);
dbytes=dbytes*ppn;
double xbytes = dbytes*0.5;
double bidibytes = dbytes;
std::cout<<GridLogMessage << lat<<"\t"<<Ls<<"\t "
<< bytes << " \t "
<<xbytes/timestat.mean
<< "\t\t"
<< bidibytes/timestat.mean<< std::endl;
fprintf(FP,"%ld, %d, %f\n",(long)bytes,dir,bidibytes/timestat.mean/1000.);
}
}
for(int d=0;d<8;d++){
acceleratorFreeDevice(xbuf[d]);
acceleratorFreeDevice(rbuf[d]);
}
}
}
fprintf(FP,"\n\n");
return;
}
static void Memory(void)
{
const int Nvec=8;
typedef Lattice< iVector< vReal,Nvec> > LatticeVec;
typedef iVector<vReal,Nvec> Vec;
Coordinate simd_layout = GridDefaultSimd(Nd,vReal::Nsimd());
Coordinate mpi_layout = GridDefaultMpi();
fprintf(FP,"Memory Bandwidth\n\n");
fprintf(FP,"Bytes, GB/s per node\n");
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << "= Benchmarking a*x + y bandwidth"<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " L "<<"\t\t"<<"bytes"<<"\t\t\t"<<"GB/s"<<"\t\t"<<"Gflop/s"<<"\t\t seconds"<< "\t\tGB/s / node"<<std::endl;
std::cout<<GridLogMessage << "----------------------------------------------------------"<<std::endl;
// uint64_t NP;
uint64_t NN;
uint64_t lmax=40;
#define NLOOP (1000*lmax*lmax*lmax*lmax/lat/lat/lat/lat)
GridSerialRNG sRNG; sRNG.SeedFixedIntegers(std::vector<int>({45,12,81,9}));
for(int lat=8;lat<=lmax;lat+=8){
Coordinate latt_size ({lat*mpi_layout[0],lat*mpi_layout[1],lat*mpi_layout[2],lat*mpi_layout[3]});
int64_t vol= latt_size[0]*latt_size[1]*latt_size[2]*latt_size[3];
GridCartesian Grid(latt_size,simd_layout,mpi_layout);
// NP= Grid.RankCount();
NN =Grid.NodeCount();
Vec rn ; random(sRNG,rn);
LatticeVec z(&Grid); z=Zero();
LatticeVec x(&Grid); x=Zero();
LatticeVec y(&Grid); y=Zero();
double a=2.0;
uint64_t Nloop=NLOOP;
double start=usecond();
for(int i=0;i<Nloop;i++){
z=a*x-y;
}
double stop=usecond();
double time = (stop-start)/Nloop*1000;
double flops=vol*Nvec*2;// mul,add
double bytes=3.0*vol*Nvec*sizeof(Real);
std::cout<<GridLogMessage<<std::setprecision(3)
<< lat<<"\t\t"<<bytes<<" \t\t"<<bytes/time<<"\t\t"<<flops/time<<"\t\t"<<(stop-start)/1000./1000.
<< "\t\t"<< bytes/time/NN <<std::endl;
fprintf(FP,"%ld, %f\n",(long)bytes,bytes/time/NN);
}
fprintf(FP,"\n\n");
};
static void BLAS(void)
{
//int nbasis, int nrhs, int coarseVol
int basis[] = { 16,32,64 };
int rhs[] = { 8,16,32 };
int vol = 4*4*4*4;
GridBLAS blas;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << "= batched GEMM (double precision) "<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " M "<<"\t\t"<<"N"<<"\t\t\t"<<"K"<<"\t\t"<<"Gflop/s / rank (coarse mrhs)"<<std::endl;
std::cout<<GridLogMessage << "----------------------------------------------------------"<<std::endl;
fprintf(FP,"GEMM\n\n M, N, K, BATCH, GF/s per rank\n");
for(int b=0;b<3;b++){
for(int r=0;r<3;r++){
int M=basis[b];
int N=rhs[r];
int K=basis[b];
int BATCH=vol;
double p=blas.benchmark(M,N,K,BATCH);
fprintf(FP,"%d, %d, %d, %d, %f\n", M, N, K, BATCH, p);
std::cout<<GridLogMessage<<std::setprecision(3)
<< M<<"\t\t"<<N<<"\t\t"<<K<<"\t\t"<<BATCH<<"\t\t"<<p<<std::endl;
}}
std::cout<<GridLogMessage << "----------------------------------------------------------"<<std::endl;
std::cout<<GridLogMessage << " M "<<"\t\t"<<"N"<<"\t\t\t"<<"K"<<"\t\t"<<"Gflop/s / rank (block project)"<<std::endl;
std::cout<<GridLogMessage << "----------------------------------------------------------"<<std::endl;
for(int b=0;b<3;b++){
for(int r=0;r<3;r++){
int M=basis[b];
int N=rhs[r];
int K=vol;
int BATCH=vol;
double p=blas.benchmark(M,N,K,BATCH);
fprintf(FP,"%d, %d, %d, %d, %f\n", M, N, K, BATCH, p);
std::cout<<GridLogMessage<<std::setprecision(3)
<< M<<"\t\t"<<N<<"\t\t"<<K<<"\t\t"<<BATCH<<"\t\t"<<p<<std::endl;
}}
std::cout<<GridLogMessage << "----------------------------------------------------------"<<std::endl;
std::cout<<GridLogMessage << " M "<<"\t\t"<<"N"<<"\t\t\t"<<"K"<<"\t\t"<<"Gflop/s / rank (block promote)"<<std::endl;
std::cout<<GridLogMessage << "----------------------------------------------------------"<<std::endl;
for(int b=0;b<3;b++){
for(int r=0;r<3;r++){
int M=rhs[r];
int N=vol;
int K=basis[b];
int BATCH=vol;
double p=blas.benchmark(M,N,K,BATCH);
fprintf(FP,"%d, %d, %d, %d, %f\n", M, N, K, BATCH, p);
std::cout<<GridLogMessage<<std::setprecision(3)
<< M<<"\t\t"<<N<<"\t\t"<<K<<"\t\t"<<BATCH<<"\t\t"<<p<<std::endl;
}}
fprintf(FP,"\n\n\n");
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
};
static void SU4(void)
{
const int Nc4=4;
typedef Lattice< iMatrix< vComplexF,Nc4> > LatticeSU4;
Coordinate simd_layout = GridDefaultSimd(Nd,vComplexF::Nsimd());
Coordinate mpi_layout = GridDefaultMpi();
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << "= Benchmarking z = y*x SU(4) bandwidth"<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " L "<<"\t\t"<<"bytes"<<"\t\t\t"<<"GB/s"<<"\t\t"<<"Gflop/s"<<"\t\t seconds"<< "\t\tGB/s / node"<<std::endl;
std::cout<<GridLogMessage << "----------------------------------------------------------"<<std::endl;
uint64_t NN;
uint64_t lmax=32;
GridSerialRNG sRNG; sRNG.SeedFixedIntegers(std::vector<int>({45,12,81,9}));
for(int lat=8;lat<=lmax;lat+=8){
Coordinate latt_size ({lat*mpi_layout[0],lat*mpi_layout[1],lat*mpi_layout[2],lat*mpi_layout[3]});
int64_t vol= latt_size[0]*latt_size[1]*latt_size[2]*latt_size[3];
GridCartesian Grid(latt_size,simd_layout,mpi_layout);
NN =Grid.NodeCount();
LatticeSU4 z(&Grid); z=Zero();
LatticeSU4 x(&Grid); x=Zero();
LatticeSU4 y(&Grid); y=Zero();
// double a=2.0;
uint64_t Nloop=NLOOP;
double start=usecond();
for(int i=0;i<Nloop;i++){
z=x*y;
}
double stop=usecond();
double time = (stop-start)/Nloop*1000;
double flops=vol*Nc4*Nc4*(6+(Nc4-1)*8);// mul,add
double bytes=3.0*vol*Nc4*Nc4*2*sizeof(RealF);
std::cout<<GridLogMessage<<std::setprecision(3)
<< lat<<"\t\t"<<bytes<<" \t\t"<<bytes/time<<"\t\t"<<flops/time<<"\t\t"<<(stop-start)/1000./1000.
<< "\t\t"<< bytes/time/NN <<std::endl;
}
};
static double DWF(int Ls,int L)
{
RealD mass=0.1;
RealD M5 =1.8;
double mflops;
double mflops_best = 0;
double mflops_worst= 0;
std::vector<double> mflops_all;
///////////////////////////////////////////////////////
// Set/Get the layout & grid size
///////////////////////////////////////////////////////
int threads = GridThread::GetThreads();
Coordinate mpi = GridDefaultMpi(); assert(mpi.size()==4);
Coordinate local({L,L,L,L});
Coordinate latt4({local[0]*mpi[0],local[1]*mpi[1],local[2]*mpi[2],local[3]*mpi[3]});
GridCartesian * TmpGrid = SpaceTimeGrid::makeFourDimGrid(latt4,
GridDefaultSimd(Nd,vComplex::Nsimd()),
GridDefaultMpi());
uint64_t NP = TmpGrid->RankCount();
uint64_t NN = TmpGrid->NodeCount();
NN_global=NN;
uint64_t SHM=NP/NN;
///////// Welcome message ////////////
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << "Benchmark DWF on "<<L<<"^4 local volume "<<std::endl;
std::cout<<GridLogMessage << "* Nc : "<<Nc<<std::endl;
std::cout<<GridLogMessage << "* Global volume : "<<GridCmdVectorIntToString(latt4)<<std::endl;
std::cout<<GridLogMessage << "* Ls : "<<Ls<<std::endl;
std::cout<<GridLogMessage << "* ranks : "<<NP <<std::endl;
std::cout<<GridLogMessage << "* nodes : "<<NN <<std::endl;
std::cout<<GridLogMessage << "* ranks/node : "<<SHM <<std::endl;
std::cout<<GridLogMessage << "* ranks geom : "<<GridCmdVectorIntToString(mpi)<<std::endl;
std::cout<<GridLogMessage << "* Using "<<threads<<" threads"<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
///////// Lattice Init ////////////
GridCartesian * UGrid = SpaceTimeGrid::makeFourDimGrid(latt4, GridDefaultSimd(Nd,vComplexF::Nsimd()),GridDefaultMpi());
GridRedBlackCartesian * UrbGrid = SpaceTimeGrid::makeFourDimRedBlackGrid(UGrid);
GridCartesian * FGrid = SpaceTimeGrid::makeFiveDimGrid(Ls,UGrid);
GridRedBlackCartesian * FrbGrid = SpaceTimeGrid::makeFiveDimRedBlackGrid(Ls,UGrid);
///////// RNG Init ////////////
std::vector<int> seeds4({1,2,3,4});
std::vector<int> seeds5({5,6,7,8});
GridParallelRNG RNG4(UGrid); RNG4.SeedFixedIntegers(seeds4);
GridParallelRNG RNG5(FGrid); RNG5.SeedFixedIntegers(seeds5);
std::cout << GridLogMessage << "Initialised RNGs" << std::endl;
typedef DomainWallFermionF Action;
typedef typename Action::FermionField Fermion;
typedef LatticeGaugeFieldF Gauge;
///////// Source preparation ////////////
Gauge Umu(UGrid); SU<Nc>::HotConfiguration(RNG4,Umu);
Fermion src (FGrid); random(RNG5,src);
Fermion src_e (FrbGrid);
Fermion src_o (FrbGrid);
Fermion r_e (FrbGrid);
Fermion r_o (FrbGrid);
Fermion r_eo (FGrid);
Action Dw(Umu,*FGrid,*FrbGrid,*UGrid,*UrbGrid,mass,M5);
{
pickCheckerboard(Even,src_e,src);
pickCheckerboard(Odd,src_o,src);
#ifdef AVX512
const int num_cases = 3;
#else
const int num_cases = 2;
#endif
std::string fmt("G/S/C ; G/O/C ; G/S/S ; G/O/S ");
controls Cases [] = {
{ WilsonKernelsStatic::OptGeneric , WilsonKernelsStatic::CommsAndCompute ,CartesianCommunicator::CommunicatorPolicyConcurrent },
{ WilsonKernelsStatic::OptHandUnroll, WilsonKernelsStatic::CommsAndCompute ,CartesianCommunicator::CommunicatorPolicyConcurrent },
{ WilsonKernelsStatic::OptInlineAsm , WilsonKernelsStatic::CommsAndCompute ,CartesianCommunicator::CommunicatorPolicyConcurrent }
};
for(int c=0;c<num_cases;c++) {
WilsonKernelsStatic::Comms = Cases[c].CommsOverlap;
WilsonKernelsStatic::Opt = Cases[c].Opt;
CartesianCommunicator::SetCommunicatorPolicy(Cases[c].CommsAsynch);
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
if ( WilsonKernelsStatic::Opt == WilsonKernelsStatic::OptGeneric ) std::cout << GridLogMessage<< "* Using GENERIC Nc WilsonKernels" <<std::endl;
if ( WilsonKernelsStatic::Opt == WilsonKernelsStatic::OptInlineAsm ) std::cout << GridLogMessage<< "* Using ASM WilsonKernels" <<std::endl;
if ( WilsonKernelsStatic::Opt == WilsonKernelsStatic::OptHandUnroll) std::cout << GridLogMessage<< "* Using UNROLLED WilsonKernels" <<std::endl;
if ( WilsonKernelsStatic::Comms == WilsonKernelsStatic::CommsAndCompute ) std::cout << GridLogMessage<< "* Using Overlapped Comms/Compute" <<std::endl;
if ( WilsonKernelsStatic::Comms == WilsonKernelsStatic::CommsThenCompute) std::cout << GridLogMessage<< "* Using sequential Comms/Compute" <<std::endl;
std::cout << GridLogMessage<< "* SINGLE precision "<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
int nwarm = 10;
double t0=usecond();
FGrid->Barrier();
for(int i=0;i<nwarm;i++){
Dw.DhopEO(src_o,r_e,DaggerNo);
}
FGrid->Barrier();
double t1=usecond();
uint64_t ncall = 500;
FGrid->Broadcast(0,&ncall,sizeof(ncall));
// std::cout << GridLogMessage << " Estimate " << ncall << " calls per second"<<std::endl;
time_statistics timestat;
std::vector<double> t_time(ncall);
for(uint64_t i=0;i<ncall;i++){
t0=usecond();
Dw.DhopEO(src_o,r_e,DaggerNo);
t1=usecond();
t_time[i] = t1-t0;
}
FGrid->Barrier();
double volume=Ls; for(int mu=0;mu<Nd;mu++) volume=volume*latt4[mu];
// Nc=3 gives
// 1344= 3*(2*8+6)*2*8 + 8*3*2*2 + 3*4*2*8
// 1344 = Nc* (6+(Nc-1)*8)*2*Nd + Nd*Nc*2*2 + Nd*Nc*Ns*2
// double flops=(1344.0*volume)/2;
double fps = Nc* (6+(Nc-1)*8)*Ns*Nd + 2*Nd*Nc*Ns + 2*Nd*Nc*Ns*2;
double flops=(fps*volume)/2;
double mf_hi, mf_lo, mf_err;
timestat.statistics(t_time);
mf_hi = flops/timestat.min;
mf_lo = flops/timestat.max;
mf_err= flops/timestat.min * timestat.err/timestat.mean;
mflops = flops/timestat.mean;
mflops_all.push_back(mflops);
if ( mflops_best == 0 ) mflops_best = mflops;
if ( mflops_worst== 0 ) mflops_worst= mflops;
if ( mflops>mflops_best ) mflops_best = mflops;
if ( mflops<mflops_worst) mflops_worst= mflops;
std::cout<<GridLogMessage<< "Deo FlopsPerSite is "<<fps<<std::endl;
std::cout<<GridLogMessage << std::fixed << std::setprecision(1)<<"Deo mflop/s = "<< mflops << " ("<<mf_err<<") " << mf_lo<<"-"<<mf_hi <<std::endl;
std::cout<<GridLogMessage << std::fixed << std::setprecision(1)<<"Deo mflop/s per rank "<< mflops/NP<<std::endl;
std::cout<<GridLogMessage << std::fixed << std::setprecision(1)<<"Deo mflop/s per node "<< mflops/NN<<std::endl;
}
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << L<<"^4 x "<<Ls<< " Deo Best mflop/s = "<< mflops_best << " ; " << mflops_best/NN<<" per node " <<std::endl;
std::cout<<GridLogMessage << L<<"^4 x "<<Ls<< " Deo Worst mflop/s = "<< mflops_worst<< " ; " << mflops_worst/NN<<" per node " <<std::endl;
std::cout<<GridLogMessage <<fmt << std::endl;
std::cout<<GridLogMessage ;
for(int i=0;i<mflops_all.size();i++){
std::cout<<mflops_all[i]/NN<<" ; " ;
}
std::cout<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
}
return mflops_best;
}
static double Staggered(int L)
{
double mflops;
double mflops_best = 0;
double mflops_worst= 0;
std::vector<double> mflops_all;
///////////////////////////////////////////////////////
// Set/Get the layout & grid size
///////////////////////////////////////////////////////
int threads = GridThread::GetThreads();
Coordinate mpi = GridDefaultMpi(); assert(mpi.size()==4);
Coordinate local({L,L,L,L});
Coordinate latt4({local[0]*mpi[0],local[1]*mpi[1],local[2]*mpi[2],local[3]*mpi[3]});
GridCartesian * TmpGrid = SpaceTimeGrid::makeFourDimGrid(latt4,
GridDefaultSimd(Nd,vComplex::Nsimd()),
GridDefaultMpi());
uint64_t NP = TmpGrid->RankCount();
uint64_t NN = TmpGrid->NodeCount();
NN_global=NN;
uint64_t SHM=NP/NN;
///////// Welcome message ////////////
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << "Benchmark ImprovedStaggered on "<<L<<"^4 local volume "<<std::endl;
std::cout<<GridLogMessage << "* Global volume : "<<GridCmdVectorIntToString(latt4)<<std::endl;
std::cout<<GridLogMessage << "* ranks : "<<NP <<std::endl;
std::cout<<GridLogMessage << "* nodes : "<<NN <<std::endl;
std::cout<<GridLogMessage << "* ranks/node : "<<SHM <<std::endl;
std::cout<<GridLogMessage << "* ranks geom : "<<GridCmdVectorIntToString(mpi)<<std::endl;
std::cout<<GridLogMessage << "* Using "<<threads<<" threads"<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
///////// Lattice Init ////////////
GridCartesian * FGrid = SpaceTimeGrid::makeFourDimGrid(latt4, GridDefaultSimd(Nd,vComplexF::Nsimd()),GridDefaultMpi());
GridRedBlackCartesian * FrbGrid = SpaceTimeGrid::makeFourDimRedBlackGrid(FGrid);
///////// RNG Init ////////////
std::vector<int> seeds4({1,2,3,4});
GridParallelRNG RNG4(FGrid); RNG4.SeedFixedIntegers(seeds4);
std::cout << GridLogMessage << "Initialised RNGs" << std::endl;
RealD mass=0.1;
RealD c1=9.0/8.0;
RealD c2=-1.0/24.0;
RealD u0=1.0;
typedef ImprovedStaggeredFermionF Action;
typedef typename Action::FermionField Fermion;
typedef LatticeGaugeFieldF Gauge;
Gauge Umu(FGrid); SU<Nc>::HotConfiguration(RNG4,Umu);
typename Action::ImplParams params;
Action Ds(Umu,Umu,*FGrid,*FrbGrid,mass,c1,c2,u0,params);
///////// Source preparation ////////////
Fermion src (FGrid); random(RNG4,src);
Fermion src_e (FrbGrid);
Fermion src_o (FrbGrid);
Fermion r_e (FrbGrid);
Fermion r_o (FrbGrid);
Fermion r_eo (FGrid);
{
pickCheckerboard(Even,src_e,src);
pickCheckerboard(Odd,src_o,src);
const int num_cases = 2;
std::string fmt("G/S/C ; G/O/C ; G/S/S ; G/O/S ");
controls Cases [] = {
{ StaggeredKernelsStatic::OptGeneric , StaggeredKernelsStatic::CommsAndCompute ,CartesianCommunicator::CommunicatorPolicyConcurrent },
{ StaggeredKernelsStatic::OptHandUnroll, StaggeredKernelsStatic::CommsAndCompute ,CartesianCommunicator::CommunicatorPolicyConcurrent },
{ StaggeredKernelsStatic::OptInlineAsm , StaggeredKernelsStatic::CommsAndCompute ,CartesianCommunicator::CommunicatorPolicyConcurrent }
};
for(int c=0;c<num_cases;c++) {
StaggeredKernelsStatic::Comms = Cases[c].CommsOverlap;
StaggeredKernelsStatic::Opt = Cases[c].Opt;
CartesianCommunicator::SetCommunicatorPolicy(Cases[c].CommsAsynch);
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
if ( StaggeredKernelsStatic::Opt == StaggeredKernelsStatic::OptGeneric ) std::cout << GridLogMessage<< "* Using GENERIC Nc StaggeredKernels" <<std::endl;
std::cout << GridLogMessage<< "* SINGLE precision "<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
int nwarm = 10;
double t0=usecond();
FGrid->Barrier();
for(int i=0;i<nwarm;i++){
Ds.DhopEO(src_o,r_e,DaggerNo);
}
FGrid->Barrier();
double t1=usecond();
uint64_t ncall = 500;
FGrid->Broadcast(0,&ncall,sizeof(ncall));
// std::cout << GridLogMessage << " Estimate " << ncall << " calls per second"<<std::endl;
time_statistics timestat;
std::vector<double> t_time(ncall);
for(uint64_t i=0;i<ncall;i++){
t0=usecond();
Ds.DhopEO(src_o,r_e,DaggerNo);
t1=usecond();
t_time[i] = t1-t0;
}
FGrid->Barrier();
double volume=1; for(int mu=0;mu<Nd;mu++) volume=volume*latt4[mu];
double flops=(1146.0*volume)/2;
double mf_hi, mf_lo, mf_err;
timestat.statistics(t_time);
mf_hi = flops/timestat.min;
mf_lo = flops/timestat.max;
mf_err= flops/timestat.min * timestat.err/timestat.mean;
mflops = flops/timestat.mean;
mflops_all.push_back(mflops);
if ( mflops_best == 0 ) mflops_best = mflops;
if ( mflops_worst== 0 ) mflops_worst= mflops;
if ( mflops>mflops_best ) mflops_best = mflops;
if ( mflops<mflops_worst) mflops_worst= mflops;
std::cout<<GridLogMessage << std::fixed << std::setprecision(1)<<"Deo mflop/s = "<< mflops << " ("<<mf_err<<") " << mf_lo<<"-"<<mf_hi <<std::endl;
std::cout<<GridLogMessage << std::fixed << std::setprecision(1)<<"Deo mflop/s per rank "<< mflops/NP<<std::endl;
std::cout<<GridLogMessage << std::fixed << std::setprecision(1)<<"Deo mflop/s per node "<< mflops/NN<<std::endl;
}
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << L<<"^4 Deo Best mflop/s = "<< mflops_best << " ; " << mflops_best/NN<<" per node " <<std::endl;
std::cout<<GridLogMessage << L<<"^4 Deo Worst mflop/s = "<< mflops_worst<< " ; " << mflops_worst/NN<<" per node " <<std::endl;
std::cout<<GridLogMessage <<fmt << std::endl;
std::cout<<GridLogMessage ;
for(int i=0;i<mflops_all.size();i++){
std::cout<<mflops_all[i]/NN<<" ; " ;
}
std::cout<<std::endl;
}
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
return mflops_best;
}
static double Clover(int L)
{
double mflops;
double mflops_best = 0;
double mflops_worst= 0;
std::vector<double> mflops_all;
///////////////////////////////////////////////////////
// Set/Get the layout & grid size
///////////////////////////////////////////////////////
int threads = GridThread::GetThreads();
Coordinate mpi = GridDefaultMpi(); assert(mpi.size()==4);
Coordinate local({L,L,L,L});
Coordinate latt4({local[0]*mpi[0],local[1]*mpi[1],local[2]*mpi[2],local[3]*mpi[3]});
GridCartesian * TmpGrid = SpaceTimeGrid::makeFourDimGrid(latt4,
GridDefaultSimd(Nd,vComplex::Nsimd()),
GridDefaultMpi());
uint64_t NP = TmpGrid->RankCount();
uint64_t NN = TmpGrid->NodeCount();
NN_global=NN;
uint64_t SHM=NP/NN;
///////// Welcome message ////////////
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << "Benchmark Clover on "<<L<<"^4 local volume "<<std::endl;
std::cout<<GridLogMessage << "* Global volume : "<<GridCmdVectorIntToString(latt4)<<std::endl;
std::cout<<GridLogMessage << "* ranks : "<<NP <<std::endl;
std::cout<<GridLogMessage << "* nodes : "<<NN <<std::endl;
std::cout<<GridLogMessage << "* ranks/node : "<<SHM <<std::endl;
std::cout<<GridLogMessage << "* ranks geom : "<<GridCmdVectorIntToString(mpi)<<std::endl;
std::cout<<GridLogMessage << "* Using "<<threads<<" threads"<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
///////// Lattice Init ////////////
GridCartesian * FGrid = SpaceTimeGrid::makeFourDimGrid(latt4, GridDefaultSimd(Nd,vComplexF::Nsimd()),GridDefaultMpi());
GridRedBlackCartesian * FrbGrid = SpaceTimeGrid::makeFourDimRedBlackGrid(FGrid);
///////// RNG Init ////////////
std::vector<int> seeds4({1,2,3,4});
GridParallelRNG RNG4(FGrid); RNG4.SeedFixedIntegers(seeds4);
std::cout << GridLogMessage << "Initialised RNGs" << std::endl;
RealD mass=0.1;
RealD csw=1.0;
typedef WilsonCloverFermionF Action;
typedef typename Action::FermionField Fermion;
typedef LatticeGaugeFieldF Gauge;
Gauge Umu(FGrid); SU<Nc>::HotConfiguration(RNG4,Umu);
Action Dc(Umu,*FGrid,*FrbGrid,mass,csw,csw);
///////// Source preparation ////////////
Fermion src (FGrid); random(RNG4,src);
Fermion r (FGrid);
{
const int num_cases = 1;
std::string fmt("G/S/C ; G/O/C ; G/S/S ; G/O/S ");
controls Cases [] = {
{ WilsonKernelsStatic::OptGeneric , WilsonKernelsStatic::CommsAndCompute ,CartesianCommunicator::CommunicatorPolicyConcurrent },
};
for(int c=0;c<num_cases;c++) {
WilsonKernelsStatic::Comms = Cases[c].CommsOverlap;
WilsonKernelsStatic::Opt = Cases[c].Opt;
CartesianCommunicator::SetCommunicatorPolicy(Cases[c].CommsAsynch);
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout << GridLogMessage<< "* SINGLE precision "<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
int nwarm = 10;
double t0=usecond();
FGrid->Barrier();
for(int i=0;i<nwarm;i++){
Dc.M(src,r);
}
FGrid->Barrier();
double t1=usecond();
uint64_t ncall = 500;
FGrid->Broadcast(0,&ncall,sizeof(ncall));
// std::cout << GridLogMessage << " Estimate " << ncall << " calls per second"<<std::endl;
time_statistics timestat;
std::vector<double> t_time(ncall);
for(uint64_t i=0;i<ncall;i++){
t0=usecond();
Dc.M(src,r);
t1=usecond();
t_time[i] = t1-t0;
}
FGrid->Barrier();
double volume=1; for(int mu=0;mu<Nd;mu++) volume=volume*latt4[mu];
double flops=(1344+ 24+6*6*8*2)*volume;
double mf_hi, mf_lo, mf_err;
timestat.statistics(t_time);
mf_hi = flops/timestat.min;
mf_lo = flops/timestat.max;
mf_err= flops/timestat.min * timestat.err/timestat.mean;
mflops = flops/timestat.mean;
mflops_all.push_back(mflops);
if ( mflops_best == 0 ) mflops_best = mflops;
if ( mflops_worst== 0 ) mflops_worst= mflops;
if ( mflops>mflops_best ) mflops_best = mflops;
if ( mflops<mflops_worst) mflops_worst= mflops;
std::cout<<GridLogMessage << std::fixed << std::setprecision(1)<<"Dclov mflop/s = "<< mflops << " ("<<mf_err<<") " << mf_lo<<"-"<<mf_hi <<std::endl;
std::cout<<GridLogMessage << std::fixed << std::setprecision(1)<<"Dclov mflop/s per rank "<< mflops/NP<<std::endl;
std::cout<<GridLogMessage << std::fixed << std::setprecision(1)<<"Dclov mflop/s per node "<< mflops/NN<<std::endl;
}
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << L<<"^4 Deo Best mflop/s = "<< mflops_best << " ; " << mflops_best/NN<<" per node " <<std::endl;
std::cout<<GridLogMessage << L<<"^4 Deo Worst mflop/s = "<< mflops_worst<< " ; " << mflops_worst/NN<<" per node " <<std::endl;
std::cout<<GridLogMessage <<fmt << std::endl;
std::cout<<GridLogMessage ;
for(int i=0;i<mflops_all.size();i++){
std::cout<<mflops_all[i]/NN<<" ; " ;
}
std::cout<<std::endl;
}
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
return mflops_best;
}
};
int main (int argc, char ** argv)
{
Grid_init(&argc,&argv);
if (GlobalSharedMemory::WorldRank==0) {
FP = fopen("Benchmark_usqcd.csv","w");
} else {
FP = fopen("/dev/null","w");
}
CartesianCommunicator::SetCommunicatorPolicy(CartesianCommunicator::CommunicatorPolicySequential);
LebesgueOrder::Block = std::vector<int>({2,2,2,2});
Benchmark::Decomposition();
int do_su4=0;
int do_memory=1;
int do_comms =1;
int do_blas =1;
int sel=4;
std::vector<int> L_list({8,12,16,24,32});
int selm1=sel-1;
std::vector<double> clover;
std::vector<double> dwf4;
std::vector<double> staggered;
int Ls=1;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " Clover dslash 4D vectorised (temporarily Wilson)" <<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
for(int l=0;l<L_list.size();l++){
clover.push_back(Benchmark::DWF(1,L_list[l]));
}
Ls=12;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " Domain wall dslash 4D vectorised" <<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
for(int l=0;l<L_list.size();l++){
double result = Benchmark::DWF(Ls,L_list[l]) ;
dwf4.push_back(result);
}
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " Improved Staggered dslash 4D vectorised" <<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
for(int l=0;l<L_list.size();l++){
double result = Benchmark::Staggered(L_list[l]) ;
staggered.push_back(result);
}
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " Summary table Ls="<<Ls <<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << "L \t\t Clover \t\t DWF4 \t\t Staggered" <<std::endl;
for(int l=0;l<L_list.size();l++){
std::cout<<GridLogMessage << L_list[l] <<" \t\t "<< clover[l]<<" \t\t "<<dwf4[l] << " \t\t "<< staggered[l]<<std::endl;
}
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
int NN=NN_global;
if ( do_memory ) {
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " Memory benchmark " <<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
Benchmark::Memory();
}
if ( do_blas ) {
#if defined(GRID_CUDA) || defined(GRID_HIP) || defined(GRID_SYCL)
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " Batched BLAS benchmark " <<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
Benchmark::BLAS();
#endif
}
if ( do_su4 ) {
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " SU(4) benchmark " <<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
Benchmark::SU4();
}
if ( do_comms ) {
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " Communications benchmark " <<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
Benchmark::Comms();
}
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " Per Node Summary table Ls="<<Ls <<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " L \t\t Clover\t\t DWF4\t\t Staggered (GF/s per node)" <<std::endl;
fprintf(FP,"Per node summary table\n");
fprintf(FP,"\n");
fprintf(FP,"L , Wilson, DWF4, Staggered, GF/s per node\n");
fprintf(FP,"\n");
for(int l=0;l<L_list.size();l++){
std::cout<<GridLogMessage << L_list[l] <<" \t\t "<< clover[l]/NN<<" \t "<<dwf4[l]/NN<< " \t "<<staggered[l]/NN<<std::endl;
fprintf(FP,"%d , %.0f, %.0f, %.0f\n",L_list[l],clover[l]/NN/1000.,dwf4[l]/NN/1000.,staggered[l]/NN/1000.);
}
fprintf(FP,"\n");
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
std::cout<<GridLogMessage << " Comparison point result: " << 0.5*(dwf4[sel]+dwf4[selm1])/NN << " Mflop/s per node"<<std::endl;
std::cout<<GridLogMessage << " Comparison point is 0.5*("<<dwf4[sel]/NN<<"+"<<dwf4[selm1]/NN << ") "<<std::endl;
std::cout<<std::setprecision(3);
std::cout<<GridLogMessage << "=================================================================================="<<std::endl;
Grid_finalize();
fclose(FP);
}

View File

@ -1,12 +1,12 @@
#!/usr/bin/env bash
set -e
EIGEN_URL='https://gitlab.com/libeigen/eigen/-/archive/3.3.7/eigen-3.3.7.tar.bz2'
EIGEN_SHA256SUM='685adf14bd8e9c015b78097c1dc22f2f01343756f196acdc76a678e1ae352e11'
EIGEN_URL='https://gitlab.com/libeigen/eigen/-/archive/3.4.0/eigen-3.4.0.tar.bz2'
EIGEN_SHA256SUM='b4c198460eba6f28d34894e3a5710998818515104d6e74e5cc331ce31e46e626'
echo "-- deploying Eigen source..."
ARC=`basename ${EIGEN_URL}`
ARC=$(basename ${EIGEN_URL})
wget ${EIGEN_URL} --no-check-certificate
if command -v sha256sum; then
echo "$EIGEN_SHA256SUM $(basename "$EIGEN_URL")" \
@ -14,13 +14,8 @@ if command -v sha256sum; then
else
echo "WARNING: could not verify checksum, please install sha256sum" >&2
fi
./scripts/update_eigen.sh ${ARC}
rm ${ARC}
# patch for non-portable includes in Eigen 3.3.5
# apparently already fixed in Eigen HEAD so it should not be
# a problem in the future (A.P.)
patch Eigen/unsupported/Eigen/CXX11/Tensor scripts/eigen-3.3.5.Tensor.patch
./scripts/update_eigen.sh "${ARC}"
rm "${ARC}"
echo '-- generating Make.inc files...'
./scripts/filelist
echo '-- generating configure script...'

View File

@ -0,0 +1,183 @@
/*
* Example_plaquette.cc
*
* D. Clarke
*
* Here I just want to create an incredibly simple main to get started with GRID and get used
* to its syntax. If the reader is like me, they vaguely understand something about lattice coding,
* they don't know a ton of C++, don't know much of the fine details, and certainly know nothing about GRID.
*
* Once you've made a new executable, like this one, you can bootstrap.sh again. At this point,
* the code should be able to find your new executable. You can tell that bootstrap.sh worked by
* having a look at Make.inc. You should see your executable inside there.
*
* Warning: This code illustrative only, not well tested, and not meant for production use. The best
* way to read this code is to start at the main.
*
*/
// All your mains should have this
#include <Grid/Grid.h>
using namespace Grid;
// This copies what already exists in WilsonLoops.h. The point here is to be pedagogical and explain in
// detail what everything does so we can see how GRID works.
template <class Gimpl> class WLoops : public Gimpl {
public:
// Gimpl seems to be an arbitrary class. Within this class, it is expected that certain types are
// already defined, things like Scalar and Field. This macro includes a bunch of #typedefs that
// implement this equivalence at compile time.
INHERIT_GIMPL_TYPES(Gimpl);
// Some example Gimpls can be found in GaugeImplementations.h, at the bottom. These are in turn built
// out of GaugeImplTypes, which can be found in GaugeImplTypes.h. The GaugeImplTypes contain the base
// field/vector/link/whatever types. These inherit from iScalar, iVector, and iMatrix objects, which
// are sort of the building blocks for gerenal math objects. The "i" at the beginning of these names
// indicates that they should be for internal use only. It seems like these base types have the
// acceleration, e.g. SIMD or GPU or what-have-you, abstracted away. How you accelerate these things
// appears to be controlled through a template parameter called vtype.
// The general math/physics objects, such as a color matrix, are built up by nesting these objects.
// For instance a general color matrix has two color indices, so it's built up like
// iScalar<iScalar<iMatrix<vtype ...
// where the levels going from the inside out are color, spin, then Lorentz indices. Scalars have
// no indices, so it's what we use when such an index isn't needed. Lattice objects are made by one
// higher level of indexing using iVector.
// These types will be used for U and U_mu objects, respectively.
typedef typename Gimpl::GaugeLinkField GaugeMat;
typedef typename Gimpl::GaugeField GaugeLorentz;
// U_mu_nu(x)
static void dirPlaquette(GaugeMat &plaq, const std::vector<GaugeMat> &U, const int mu, const int nu) {
// Calls like CovShiftForward and CovShiftBackward have 3 arguments, and they multiply together
// the first and last argument. (Second arg gives the shift direction.) The CovShiftIdentityBackward
// has meanwhile only two arguments; it just returns the shifted (adjoint since backward) link.
plaq = Gimpl::CovShiftForward(U[mu],mu,
// Means Link*Cshift(field,mu,1), arguments are Link, mu, field in that order.
Gimpl::CovShiftForward(U[nu],nu,
Gimpl::CovShiftBackward(U[mu],mu,
// This means Cshift(adj(Link), mu, -1)
Gimpl::CovShiftIdentityBackward(U[nu], nu))));
}
// tr U_mu_nu(x)
static void traceDirPlaquette(ComplexField &plaq, const std::vector<GaugeMat> &U, const int mu, const int nu) {
// This .Grid() syntax seems to get the pointer to the GridBase. Apparently this is needed as argument
// to instantiate a Lattice object.
GaugeMat sp(U[0].Grid());
dirPlaquette(sp, U, mu, nu);
plaq = trace(sp);
}
// sum_mu_nu tr U_mu_nu(x)
static void sitePlaquette(ComplexField &Plaq, const std::vector<GaugeMat> &U) {
ComplexField sitePlaq(U[0].Grid());
Plaq = Zero();
// Nd=4 and Nc=3 are set as global constants in QCD.h
for (int mu = 1; mu < Nd; mu++) {
for (int nu = 0; nu < mu; nu++) {
traceDirPlaquette(sitePlaq, U, mu, nu);
Plaq = Plaq + sitePlaq;
}
}
}
// sum_mu_nu_x Re tr U_mu_nu(x)
static RealD sumPlaquette(const GaugeLorentz &Umu) {
std::vector<GaugeMat> U(Nd, Umu.Grid());
for (int mu = 0; mu < Nd; mu++) {
// Umu is a GaugeLorentz object, and as such has a non-trivial Lorentz index. We can
// access the element in the mu Lorentz index with this PeekIndex syntax.
U[mu] = PeekIndex<LorentzIndex>(Umu, mu);
}
ComplexField Plaq(Umu.Grid());
sitePlaquette(Plaq, U);
// I guess this should be the line that sums over all space-time sites.
auto Tp = sum(Plaq);
// Until now, we have been working with objects inside the tensor nest. This TensorRemove gets
// rid of the tensor nest to return whatever is inside.
auto p = TensorRemove(Tp);
return p.real();
}
// < Re tr U_mu_nu(x) >
static RealD avgPlaquette(const GaugeLorentz &Umu) {
// Real double type
RealD sumplaq = sumPlaquette(Umu);
// gSites() is the number of global sites. there is also lSites() for local sites.
double vol = Umu.Grid()->gSites();
// The number of orientations. 4*3/2=6 for Nd=4, as known.
double faces = (1.0 * Nd * (Nd - 1)) / 2.0;
return sumplaq / vol / faces / Nc;
}
};
// Next we show an example of how to construct an input parameter class. We first inherit
// from Serializable. Then all class data members have to be defined using the
// GRID_SERIALIZABLE_CLASS_MEMBERS macro. This variadic macro allows for arbitrarily many
// class data members. In the below case, we make a parameter file holding the configuration
// name. Here, it expects the name to be labeled with "conf_name" in the configuration file.
struct ConfParameters: Serializable {
GRID_SERIALIZABLE_CLASS_MEMBERS(
ConfParameters,
std::string, conf_name);
template <class ReaderClass>
ConfParameters(Reader<ReaderClass>& Reader){
// If we are reading an XML file, it should be structured like:
// <grid>
// <parameters>
// <conf_name>l20t20b06498a_nersc.302500</conf_name>
// </parameters>
// </grid>
read(Reader, "parameters", *this);
}
};
// This syntax lets you pass command line arguments to main. An asterisk means that what follows is
// a pointer. Two asterisks means what follows is a pointer to an array.
int main (int argc, char **argv)
{
// This initializes Grid. Some command line options include
// --mpi n.n.n.n
// --threads n
// --grid n.n.n.n
Grid_init(&argc, &argv);
// This is where you would specify a custom lattice size, if not from the command line. Here
// Nd is a global quantity that is currently set to 4.
Coordinate simd_layout = GridDefaultSimd(Nd,vComplex::Nsimd());
Coordinate mpi_layout = GridDefaultMpi();
Coordinate latt_size = GridDefaultLatt();
// Instantiate the spacetime Grid on which everything will be built.
GridCartesian GRID(latt_size,simd_layout,mpi_layout);
// The PeriodicGimplD type is what you want for gauge matrices. There is also a LatticeGaugeFieldD
// type that you can use, which will work perfectly with what follows.
PeriodicGimplD::Field U(&GRID);
// Here we read in the parameter file params.json to get conf_name. The last argument is what the
// top organizational level is called in the param file.
XmlReader Reader("Example_plaquette.xml",false, "grid");
ConfParameters param(Reader);
// Load a lattice from SIMULATeQCD into U. SIMULATeQCD finds plaquette = 0.6381995717
FieldMetaData header;
NerscIO::readConfiguration(U, header, param.conf_name);
// Let's see what we find.
RealD plaq = WLoops<PeriodicGimplD>::avgPlaquette(U);
// This is how you make log messages.
std::cout << GridLogMessage << std::setprecision(std::numeric_limits<Real>::digits10 + 1) << "Plaquette = " << plaq << std::endl;
// To wrap things up.
Grid_finalize();
}

View File

@ -1,19 +0,0 @@
--- ./Eigen/unsupported/Eigen/CXX11/Tensor 2018-07-23 10:33:42.000000000 +0100
+++ Tensor 2018-08-28 16:15:56.000000000 +0100
@@ -25,7 +25,7 @@
#include <utility>
#endif
-#include <Eigen/src/Core/util/DisableStupidWarnings.h>
+#include "../../../Eigen/src/Core/util/DisableStupidWarnings.h"
#include "../SpecialFunctions"
#include "src/util/CXX11Meta.h"
@@ -147,6 +147,6 @@
#include "src/Tensor/TensorIO.h"
-#include <Eigen/src/Core/util/ReenableStupidWarnings.h>
+#include "../../../Eigen/src/Core/util/ReenableStupidWarnings.h"
//#endif // EIGEN_CXX11_TENSOR_MODULE

View File

@ -25,12 +25,16 @@ export MPIR_CVAR_CH4_OFI_ENABLE_GPU_PIPELINE=1
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_D2H_ENGINE_TYPE=0
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_H2D_ENGINE_TYPE=0
export MPIR_CVAR_GPU_USE_IMMEDIATE_COMMAND_LIST=1
#export MPIR_CVAR_GPU_USE_IMMEDIATE_COMMAND_LIST=1
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_BUFFER_SZ=1048576
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_THRESHOLD=131072
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_NUM_BUFFERS_PER_CHUNK=16
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_MAX_NUM_BUFFERS=16
export MPICH_OFI_NIC_POLICY=GPU
export FI_CXI_CQ_FILL_PERCENT=10
export FI_CXI_DEFAULT_CQ_SIZE=262144
#export FI_CXI_DEFAULT_CQ_SIZE=131072
#export FI_CXI_CQ_FILL_PERCENT=20
# 12 ppn, 32 nodes, 384 ranks
#
@ -45,12 +49,12 @@ CMD="mpiexec -np 12288 -ppn 12 -envall \
./gpu_tile_compact.sh \
./Benchmark_dwf_fp32 --mpi 8.8.8.24 --grid 128.128.128.384 \
--shm-mpi 1 --shm 2048 --device-mem 32000 --accelerator-threads 32 --comms-overlap"
$CMD | tee 1024node.dwf.small
$CMD | tee 1024node.dwf.small.cq
CMD="mpiexec -np 12288 -ppn 12 -envall \
./gpu_tile_compact.sh \
./Benchmark_dwf_fp32 --mpi 16.8.8.12 --grid 256.256.256.384 \
--shm-mpi 1 --shm 2048 --device-mem 32000 --accelerator-threads 32 --comms-overlap"
$CMD | tee 1024node.dwf
$CMD | tee 1024node.dwf.cq

View File

@ -17,6 +17,7 @@ source ../sourceme.sh
export OMP_NUM_THREADS=3
export MPIR_CVAR_CH4_OFI_ENABLE_GPU_PIPELINE=1
#unset MPIR_CVAR_CH4_OFI_GPU_PIPELINE_D2H_ENGINE_TYPE
#unset MPIR_CVAR_CH4_OFI_GPU_PIPELINE_H2D_ENGINE_TYPE
#unset MPIR_CVAR_GPU_USE_IMMEDIATE_COMMAND_LIST
@ -35,11 +36,25 @@ CMD="mpiexec -np 24 -ppn 12 -envall \
./Benchmark_comms_host_device --mpi 2.3.2.2 --grid 32.24.32.192 \
--shm-mpi 1 --shm 2048 --device-mem 32000 --accelerator-threads 32"
$CMD
#$CMD
CMD="mpiexec -np 24 -ppn 12 -envall \
./gpu_tile_compact.sh \
./Benchmark_dwf_fp32 --mpi 2.3.2.2 --grid 64.96.64.64 --comms-overlap \
--shm-mpi 1 --shm 2048 --device-mem 32000 --accelerator-threads 32"
#$CMD
CMD="mpiexec -np 1 -ppn 1 -envall \
./gpu_tile_compact.sh \
./Benchmark_dwf --mpi 1.1.1.1 --grid 16.32.32.32 --comms-sequential \
--shm-mpi 1 --shm 2048 --device-mem 32000 --accelerator-threads 32"
$CMD
CMD="mpiexec -np 1 -ppn 1 -envall \
./gpu_tile_compact.sh \
./Benchmark_dwf_fp32 --mpi 1.1.1.1 --grid 16.32.32.32 --comms-sequential \
--shm-mpi 1 --shm 2048 --device-mem 32000 --accelerator-threads 32"
$CMD

View File

@ -11,6 +11,6 @@ TOOLS=$HOME/tools
--enable-unified=no \
MPICXX=mpicxx \
CXX=icpx \
LDFLAGS="-fiopenmp -fsycl -fsycl-device-code-split=per_kernel -fsycl-device-lib=all -lze_loader -L$TOOLS/lib64/" \
CXXFLAGS="-fiopenmp -fsycl-unnamed-lambda -fsycl -I$INSTALL/include -Wno-tautological-compare -I$HOME/ -I$TOOLS/include"
LDFLAGS="-fiopenmp -fsycl -fsycl-device-code-split=per_kernel -fsycl-device-lib=all -lze_loader -L$TOOLS/lib64/ -L${MKLROOT}/lib -qmkl=parallel " \
CXXFLAGS="-fiopenmp -fsycl-unnamed-lambda -fsycl -I$INSTALL/include -Wno-tautological-compare -I$HOME/ -I$TOOLS/include -qmkl=parallel"

View File

@ -3,10 +3,24 @@
module use /soft/modulefiles
module load intel_compute_runtime/release/agama-devel-682.22
export FI_CXI_DEFAULT_CQ_SIZE=131072
export FI_CXI_CQ_FILL_PERCENT=20
export SYCL_PROGRAM_COMPILE_OPTIONS="-ze-opt-large-register-file"
#export SYCL_PROGRAM_COMPILE_OPTIONS="-ze-intel-enable-auto-large-GRF-mode"
#
# -ftarget-register-alloc-mode=pvc:default
# -ftarget-register-alloc-mode=pvc:small
# -ftarget-register-alloc-mode=pvc:large
# -ftarget-register-alloc-mode=pvc:auto
#
export HTTP_PROXY=http://proxy.alcf.anl.gov:3128
export HTTPS_PROXY=http://proxy.alcf.anl.gov:3128
export http_proxy=http://proxy.alcf.anl.gov:3128
export https_proxy=http://proxy.alcf.anl.gov:3128
#export MPIR_CVAR_CH4_OFI_ENABLE_HMEM=1
git config --global http.proxy http://proxy.alcf.anl.gov:3128
export SYCL_PROGRAM_COMPILE_OPTIONS="-ze-opt-large-register-file"

View File

@ -0,0 +1,41 @@
#!/bin/bash
## qsub -q EarlyAppAccess -A Aurora_Deployment -I -l select=1 -l walltime=60:00
#PBS -q EarlyAppAccess
#PBS -l select=128
#PBS -l walltime=02:00:00
#PBS -A LatticeQCD_aesp_CNDA
#export OMP_PROC_BIND=spread
#unset OMP_PLACES
cd $PBS_O_WORKDIR
source ../sourceme.sh
cat $PBS_NODEFILE
export OMP_NUM_THREADS=3
export MPIR_CVAR_CH4_OFI_ENABLE_GPU_PIPELINE=1
#unset MPIR_CVAR_CH4_OFI_GPU_PIPELINE_D2H_ENGINE_TYPE
#unset MPIR_CVAR_CH4_OFI_GPU_PIPELINE_H2D_ENGINE_TYPE
#unset MPIR_CVAR_GPU_USE_IMMEDIATE_COMMAND_LIST
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_D2H_ENGINE_TYPE=0
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_H2D_ENGINE_TYPE=0
export MPIR_CVAR_GPU_USE_IMMEDIATE_COMMAND_LIST=1
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_BUFFER_SZ=1048576
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_THRESHOLD=131072
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_NUM_BUFFERS_PER_CHUNK=16
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_MAX_NUM_BUFFERS=16
export MPICH_OFI_NIC_POLICY=GPU
# 12 ppn, 16 nodes, 192 ranks
# 12 ppn, 128 nodes, 1536 ranks
CMD="mpiexec -np 1536 -ppn 12 -envall \
./gpu_tile_compact.sh \
./Test_dwf_mixedcg_prec --mpi 4.4.4.24 --grid 128.128.128.384 \
--shm-mpi 1 --shm 4096 --device-mem 32000 --accelerator-threads 32 --seconds 7000 --comms-overlap "
$CMD

View File

@ -0,0 +1,41 @@
#!/bin/bash
## qsub -q EarlyAppAccess -A Aurora_Deployment -I -l select=1 -l walltime=60:00
#PBS -q EarlyAppAccess
#PBS -l select=16
#PBS -l walltime=02:00:00
#PBS -A LatticeQCD_aesp_CNDA
#export OMP_PROC_BIND=spread
#unset OMP_PLACES
cd $PBS_O_WORKDIR
source ../sourceme.sh
cat $PBS_NODEFILE
export OMP_NUM_THREADS=3
export MPIR_CVAR_CH4_OFI_ENABLE_GPU_PIPELINE=1
#unset MPIR_CVAR_CH4_OFI_GPU_PIPELINE_D2H_ENGINE_TYPE
#unset MPIR_CVAR_CH4_OFI_GPU_PIPELINE_H2D_ENGINE_TYPE
#unset MPIR_CVAR_GPU_USE_IMMEDIATE_COMMAND_LIST
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_D2H_ENGINE_TYPE=0
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_H2D_ENGINE_TYPE=0
export MPIR_CVAR_GPU_USE_IMMEDIATE_COMMAND_LIST=1
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_BUFFER_SZ=1048576
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_THRESHOLD=131072
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_NUM_BUFFERS_PER_CHUNK=16
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_MAX_NUM_BUFFERS=16
export MPICH_OFI_NIC_POLICY=GPU
# 12 ppn, 16 nodes, 192 ranks
CMD="mpiexec -np 192 -ppn 12 -envall \
./gpu_tile_compact.sh \
./Test_dwf_mixedcg_prec --mpi 2.4.4.6 --grid 64.128.128.192 \
--shm-mpi 1 --shm 4096 --device-mem 32000 --accelerator-threads 32 --seconds 6000 "
#--comms-overlap
$CMD

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@ -0,0 +1,40 @@
#!/bin/bash
## qsub -q EarlyAppAccess -A Aurora_Deployment -I -l select=1 -l walltime=60:00
#PBS -q EarlyAppAccess
#PBS -l select=16
#PBS -l walltime=01:00:00
#PBS -A LatticeQCD_aesp_CNDA
#export OMP_PROC_BIND=spread
#unset OMP_PLACES
cd $PBS_O_WORKDIR
source ../../sourceme.sh
cat $PBS_NODEFILE
export OMP_NUM_THREADS=3
export MPIR_CVAR_CH4_OFI_ENABLE_GPU_PIPELINE=1
#unset MPIR_CVAR_CH4_OFI_GPU_PIPELINE_D2H_ENGINE_TYPE
#unset MPIR_CVAR_CH4_OFI_GPU_PIPELINE_H2D_ENGINE_TYPE
#unset MPIR_CVAR_GPU_USE_IMMEDIATE_COMMAND_LIST
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_D2H_ENGINE_TYPE=0
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_H2D_ENGINE_TYPE=0
export MPIR_CVAR_GPU_USE_IMMEDIATE_COMMAND_LIST=1
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_BUFFER_SZ=1048576
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_THRESHOLD=131072
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_NUM_BUFFERS_PER_CHUNK=16
export MPIR_CVAR_CH4_OFI_GPU_PIPELINE_MAX_NUM_BUFFERS=16
export MPICH_OFI_NIC_POLICY=GPU
# 12 ppn, 16 nodes, 192 ranks
CMD="mpiexec -np 192 -ppn 12 -envall \
./gpu_tile_compact.sh \
./Test_staggered_cg_prec --mpi 2.4.4.6 --grid 128.128.128.192 \
--shm-mpi 1 --shm 4096 --device-mem 32000 --accelerator-threads 32 --seconds 3000 --comms-overlap"
$CMD

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@ -0,0 +1,70 @@
Memory Bandwidth
Bytes, GB/s per node
3145728, 225.900365
50331648, 2858.859504
254803968, 4145.556367
805306368, 4905.772480
1966080000, 4978.312557
GEMM
M, N, K, BATCH, GF/s per rank
16, 8, 16, 256, 1.713639
16, 16, 16, 256, 288.268316
16, 32, 16, 256, 597.053950
32, 8, 32, 256, 557.382591
32, 16, 32, 256, 1100.145311
32, 32, 32, 256, 1885.080449
64, 8, 64, 256, 1725.163599
64, 16, 64, 256, 3389.336566
64, 32, 64, 256, 4168.252422
16, 8, 256, 256, 1326.262134
16, 16, 256, 256, 2318.095475
16, 32, 256, 256, 3555.436503
32, 8, 256, 256, 1920.139170
32, 16, 256, 256, 3486.174753
32, 32, 256, 256, 5320.821724
64, 8, 256, 256, 2539.597502
64, 16, 256, 256, 5003.456775
64, 32, 256, 256, 7837.531562
8, 256, 16, 256, 1427.848170
16, 256, 16, 256, 2222.147815
32, 256, 16, 256, 2877.121715
8, 256, 32, 256, 1922.890086
16, 256, 32, 256, 3199.469082
32, 256, 32, 256, 4845.405343
8, 256, 64, 256, 2639.483343
16, 256, 64, 256, 5012.800299
32, 256, 64, 256, 7216.006882
Communications
Packet bytes, direction, GB/s per node
4718592, 2, 206.570734
4718592, 3, 207.501847
4718592, 6, 189.730277
4718592, 7, 204.301218
15925248, 2, 307.882997
15925248, 3, 287.901076
15925248, 6, 295.603109
15925248, 7, 300.682033
37748736, 2, 331.740364
37748736, 3, 338.610627
37748736, 6, 332.580657
37748736, 7, 336.336579
Per node summary table
L , Wilson, DWF4, Staggered, GF/s per node
8 , 16, 1165, 10
12 , 473, 4901, 163
16 , 1436, 8464, 442
24 , 4133, 10139, 1530
32 , 5726, 11487, 2518
1 Memory Bandwidth
2 Bytes, GB/s per node
3 3145728, 225.900365
4 50331648, 2858.859504
5 254803968, 4145.556367
6 805306368, 4905.772480
7 1966080000, 4978.312557
8 GEMM
9 M, N, K, BATCH, GF/s per rank
10 16, 8, 16, 256, 1.713639
11 16, 16, 16, 256, 288.268316
12 16, 32, 16, 256, 597.053950
13 32, 8, 32, 256, 557.382591
14 32, 16, 32, 256, 1100.145311
15 32, 32, 32, 256, 1885.080449
16 64, 8, 64, 256, 1725.163599
17 64, 16, 64, 256, 3389.336566
18 64, 32, 64, 256, 4168.252422
19 16, 8, 256, 256, 1326.262134
20 16, 16, 256, 256, 2318.095475
21 16, 32, 256, 256, 3555.436503
22 32, 8, 256, 256, 1920.139170
23 32, 16, 256, 256, 3486.174753
24 32, 32, 256, 256, 5320.821724
25 64, 8, 256, 256, 2539.597502
26 64, 16, 256, 256, 5003.456775
27 64, 32, 256, 256, 7837.531562
28 8, 256, 16, 256, 1427.848170
29 16, 256, 16, 256, 2222.147815
30 32, 256, 16, 256, 2877.121715
31 8, 256, 32, 256, 1922.890086
32 16, 256, 32, 256, 3199.469082
33 32, 256, 32, 256, 4845.405343
34 8, 256, 64, 256, 2639.483343
35 16, 256, 64, 256, 5012.800299
36 32, 256, 64, 256, 7216.006882
37 Communications
38 Packet bytes, direction, GB/s per node
39 4718592, 2, 206.570734
40 4718592, 3, 207.501847
41 4718592, 6, 189.730277
42 4718592, 7, 204.301218
43 15925248, 2, 307.882997
44 15925248, 3, 287.901076
45 15925248, 6, 295.603109
46 15925248, 7, 300.682033
47 37748736, 2, 331.740364
48 37748736, 3, 338.610627
49 37748736, 6, 332.580657
50 37748736, 7, 336.336579
51 Per node summary table
52 L , Wilson, DWF4, Staggered, GF/s per node
53 8 , 16, 1165, 10
54 12 , 473, 4901, 163
55 16 , 1436, 8464, 442
56 24 , 4133, 10139, 1530
57 32 , 5726, 11487, 2518

View File

@ -5,10 +5,12 @@ LIME=/p/home/jusers/boyle2/juwels/gm2dwf/boyle/
--enable-gen-simd-width=64 \
--enable-shm=nvlink \
--enable-accelerator=cuda \
--disable-gparity \
--disable-fermion-reps \
--with-lime=$LIME \
--disable-accelerator-cshift \
--enable-accelerator-cshift \
--disable-unified \
CXX=nvcc \
LDFLAGS="-cudart shared " \
CXXFLAGS="-ccbin mpicxx -gencode arch=compute_80,code=sm_80 -std=c++14 -cudart shared"
CXXFLAGS="-ccbin mpicxx -gencode arch=compute_80,code=sm_80 -std=c++17 -cudart shared -lcublas"

View File

@ -1,5 +1,5 @@
module load GCC/9.3.0
module load GMP/6.2.0
module load MPFR/4.1.0
module load OpenMPI/4.1.0rc1
module load CUDA/11.3
module load GCC
module load GMP
module load MPFR
module load OpenMPI
module load CUDA

View File

@ -16,7 +16,7 @@ CLIME=`spack find --paths c-lime@2-3-9 | grep c-lime| cut -c 15-`
--disable-fermion-reps \
CXX=hipcc MPICXX=mpicxx \
CXXFLAGS="-fPIC -I{$ROCM_PATH}/include/ -I${MPICH_DIR}/include -L/lib64 -fgpu-sanitize" \
LDFLAGS="-L/lib64 -L${MPICH_DIR}/lib -lmpi -L${CRAY_MPICH_ROOTDIR}/gtl/lib -lmpi_gtl_hsa -lamdhip64 "
LDFLAGS="-L/lib64 -L${MPICH_DIR}/lib -lmpi -L${CRAY_MPICH_ROOTDIR}/gtl/lib -lmpi_gtl_hsa -lamdhip64 -lhipblas -lrocblas"

View File

@ -1,3 +1,5 @@
export https_proxy=http://proxy-chain.intel.com:911
module load intel-release
module load intel/mpich
export MPIR_CVAR_CH4_OFI_ENABLE_GPU_PIPELINE=1
export SYCL_PROGRAM_COMPILE_OPTIONS="-ze-opt-large-register-file"

View File

@ -1,4 +1,3 @@
BREW=/opt/local/
MPICXX=mpicxx ../../configure --enable-simd=GEN --enable-comms=mpi-auto --enable-unified=yes --prefix $HOME/QCD/GridInstall --with-lime=/Users/peterboyle/QCD/SciDAC/install/ --with-openssl=$BREW --disable-fermion-reps --disable-gparity --disable-debug
CXXFLAGS=-I/opt/local/include LDFLAGS=-L/opt/local/lib/ CXX=c++-13 MPICXX=mpicxx ../../configure --enable-simd=GEN --enable-comms=mpi-auto --enable-unified=yes --prefix $HOME/QCD/GridInstall --with-lime=/Users/peterboyle/QCD/SciDAC/install/ --with-openssl=$BREW --disable-fermion-reps --disable-gparity --disable-debug

View File

@ -30,27 +30,20 @@ Author: Peter Boyle <paboyle@ph.ed.ac.uk>
using namespace std;
using namespace Grid;
template<class d>
struct scal {
d internal;
};
Gamma::Algebra Gmu [] = {
Gamma::Algebra::GammaX,
Gamma::Algebra::GammaY,
Gamma::Algebra::GammaZ,
Gamma::Algebra::GammaT
};
#ifndef HOST_NAME_MAX
#define HOST_NAME_MAX _POSIX_HOST_NAME_MAX
#endif
int main (int argc, char ** argv)
{
char hostname[HOST_NAME_MAX+1];
gethostname(hostname, HOST_NAME_MAX+1);
std::string host(hostname);
Grid_init(&argc,&argv);
const int Ls=12;
std::cout << GridLogMessage << "::::: NB: to enable a quick bit reproducibility check use the --checksums flag. " << std::endl;
{
GridCartesian * UGrid = SpaceTimeGrid::makeFourDimGrid(GridDefaultLatt(), GridDefaultSimd(Nd,vComplexD::Nsimd()),GridDefaultMpi());
GridRedBlackCartesian * UrbGrid = SpaceTimeGrid::makeFourDimRedBlackGrid(UGrid);
GridCartesian * FGrid = SpaceTimeGrid::makeFiveDimGrid(Ls,UGrid);
@ -92,7 +85,14 @@ int main (int argc, char ** argv)
SchurDiagMooeeOperator<DomainWallFermionD,LatticeFermionD> HermOpEO(Ddwf);
SchurDiagMooeeOperator<DomainWallFermionF,LatticeFermionF> HermOpEO_f(Ddwf_f);
std::cout << GridLogMessage << "::::::::::::: Starting mixed CG" << std::endl;
int nsecs=600;
if( GridCmdOptionExists(argv,argv+argc,"--seconds") ){
std::string arg = GridCmdOptionPayload(argv,argv+argc,"--seconds");
GridCmdOptionInt(arg,nsecs);
}
std::cout << GridLogMessage << "::::::::::::: Starting mixed CG for "<<nsecs <<" seconds" << std::endl;
MixedPrecisionConjugateGradient<LatticeFermionD,LatticeFermionF> mCG(1.0e-8, 10000, 50, FrbGrid_f, HermOpEO_f, HermOpEO);
double t1,t2,flops;
double MdagMsiteflops = 1452; // Mobius (real coeffs)
@ -101,7 +101,19 @@ int main (int argc, char ** argv)
std:: cout << " MdagM site flops = "<< 4*MdagMsiteflops<<std::endl;
std:: cout << " CG site flops = "<< CGsiteflops <<std::endl;
int iters;
for(int i=0;i<10;i++){
time_t start = time(NULL);
uint32_t csum, csumref;
csumref=0;
int iter=0;
do {
if ( iter == 0 ) {
SetGridNormLoggingMode(GridNormLoggingModeRecord);
} else {
SetGridNormLoggingMode(GridNormLoggingModeVerify);
}
std::cerr << "******************* SINGLE PRECISION SOLVE "<<iter<<std::endl;
result_o = Zero();
t1=usecond();
mCG(src_o,result_o);
@ -111,10 +123,33 @@ int main (int argc, char ** argv)
flops+= CGsiteflops*FrbGrid->gSites()*iters;
std::cout << " SinglePrecision iterations/sec "<< iters/(t2-t1)*1000.*1000.<<std::endl;
std::cout << " SinglePrecision GF/s "<< flops/(t2-t1)/1000.<<std::endl;
}
std::cout << GridLogMessage << "::::::::::::: Starting regular CG" << std::endl;
csum = crc(result_o);
if ( csumref == 0 ) {
csumref = csum;
} else {
if ( csum != csumref ) {
std::cerr << host<<" FAILURE " <<iter <<" csum "<<std::hex<<csum<< " != "<<csumref <<std::dec<<std::endl;
assert(0);
} else {
std::cout << host <<" OK " <<iter <<" csum "<<std::hex<<csum<<std::dec<<" -- OK! "<<std::endl;
}
}
iter ++;
} while (time(NULL) < (start + nsecs/2) );
std::cout << GridLogMessage << "::::::::::::: Starting double precision CG" << std::endl;
ConjugateGradient<LatticeFermionD> CG(1.0e-8,10000);
for(int i=0;i<1;i++){
csumref=0;
int i=0;
do {
if ( iter == 0 ) {
SetGridNormLoggingMode(GridNormLoggingModeRecord);
} else {
SetGridNormLoggingMode(GridNormLoggingModeVerify);
}
std::cerr << "******************* DOUBLE PRECISION SOLVE "<<i<<std::endl;
result_o_2 = Zero();
t1=usecond();
CG(HermOpEO,src_o,result_o_2);
@ -122,46 +157,30 @@ int main (int argc, char ** argv)
iters = CG.IterationsToComplete;
flops = MdagMsiteflops*4*FrbGrid->gSites()*iters;
flops+= CGsiteflops*FrbGrid->gSites()*iters;
std::cout << " DoublePrecision iterations/sec "<< iters/(t2-t1)*1000.*1000.<<std::endl;
std::cout << " DoublePrecision GF/s "<< flops/(t2-t1)/1000.<<std::endl;
}
// MemoryManager::Print();
csum = crc(result_o);
if ( csumref == 0 ) {
csumref = csum;
} else {
if ( csum != csumref ) {
std::cerr << i <<" csum "<<std::hex<<csum<< " != "<<csumref <<std::dec<<std::endl;
assert(0);
} else {
std::cout << i <<" csum "<<std::hex<<csum<<std::dec<<" -- OK! "<<std::endl;
}
}
i++;
} while (time(NULL) < (start + nsecs) );
LatticeFermionD diff_o(FrbGrid);
RealD diff = axpy_norm(diff_o, -1.0, result_o, result_o_2);
std::cout << GridLogMessage << "::::::::::::: Diff between mixed and regular CG: " << diff << std::endl;
#ifdef HAVE_LIME
if( GridCmdOptionExists(argv,argv+argc,"--checksums") ){
assert(diff < 1e-4);
std::string file1("./Propagator1");
emptyUserRecord record;
uint32_t nersc_csum;
uint32_t scidac_csuma;
uint32_t scidac_csumb;
typedef SpinColourVectorD FermionD;
typedef vSpinColourVectorD vFermionD;
BinarySimpleMunger<FermionD,FermionD> munge;
std::string format = getFormatString<vFermionD>();
BinaryIO::writeLatticeObject<vFermionD,FermionD>(result_o,file1,munge, 0, format,
nersc_csum,scidac_csuma,scidac_csumb);
std::cout << GridLogMessage << " Mixed checksums "<<std::hex << scidac_csuma << " "<<scidac_csumb<<std::endl;
BinaryIO::writeLatticeObject<vFermionD,FermionD>(result_o_2,file1,munge, 0, format,
nersc_csum,scidac_csuma,scidac_csumb);
std::cout << GridLogMessage << " CG checksums "<<std::hex << scidac_csuma << " "<<scidac_csumb<<std::endl;
}
#endif
}
MemoryManager::Print();
Grid_finalize();
}

321
tests/core/Test_sliceSum.cc Normal file
View File

@ -0,0 +1,321 @@
#include <Grid/Grid.h>
template<class vobj> inline void sliceSumCPU(const Grid::Lattice<vobj> &Data,std::vector<typename vobj::scalar_object> &result,int orthogdim)
{
using namespace Grid;
///////////////////////////////////////////////////////
// FIXME precision promoted summation
// may be important for correlation functions
// But easily avoided by using double precision fields
///////////////////////////////////////////////////////
typedef typename vobj::scalar_object sobj;
typedef typename vobj::scalar_object::scalar_type scalar_type;
GridBase *grid = Data.Grid();
assert(grid!=NULL);
const int Nd = grid->_ndimension;
const int Nsimd = grid->Nsimd();
assert(orthogdim >= 0);
assert(orthogdim < Nd);
int fd=grid->_fdimensions[orthogdim];
int ld=grid->_ldimensions[orthogdim];
int rd=grid->_rdimensions[orthogdim];
Vector<vobj> lvSum(rd); // will locally sum vectors first
Vector<sobj> lsSum(ld,Zero()); // sum across these down to scalars
ExtractBuffer<sobj> extracted(Nsimd); // splitting the SIMD
result.resize(fd); // And then global sum to return the same vector to every node
for(int r=0;r<rd;r++){
lvSum[r]=Zero();
}
int e1= grid->_slice_nblock[orthogdim];
int e2= grid->_slice_block [orthogdim];
int stride=grid->_slice_stride[orthogdim];
int ostride=grid->_ostride[orthogdim];
//Reduce Data down to lvSum
sliceSumReduction_cpu(Data,lvSum,rd, e1,e2,stride,ostride,Nsimd);
// Sum across simd lanes in the plane, breaking out orthog dir.
Coordinate icoor(Nd);
for(int rt=0;rt<rd;rt++){
extract(lvSum[rt],extracted);
for(int idx=0;idx<Nsimd;idx++){
grid->iCoorFromIindex(icoor,idx);
int ldx =rt+icoor[orthogdim]*rd;
lsSum[ldx]=lsSum[ldx]+extracted[idx];
}
}
// sum over nodes.
for(int t=0;t<fd;t++){
int pt = t/ld; // processor plane
int lt = t%ld;
if ( pt == grid->_processor_coor[orthogdim] ) {
result[t]=lsSum[lt];
} else {
result[t]=Zero();
}
}
scalar_type * ptr = (scalar_type *) &result[0];
int words = fd*sizeof(sobj)/sizeof(scalar_type);
grid->GlobalSumVector(ptr, words);
}
int main (int argc, char ** argv) {
using namespace Grid;
Grid_init(&argc,&argv);
Coordinate latt_size({64,64,64,16});
auto simd_layout = GridDefaultSimd(Nd, vComplexD::Nsimd());
auto mpi_layout = GridDefaultMpi();
GridCartesian Grid(latt_size, simd_layout, mpi_layout);
std::vector<int> seeds({1, 2, 3, 4});
GridParallelRNG pRNG(&Grid);
pRNG.SeedFixedIntegers(seeds);
LatticeComplexD test_data(&Grid);
gaussian(pRNG,test_data);
std::vector<TComplexD> reduction_reference;
std::vector<TComplexD> reduction_result;
//warmup
for (int sweeps = 0; sweeps < 5; sweeps++) {
reduction_result = sliceSum(test_data,0);
}
int trace_id = traceStart("sliceSum benchmark - ComplexD");
std::cout << GridLogMessage << "Testing ComplexD" << std::endl;
std::cout << GridLogMessage << "sizeof(ComplexD) = " << sizeof(ComplexD) << std::endl;
std::cout << GridLogMessage << "sizeof(vComplexD) = " << sizeof(vComplexD) << std::endl;
for (int i = 0; i < Nd; i++) {
RealD t=-usecond();
tracePush("sliceSum");
sliceSumCPU(test_data,reduction_reference,i);
tracePop("sliceSum");
t+=usecond();
std::cout << GridLogMessage << "Orthog. dir. = " << i << std::endl;
std::cout << GridLogMessage << "CPU sliceSum took "<<t<<" usecs"<<std::endl;
RealD tgpu=-usecond();
tracePush("sliceSumGpu");
reduction_result = sliceSum(test_data,i);
tracePop("sliceSumGpu");
tgpu+=usecond();
std::cout << GridLogMessage <<"GPU sliceSum took "<<tgpu<<" usecs"<<std::endl<<std::endl;;
for(int t=0;t<reduction_reference.size();t++) {
auto diff = reduction_reference[t]-reduction_result[t];
assert(abs(TensorRemove(diff)) < 1e-8 );
}
}
traceStop(trace_id);
LatticeSpinVectorD test_data_cv(&Grid);
gaussian(pRNG,test_data_cv);
std::vector<SpinVectorD> reduction_reference_cv;
std::vector<SpinVectorD> reduction_result_cv;
//warmup
for (int sweeps = 0; sweeps < 5; sweeps++) {
reduction_result_cv = sliceSum(test_data_cv,0);
}
trace_id = traceStart("sliceSum benchmark - SpinVectorD");
std::cout << GridLogMessage << "Testing SpinVectorD" << std::endl;
std::cout << GridLogMessage << "sizeof(SpinVectorD) = " << sizeof(SpinVectorD) << std::endl;
std::cout << GridLogMessage << "sizeof(vSpinVectorD) = " << sizeof(vSpinVectorD) << std::endl;
for (int i = 0; i < Nd; i++) {
RealD t=-usecond();
tracePush("sliceSum");
sliceSumCPU(test_data_cv,reduction_reference_cv,i);
tracePop("sliceSum");
t+=usecond();
std::cout << GridLogMessage << "Orthog. dir. = " << i << std::endl;
std::cout << GridLogMessage << "CPU sliceSum took "<<t<<" usecs"<<std::endl;
RealD tgpu=-usecond();
tracePush("sliceSumGpu");
reduction_result_cv = sliceSum(test_data_cv,i);
tracePop("sliceSumGpu");
tgpu+=usecond();
std::cout << GridLogMessage <<"GPU sliceSum took "<<tgpu<<" usecs"<<std::endl<<std::endl;;
for(int t=0;t<reduction_reference_cv.size();t++) {
auto diff = reduction_reference_cv[t]-reduction_result_cv[t];
assert(abs(diff()(0)()) < 1e-8 );
assert(abs(diff()(1)()) < 1e-8 );
assert(abs(diff()(2)()) < 1e-8 );
assert(abs(diff()(3)()) < 1e-8 );
}
}
traceStop(trace_id);
LatticeSpinColourVectorD test_data_scv(&Grid);
gaussian(pRNG,test_data_scv);
std::vector<SpinColourVectorD> reduction_reference_scv;
std::vector<SpinColourVectorD> reduction_result_scv;
//warmup
for (int sweeps = 0; sweeps < 5; sweeps++) {
reduction_result_scv = sliceSum(test_data_scv,0);
}
trace_id = traceStart("sliceSum benchmark - SpinColourVectorD");
std::cout << GridLogMessage << "Testing SpinColourVectorD" << std::endl;
std::cout << GridLogMessage << "sizeof(SpinColourVectorD) = " << sizeof(SpinColourVectorD) << std::endl;
std::cout << GridLogMessage << "sizeof(vSpinColourVectorD) = " << sizeof(vSpinColourVectorD) << std::endl;
for (int i = 0; i < Nd; i++) {
RealD t=-usecond();
tracePush("sliceSum");
sliceSumCPU(test_data_scv,reduction_reference_scv,i);
tracePop("sliceSum");
t+=usecond();
std::cout << GridLogMessage << "Orthog. dir. = " << i << std::endl;
std::cout << GridLogMessage << "CPU sliceSum took "<<t<<" usecs"<<std::endl;
RealD tgpu=-usecond();
tracePush("sliceSumGpu");
reduction_result_scv = sliceSum(test_data_scv,i);
tracePop("sliceSumGpu");
tgpu+=usecond();
std::cout << GridLogMessage <<"GPU sliceSum took "<<tgpu<<" usecs"<<std::endl<<std::endl;;
for(int t=0;t<reduction_reference_scv.size();t++) {
auto diff = reduction_reference_scv[t]-reduction_result_scv[t];
// std::cout << diff <<std::endl;
assert(abs(diff()(0)(0)) < 1e-8 );
assert(abs(diff()(0)(1)) < 1e-8 );
assert(abs(diff()(0)(2)) < 1e-8 );
assert(abs(diff()(1)(0)) < 1e-8 );
assert(abs(diff()(1)(1)) < 1e-8 );
assert(abs(diff()(1)(2)) < 1e-8 );
assert(abs(diff()(2)(0)) < 1e-8 );
assert(abs(diff()(2)(1)) < 1e-8 );
assert(abs(diff()(2)(2)) < 1e-8 );
assert(abs(diff()(3)(0)) < 1e-8 );
assert(abs(diff()(3)(1)) < 1e-8 );
assert(abs(diff()(3)(2)) < 1e-8 );
}
}
traceStop(trace_id);
LatticeSpinColourMatrixD test_data_scm(&Grid);
gaussian(pRNG,test_data_scm);
std::vector<SpinColourMatrixD> reduction_reference_scm;
std::vector<SpinColourMatrixD> reduction_result_scm;
//warmup
for (int sweeps = 0; sweeps < 5; sweeps++) {
reduction_result_scm = sliceSum(test_data_scm,0);
}
trace_id = traceStart("sliceSum benchmark - SpinColourMatrixD");
std::cout << GridLogMessage << "Testing SpinColourMatrixD" << std::endl;
std::cout << GridLogMessage << "sizeof(SpinColourMatrixD) = " << sizeof(SpinColourMatrixD) << std::endl;
std::cout << GridLogMessage << "sizeof(vSpinColourMatrixD) = " << sizeof(vSpinColourMatrixD) << std::endl;
for (int i = 0; i < Nd; i++) {
RealD t=-usecond();
tracePush("sliceSum");
sliceSumCPU(test_data_scm,reduction_reference_scm,i);
tracePop("sliceSum");
t+=usecond();
std::cout << GridLogMessage << "Orthog. dir. = " << i << std::endl;
std::cout << GridLogMessage << "CPU sliceSum took "<<t<<" usecs"<<std::endl;
RealD tgpu=-usecond();
tracePush("sliceSumGpu");
reduction_result_scm = sliceSum(test_data_scm,i);
tracePop("sliceSumGpu");
tgpu+=usecond();
std::cout << GridLogMessage <<"GPU sliceSum took "<<tgpu<<" usecs"<<std::endl<<std::endl;;
for(int t=0;t<reduction_reference_scm.size();t++) {
auto diff = reduction_reference_scm[t]-reduction_result_scm[t];
// std::cout << diff <<std::endl;
for (int is = 0; is < Ns; is++) {
for (int js = 0; js < Ns; js++) {
for (int ic = 0; ic < Nc; ic++) {
for (int jc = 0; jc < Nc; jc++) {
assert(abs(diff()(is,js)(ic,jc)) < 1e-8);
}
}
}
}
}
}
traceStop(trace_id);
Grid_finalize();
return 0;
}

View File

@ -32,6 +32,7 @@ Author: Peter Boyle <paboyle@ph.ed.ac.uk>
using namespace std;
using namespace Grid;
// This is to optimize the SIMD
template<class vobj> void gpermute(vobj & inout,int perm){
vobj tmp=inout;
if (perm & 0x1 ) { permute(inout,tmp,0); tmp=inout;}
@ -39,7 +40,8 @@ template<class vobj> void gpermute(vobj & inout,int perm){
if (perm & 0x4 ) { permute(inout,tmp,2); tmp=inout;}
if (perm & 0x8 ) { permute(inout,tmp,3); tmp=inout;}
}
int main (int argc, char ** argv)
{
Grid_init(&argc,&argv);
@ -47,20 +49,21 @@ int main (int argc, char ** argv)
Coordinate latt_size = GridDefaultLatt();
Coordinate simd_layout= GridDefaultSimd(Nd,vComplexD::Nsimd());
Coordinate mpi_layout = GridDefaultMpi();
std::cout << " mpi "<<mpi_layout<<std::endl;
std::cout << " simd "<<simd_layout<<std::endl;
std::cout << " latt "<<latt_size<<std::endl;
std::cout << GridLogMessage << " mpi "<<mpi_layout<<std::endl;
std::cout << GridLogMessage << " simd "<<simd_layout<<std::endl;
std::cout << GridLogMessage << " latt "<<latt_size<<std::endl;
GridCartesian GRID(latt_size,simd_layout,mpi_layout);
// Initialize configuration as hot start.
GridParallelRNG pRNG(&GRID);
pRNG.SeedFixedIntegers(std::vector<int>({45,12,81,9}));
LatticeGaugeField Umu(&GRID);
pRNG.SeedFixedIntegers(std::vector<int>({45,12,81,9}));
SU<Nc>::HotConfiguration(pRNG,Umu);
Real plaq=WilsonLoops<PeriodicGimplR>::avgPlaquette(Umu);
LatticeComplex trplaq(&GRID);
// Store Umu in U. Peek/Poke mean respectively getElement/setElement.
std::vector<LatticeColourMatrix> U(Nd, Umu.Grid());
for (int mu = 0; mu < Nd; mu++) {
U[mu] = PeekIndex<LorentzIndex>(Umu, mu);
@ -70,9 +73,7 @@ int main (int argc, char ** argv)
LatticeComplex cplaq(&GRID); cplaq=Zero();
/////////////////////////////////////////////////
// Create a padded cell of extra padding depth=1
/////////////////////////////////////////////////
int depth = 1;
PaddedCell Ghost(depth,&GRID);
LatticeGaugeField Ughost = Ghost.Exchange(Umu);
@ -114,18 +115,25 @@ int main (int argc, char ** argv)
}
#endif
///// Array for the site plaquette
// Array for the site plaquette
GridBase *GhostGrid = Ughost.Grid();
LatticeComplex gplaq(GhostGrid);
// Now we're going to put together the "stencil" that will be useful to us when
// calculating the plaquette. Our eventual goal is to make the product
// Umu(x) Unu(x+mu) Umu^dag(x+nu) Unu^dag(x),
// which requires, in order, the sites x, x+mu, x+nu, and x. We arrive at these
// sites relative to x through "shifts", which is represented here by a 4-d
// vector of 0s (no movement) and 1s (shift one unit) at each site. The
// "stencil" is the set of all these shifts.
std::vector<Coordinate> shifts;
for(int mu=0;mu<Nd;mu++){
for(int nu=mu+1;nu<Nd;nu++){
// Umu(x) Unu(x+mu) Umu^dag(x+nu) Unu^dag(x)
Coordinate shift_0(Nd,0);
Coordinate shift_mu(Nd,0); shift_mu[mu]=1;
Coordinate shift_nu(Nd,0); shift_nu[nu]=1;
// push_back creates an element at the end of shifts and
// assigns the data in the argument to it.
shifts.push_back(shift_0);
shifts.push_back(shift_mu);
shifts.push_back(shift_nu);
@ -135,41 +143,51 @@ int main (int argc, char ** argv)
GeneralLocalStencil gStencil(GhostGrid,shifts);
gplaq=Zero();
{
autoView( gp_v , gplaq, CpuWrite);
autoView( t_v , trplaq, CpuRead);
autoView( U_v , Ughost, CpuRead);
for(int ss=0;ss<gp_v.size();ss++){
int s=0;
for(int mu=0;mu<Nd;mu++){
for(int nu=mu+1;nu<Nd;nu++){
auto SE0 = gStencil.GetEntry(s+0,ss);
auto SE1 = gStencil.GetEntry(s+1,ss);
auto SE2 = gStencil.GetEntry(s+2,ss);
auto SE3 = gStencil.GetEntry(s+3,ss);
int o0 = SE0->_offset;
int o1 = SE1->_offset;
int o2 = SE2->_offset;
int o3 = SE3->_offset;
auto U0 = U_v[o0](mu);
auto U1 = U_v[o1](nu);
auto U2 = adj(U_v[o2](mu));
auto U3 = adj(U_v[o3](nu));
// Before doing accelerator stuff, there is an opening and closing of "Views". I guess the
// "Views" are stored in *_v variables listed below.
autoView( gp_v , gplaq, CpuWrite);
autoView( t_v , trplaq, CpuRead);
autoView( U_v , Ughost, CpuRead);
gpermute(U0,SE0->_permute);
gpermute(U1,SE1->_permute);
gpermute(U2,SE2->_permute);
gpermute(U3,SE3->_permute);
gp_v[ss]() =gp_v[ss]() + trace( U0*U1*U2*U3 );
s=s+4;
}
}
// This is now a loop over stencil shift elements. That is, s increases as we make our
// way through the spacetimes sites, but also as we make our way around the plaquette.
for(int ss=0;ss<gp_v.size();ss++){
int s=0;
for(int mu=0;mu<Nd;mu++){
for(int nu=mu+1;nu<Nd;nu++){
auto SE0 = gStencil.GetEntry(s+0,ss);
auto SE1 = gStencil.GetEntry(s+1,ss);
auto SE2 = gStencil.GetEntry(s+2,ss);
auto SE3 = gStencil.GetEntry(s+3,ss);
// Due to our strategy, each offset corresponds to a site.
int o0 = SE0->_offset;
int o1 = SE1->_offset;
int o2 = SE2->_offset;
int o3 = SE3->_offset;
auto U0 = U_v[o0](mu);
auto U1 = U_v[o1](nu);
auto U2 = adj(U_v[o2](mu));
auto U3 = adj(U_v[o3](nu));
gpermute(U0,SE0->_permute);
gpermute(U1,SE1->_permute);
gpermute(U2,SE2->_permute);
gpermute(U3,SE3->_permute);
gp_v[ss]() =gp_v[ss]() + trace( U0*U1*U2*U3 );
s=s+4;
}
}
}
// Here is my understanding of this part: The padded cell has its own periodic BCs, so
// if I take a step to the right at the right-most side of the cell, I end up on the
// left-most side. This means that the plaquettes in the padding are wrong. Luckily
// all we care about are the plaquettes in the cell, which we obtain from Extract.
cplaq = Ghost.Extract(gplaq);
RealD vol = cplaq.Grid()->gSites();
RealD faces = (Nd * (Nd-1))/2;

View File

@ -0,0 +1,181 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./tests/smearing/Test_fatLinks.cc
Copyright (C) 2023
Author: D. A. Clarke <clarke.davida@gmail.com>
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
*************************************************************************************/
/*
@file Test_fatLinks.cc
@brief test of the HISQ smearing
*/
#include <Grid/Grid.h>
#include <Grid/lattice/PaddedCell.h>
#include <Grid/stencil/GeneralLocalStencil.h>
#include <Grid/qcd/smearing/HISQSmearing.h>
using namespace Grid;
/*! @brief parameter file to easily adjust Nloop */
struct ConfParameters: Serializable {
GRID_SERIALIZABLE_CLASS_MEMBERS(
ConfParameters,
int, benchmark,
int, Nloop);
template <class ReaderClass>
ConfParameters(Reader<ReaderClass>& Reader){
read(Reader, "parameters", *this);
}
};
bool testSmear(GridCartesian& GRID, LatticeGaugeFieldD Umu, LatticeGaugeFieldD Usmr, LatticeGaugeFieldD Unaik,
LatticeGaugeFieldD Ucontrol, Real c1, Real cnaik, Real c3, Real c5, Real c7, Real clp) {
Smear_HISQ<PeriodicGimplD> hisq_fat(&GRID,c1,cnaik,c3,c5,c7,clp);
LatticeGaugeFieldD diff(&GRID), Uproj(&GRID);
hisq_fat.smear(Usmr, Unaik, Umu);
bool result;
if (cnaik < 1e-30) { // Testing anything but Naik term
diff = Ucontrol-Usmr;
auto absDiff = norm2(diff)/norm2(Ucontrol);
if (absDiff < 1e-30) {
Grid_pass(" |Umu-Usmr|/|Umu| = ",absDiff);
result = true;
} else {
Grid_error(" |Umu-Usmr|/|Umu| = ",absDiff);
result = false;
}
} else { // Testing Naik specifically
diff = Ucontrol-Unaik;
auto absDiff = norm2(diff)/norm2(Ucontrol);
if (absDiff < 1e-30) {
Grid_pass(" |Umu-Unaik|/|Umu| = ",absDiff);
result = true;
} else {
Grid_error(" |Umu-Unaik|/|Umu| = ",absDiff);
result = false;
}
hisq_fat.projectU3(Uproj,Ucontrol);
// NerscIO::writeConfiguration(Unaik,"nersc.l8t4b3360.naik");
}
return result;
}
int main (int argc, char** argv) {
// Params for the test.
int Ns = 8;
int Nt = 4;
Coordinate latt_size(Nd,0); latt_size[0]=Ns; latt_size[1]=Ns; latt_size[2]=Ns; latt_size[3]=Nt;
std::string conf_in = "nersc.l8t4b3360";
int threads = GridThread::GetThreads();
typedef LatticeGaugeFieldD LGF;
// Initialize the Grid
Grid_init(&argc,&argv);
Coordinate simd_layout = GridDefaultSimd(Nd,vComplexD::Nsimd());
Coordinate mpi_layout = GridDefaultMpi();
Grid_log("mpi = ",mpi_layout);
Grid_log("simd = ",simd_layout);
Grid_log("latt = ",latt_size);
Grid_log("threads = ",threads);
GridCartesian GRID(latt_size,simd_layout,mpi_layout);
XmlReader Reader("fatParams.xml",false,"grid");
ConfParameters param(Reader);
if(param.benchmark) Grid_log(" Nloop = ",param.Nloop);
LGF Umu(&GRID), Usmr(&GRID), Unaik(&GRID), Ucontrol(&GRID);
// Read the configuration into Umu
FieldMetaData header;
NerscIO::readConfiguration(Umu, header, conf_in);
bool pass=true;
// Carry out various tests
NerscIO::readConfiguration(Ucontrol, header, "nersc.l8t4b3360.357lplink.control");
pass *= testSmear(GRID,Umu,Usmr,Unaik,Ucontrol,1/8.,0.,1/16.,1/64.,1/384.,-1/8.);
NerscIO::readConfiguration(Ucontrol, header, "nersc.l8t4b3360.357link.control");
pass *= testSmear(GRID,Umu,Usmr,Unaik,Ucontrol,1/8.,0.,1/16.,1/64.,1/384.,0.);
NerscIO::readConfiguration(Ucontrol, header, "nersc.l8t4b3360.35link.control");
pass *= testSmear(GRID,Umu,Usmr,Unaik,Ucontrol,1/8.,0.,1/16.,1/64.,0.,0.);
NerscIO::readConfiguration(Ucontrol, header, "nersc.l8t4b3360.3link.control");
pass *= testSmear(GRID,Umu,Usmr,Unaik,Ucontrol,1/8.,0.,1/16.,0.,0.,0.);
NerscIO::readConfiguration(Ucontrol, header, "nersc.l8t4b3360.naik.control");
pass *= testSmear(GRID,Umu,Usmr,Unaik,Ucontrol,0.,0.8675309,0.,0.,0.,0.);
if(pass){
Grid_pass("All tests passed.");
} else {
Grid_error("At least one test failed.");
}
// Test a C-style instantiation
double path_coeff[6] = {1, 2, 3, 4, 5, 6};
Smear_HISQ<PeriodicGimplD> hisq_fat_Cstyle(&GRID,path_coeff);
if (param.benchmark) {
autoView(U_v, Umu, CpuRead); // Gauge accessor
// Read in lattice sequentially, Nloop times
double lookupTime = 0.;
for(int i=0;i<param.Nloop;i++) {
double start = usecond();
for(int ss=0;ss<U_v.size();ss++)
for(int mu=0;mu<Nd;mu++) {
auto U1 = U_v[ss](mu);
}
double stop = usecond();
lookupTime += stop-start; // microseconds
}
Grid_log("Time to lookup: ",lookupTime,"[ms]");
// Raise a matrix to the power nmat, for each link.
auto U1 = U_v[0](0);
for(int nmat=1;nmat<8;nmat++) {
double multTime = 0.;
for(int i=0;i<param.Nloop;i++) {
double start=usecond();
for(int ss=0;ss<U_v.size();ss++)
for(int mu=0;mu<Nd;mu++) {
auto U2 = U1;
for(int j=1;j<nmat;j++) {
U2 *= U1;
}
}
double stop=usecond();
multTime += stop-start;
}
Grid_log("Time to multiply ",nmat," matrices: ",multTime," [ms]");
}
}
Grid_finalize();
}