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Author SHA1 Message Date
cb538bfbf1 Merge pull request 'Updates GPU launch wrapper and install script' (#8) from aturner/lattice-benchmarks:main into main
Reviewed-on: portelli/lattice-benchmarks#8
2025-03-31 16:08:45 +01:00
9056e9023c Updates knem location in install script 2024-12-17 13:46:43 +00:00
c049a2ad0b Merge pull request 'benchmark-quda' (#3) from simon.buerger/lattice-benchmarks:benchmark-quda into main
Reviewed-on: portelli/lattice-benchmarks#3
2024-11-26 10:57:28 +00:00
fb43d16830 log iso-timestamp instead of seconds-since-start 2024-11-25 15:45:59 +00:00
6fa2e6bcd0 fix bug that made benchmark_quda hang randomly 2024-11-25 15:45:59 +00:00
fb4c456776 choose iteration count automatically 2024-11-25 15:45:58 +00:00
3fbb8ea346 add timestamps to benchmarks 2024-11-25 15:45:58 +00:00
86b160cb5c add json output to Benchmark_Quda 2024-11-25 15:45:58 +00:00
dc411017bb Update 'Quda/Readme.md' 2024-11-25 15:45:58 +00:00
b2cc780690 add Readme.md to Quda benchmark 2024-11-25 15:45:58 +00:00
6d87396576 clean up build script a bit 2024-11-25 15:45:58 +00:00
e9d084ce09 better range of lattice sizes 2024-11-25 15:45:58 +00:00
32e301fc67 add DWF benchmark 2024-11-25 15:45:58 +00:00
eaa4feee43 benchmark Dslash(...) instead of full M(...) 2024-11-25 15:45:58 +00:00
025f9dab50 fix scaling conventions for multi-gpu 2024-11-25 15:45:57 +00:00
3a561091d9 tidy up the wilson benchmark and add environment script 2024-11-25 15:45:57 +00:00
191c0cfca5 add quda axpy/memory benchmark 2024-11-25 15:45:57 +00:00
6f9af8acad first draft of Quda Benchmark 2024-11-25 15:45:57 +00:00
371a329457 Merge pull request 'Point-to-Point latency' (#7) from simon.buerger/lattice-benchmarks:latency_benchmark into main
Reviewed-on: portelli/lattice-benchmarks#7
Reviewed-by: Antonin Portelli <antonin.portelli@me.com>
2024-11-19 10:37:26 +00:00
f81cb198ab add command line options to Benchmark_Grid 2024-11-18 23:50:45 +00:00
a7e1d9e67f lower loop counts a bit for p2p/latency 2024-10-11 18:27:00 +01:00
19c9dcb6ae fix order of ranks in latency/p2p 2024-10-10 11:40:44 +01:00
7d89380b80 point-to-point bandwith benchmark 2024-10-07 17:22:26 +01:00
4cd67805b9 make Latency benchmark proper one-way and increase statistics 2024-09-26 09:31:22 +01:00
f7e607eae4 proper warmup loop for latency 2024-05-09 23:33:04 +01:00
a267986800 naming consitency 2024-05-09 23:25:06 +01:00
a1ec08cdb3 point-to-point latency 2024-05-09 23:17:54 +01:00
fb6c79d9ca shm direction fix 2024-03-21 13:51:49 +09:00
d7647afa72 Merge remote-tracking branch 'upstream/main' into main 2024-01-23 10:10:52 +00:00
ba00493c7d Merge pull request 'fix incompatibility with latest Grid' (#5) from simon.buerger/lattice-benchmarks:main into main
Reviewed-on: portelli/lattice-benchmarks#5
2023-12-20 15:06:41 +00:00
6055e0503c simple latency benchmark 2023-12-20 13:43:51 +00:00
6ea093fc80 fix incompatibility with latest Grid 2023-12-18 16:48:19 +00:00
fa47ec5bbe Merge pull request 'refactor and repair the spack environment' (#4) from simon.buerger/lattice-benchmarks:fix_spack_environment into main
Reviewed-on: portelli/lattice-benchmarks#4
2023-07-05 15:11:40 +01:00
7235bfde4c refactor and repair the spack environment 2023-07-04 22:30:54 +01:00
e5c61c2db1 Merge pull request 'add indication of shared-memory directions in comms benchmark' (#2) from simon.buerger/lattice-benchmarks:feature/grid-shared-mem into main
Reviewed-on: portelli/lattice-benchmarks#2
2023-04-12 15:05:39 +01:00
80c80049d7 add indication of shared-memory directions in comms benchmark 2023-04-12 11:40:39 +01:00
ce0d4d9457 Grid comms warmup sequence 2023-02-03 20:59:20 +00:00
cc4c0255bc Grid Tursa 32 node MPI layout change 2023-02-03 20:59:02 +00:00
bdfb94bf11 Grid overflow fix 2023-02-03 20:58:41 +00:00
af950e6e28 Grid Tursa 32 node batch script 2023-02-01 23:55:50 +00:00
14fb2fddc2 Grid benchmark build script fix 2023-02-01 23:55:37 +00:00
5198bbe1cd Grid benchmark documentation update 2023-01-30 18:28:38 +00:00
5f9abbb8d0 minor label fix 2023-01-30 18:28:17 +00:00
9b6c6d4d40 Grid: geometry JSON output and cleanup 2023-01-30 17:43:35 +00:00
43e264d29b Proper runscript example for Tursa 2023-01-30 16:58:54 +00:00
51eae5723e Grid IO benchmark cleanup 2023-01-29 14:56:37 +00:00
ce890a8fc2 Merge branch 'main' of git.dev.dirac.ed.ac.uk:portelli/lattice-benchmarks 2023-01-28 15:28:34 +00:00
8f1a556afa Finale cleanup! 2023-01-28 15:28:23 +00:00
58080730ae FInale cleanup! 2023-01-28 15:26:03 +00:00
f180cbb8ec JSON fix 2023-01-28 14:44:32 +00:00
5098f57f08 Grid Tursa wrapper permission fix 2023-01-28 14:19:47 +00:00
0e2b7225db Gird Makefile.am fix 2023-01-28 14:19:25 +00:00
7b689a8c94 removing old benchmarks 2023-01-28 14:18:56 +00:00
77c75ea5b8 Memory benchmarks cleanup and fix 2023-01-28 14:18:48 +00:00
78c464d1d8 Grid benchmark big formatting cleanup 2023-01-27 18:49:53 +00:00
8f043343fb Trusa Grid env fix 2023-01-27 17:56:10 +00:00
23 changed files with 1542 additions and 1334 deletions

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@ -32,7 +32,7 @@ along with this program. If not, see <http://www.gnu.org/licenses/>.
#ifdef HAVE_LIME
using namespace Grid;
std::string filestem(const int l) { return "iobench_l" + std::to_string(l); }
std::string filestem(const int l) { return "io/iobench_l" + std::to_string(l); }
int vol(const int i) { return BENCH_IO_LMIN + 2 * i; }
@ -56,13 +56,6 @@ template <typename Mat> void stats(Mat &mean, Mat &stdDev, const std::vector<Mat
mean /= n;
}
#define grid_printf(...) \
{ \
char _buf[1024]; \
sprintf(_buf, __VA_ARGS__); \
MSG << _buf; \
}
enum
{
sRead = 0,
@ -83,58 +76,58 @@ int main(int argc, char **argv)
std::vector<Eigen::VectorXd> avPerf(BENCH_IO_NPASS, Eigen::VectorXd::Zero(4));
std::vector<int> latt;
MSG << "Grid is setup to use " << threads << " threads" << std::endl;
MSG << "MPI partition " << mpi << std::endl;
GRID_MSG << "Grid is setup to use " << threads << " threads" << std::endl;
GRID_MSG << "MPI partition " << mpi << std::endl;
for (unsigned int i = 0; i < BENCH_IO_NPASS; ++i)
{
MSG << BIGSEP << std::endl;
MSG << "Pass " << i + 1 << "/" << BENCH_IO_NPASS << std::endl;
MSG << BIGSEP << std::endl;
MSG << SEP << std::endl;
MSG << "Benchmark std write" << std::endl;
MSG << SEP << std::endl;
grid_big_sep();
GRID_MSG << "Pass " << i + 1 << "/" << BENCH_IO_NPASS << std::endl;
grid_big_sep();
grid_small_sep();
GRID_MSG << "Benchmark std write" << std::endl;
grid_small_sep();
for (int l = BENCH_IO_LMIN; l <= BENCH_IO_LMAX; l += 2)
{
latt = {l * mpi[0], l * mpi[1], l * mpi[2], l * mpi[3]};
MSG << "-- Local volume " << l << "^4" << std::endl;
GRID_MSG << "-- Local volume " << l << "^4" << std::endl;
writeBenchmark<LatticeFermion>(latt, filestem(l), stdWrite<LatticeFermion>);
perf[i](volInd(l), sWrite) = BinaryIO::lastPerf.mbytesPerSecond;
}
MSG << SEP << std::endl;
MSG << "Benchmark std read" << std::endl;
MSG << SEP << std::endl;
grid_small_sep();
GRID_MSG << "Benchmark std read" << std::endl;
grid_small_sep();
for (int l = BENCH_IO_LMIN; l <= BENCH_IO_LMAX; l += 2)
{
latt = {l * mpi[0], l * mpi[1], l * mpi[2], l * mpi[3]};
MSG << "-- Local volume " << l << "^4" << std::endl;
GRID_MSG << "-- Local volume " << l << "^4" << std::endl;
readBenchmark<LatticeFermion>(latt, filestem(l), stdRead<LatticeFermion>);
perf[i](volInd(l), sRead) = BinaryIO::lastPerf.mbytesPerSecond;
}
#ifdef HAVE_LIME
MSG << SEP << std::endl;
MSG << "Benchmark Grid C-Lime write" << std::endl;
MSG << SEP << std::endl;
grid_small_sep();
GRID_MSG << "Benchmark Grid C-Lime write" << std::endl;
grid_small_sep();
for (int l = BENCH_IO_LMIN; l <= BENCH_IO_LMAX; l += 2)
{
latt = {l * mpi[0], l * mpi[1], l * mpi[2], l * mpi[3]};
MSG << "-- Local volume " << l << "^4" << std::endl;
GRID_MSG << "-- Local volume " << l << "^4" << std::endl;
writeBenchmark<LatticeFermion>(latt, filestem(l), limeWrite<LatticeFermion>);
perf[i](volInd(l), gWrite) = BinaryIO::lastPerf.mbytesPerSecond;
}
MSG << SEP << std::endl;
MSG << "Benchmark Grid C-Lime read" << std::endl;
MSG << SEP << std::endl;
grid_small_sep();
GRID_MSG << "Benchmark Grid C-Lime read" << std::endl;
grid_small_sep();
for (int l = BENCH_IO_LMIN; l <= BENCH_IO_LMAX; l += 2)
{
latt = {l * mpi[0], l * mpi[1], l * mpi[2], l * mpi[3]};
MSG << "-- Local volume " << l << "^4" << std::endl;
GRID_MSG << "-- Local volume " << l << "^4" << std::endl;
readBenchmark<LatticeFermion>(latt, filestem(l), limeRead<LatticeFermion>);
perf[i](volInd(l), gRead) = BinaryIO::lastPerf.mbytesPerSecond;
}
@ -159,13 +152,13 @@ int main(int argc, char **argv)
avRob.fill(100.);
avRob -= 100. * avStdDev.cwiseQuotient(avMean.cwiseAbs());
MSG << BIGSEP << std::endl;
MSG << "SUMMARY" << std::endl;
MSG << BIGSEP << std::endl;
MSG << "Summary of individual results (all results in MB/s)." << std::endl;
MSG << "Every second colum gives the standard deviation of the previous column."
<< std::endl;
MSG << std::endl;
grid_big_sep();
GRID_MSG << "SUMMARY" << std::endl;
grid_big_sep();
GRID_MSG << "Summary of individual results (all results in MB/s)." << std::endl;
GRID_MSG << "Every second colum gives the standard deviation of the previous column."
<< std::endl;
GRID_MSG << std::endl;
grid_printf("%4s %12s %12s %12s %12s %12s %12s %12s %12s\n", "L", "std read", "std dev",
"std write", "std dev", "Grid read", "std dev", "Grid write", "std dev");
for (int l = BENCH_IO_LMIN; l <= BENCH_IO_LMAX; l += 2)
@ -176,10 +169,10 @@ int main(int argc, char **argv)
stdDev(volInd(l), gRead), mean(volInd(l), gWrite),
stdDev(volInd(l), gWrite));
}
MSG << std::endl;
MSG << "Robustness of individual results, in %. (rob = 100% - std dev / mean)"
<< std::endl;
MSG << std::endl;
GRID_MSG << std::endl;
GRID_MSG << "Robustness of individual results, in %. (rob = 100% - std dev / mean)"
<< std::endl;
GRID_MSG << std::endl;
grid_printf("%4s %12s %12s %12s %12s\n", "L", "std read", "std write", "Grid read",
"Grid write");
for (int l = BENCH_IO_LMIN; l <= BENCH_IO_LMAX; l += 2)
@ -187,21 +180,21 @@ int main(int argc, char **argv)
grid_printf("%4d %12.1f %12.1f %12.1f %12.1f\n", l, rob(volInd(l), sRead),
rob(volInd(l), sWrite), rob(volInd(l), gRead), rob(volInd(l), gWrite));
}
MSG << std::endl;
MSG << "Summary of results averaged over local volumes 24^4-" << BENCH_IO_LMAX
<< "^4 (all results in MB/s)." << std::endl;
MSG << "Every second colum gives the standard deviation of the previous column."
<< std::endl;
MSG << std::endl;
GRID_MSG << std::endl;
GRID_MSG << "Summary of results averaged over local volumes 24^4-" << BENCH_IO_LMAX
<< "^4 (all results in MB/s)." << std::endl;
GRID_MSG << "Every second colum gives the standard deviation of the previous column."
<< std::endl;
GRID_MSG << std::endl;
grid_printf("%12s %12s %12s %12s %12s %12s %12s %12s\n", "std read", "std dev",
"std write", "std dev", "Grid read", "std dev", "Grid write", "std dev");
grid_printf("%12.1f %12.1f %12.1f %12.1f %12.1f %12.1f %12.1f %12.1f\n", avMean(sRead),
avStdDev(sRead), avMean(sWrite), avStdDev(sWrite), avMean(gRead),
avStdDev(gRead), avMean(gWrite), avStdDev(gWrite));
MSG << std::endl;
MSG << "Robustness of volume-averaged results, in %. (rob = 100% - std dev / mean)"
<< std::endl;
MSG << std::endl;
GRID_MSG << std::endl;
GRID_MSG << "Robustness of volume-averaged results, in %. (rob = 100% - std dev / mean)"
<< std::endl;
GRID_MSG << std::endl;
grid_printf("%12s %12s %12s %12s\n", "std read", "std write", "Grid read",
"Grid write");
grid_printf("%12.1f %12.1f %12.1f %12.1f\n", avRob(sRead), avRob(sWrite), avRob(gRead),

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@ -18,12 +18,8 @@ along with this program. If not, see <http://www.gnu.org/licenses/>.
#ifndef Benchmark_IO_hpp_
#define Benchmark_IO_hpp_
#include "Common.hpp"
#include <Grid/Grid.h>
#define MSG std::cout << GridLogMessage
#define SEP \
"-----------------------------------------------------------------------------"
#define BIGSEP \
"============================================================================="
#ifdef HAVE_LIME
namespace Grid
@ -50,9 +46,9 @@ namespace Grid
// crc = GridChecksum::crc32(vec_v.cpu_ptr, size);
// std::fwrite(&crc, sizeof(uint32_t), 1, file);
// crcWatch.Stop();
// MSG << "Std I/O write: Data CRC32 " << std::hex << crc << std::dec << std::endl;
// ioWatch.Start();
// std::fwrite(vec_v.cpu_ptr, sizeof(typename Field::scalar_object),
// GRID_MSG << "Std I/O write: Data CRC32 " << std::hex << crc << std::dec <<
// std::endl; ioWatch.Start(); std::fwrite(vec_v.cpu_ptr, sizeof(typename
// Field::scalar_object),
// vec.Grid()->lSites(), file);
// ioWatch.Stop();
// std::fclose(file);
@ -61,11 +57,11 @@ namespace Grid
// p.size = size;
// p.time = ioWatch.useconds();
// p.mbytesPerSecond = size / 1024. / 1024. / (ioWatch.useconds() / 1.e6);
// MSG << "Std I/O write: Wrote " << p.size << " bytes in " << ioWatch.Elapsed()
// GRID_MSG << "Std I/O write: Wrote " << p.size << " bytes in " << ioWatch.Elapsed()
// << ",
// "
// << p.mbytesPerSecond << " MB/s" << std::endl;
// MSG << "Std I/O write: checksum overhead " << crcWatch.Elapsed() << std::endl;
// GRID_MSG << "Std I/O write: checksum overhead " << crcWatch.Elapsed() << std::endl;
// }
// template <typename Field> void stdRead(Field &vec, const std::string filestem)
@ -94,16 +90,14 @@ namespace Grid
// crcData = GridChecksum::crc32(vec_v.cpu_ptr, size);
// crcWatch.Stop();
// }
// MSG << "Std I/O read: Data CRC32 " << std::hex << crcData << std::dec << std::endl;
// assert(crcData == crcRead);
// size *= vec.Grid()->ProcessorCount();
// auto &p = BinaryIO::lastPerf;
// p.size = size;
// p.time = ioWatch.useconds();
// GRID_MSG << "Std I/O read: Data CRC32 " << std::hex << crcData << std::dec <<
// std::endl; assert(crcData == crcRead); size *= vec.Grid()->ProcessorCount(); auto
// &p = BinaryIO::lastPerf; p.size = size; p.time = ioWatch.useconds();
// p.mbytesPerSecond = size / 1024. / 1024. / (ioWatch.useconds() / 1.e6);
// MSG << "Std I/O read: Read " << p.size << " bytes in " << ioWatch.Elapsed() << ", "
// GRID_MSG << "Std I/O read: Read " << p.size << " bytes in " << ioWatch.Elapsed() <<
// ", "
// << p.mbytesPerSecond << " MB/s" << std::endl;
// MSG << "Std I/O read: checksum overhead " << crcWatch.Elapsed() << std::endl;
// GRID_MSG << "Std I/O read: checksum overhead " << crcWatch.Elapsed() << std::endl;
// }
template <typename Field> void stdWrite(const std::string filestem, Field &vec)
@ -122,7 +116,7 @@ namespace Grid
crc = GridChecksum::crc32(vec_v.cpu_ptr, size);
file.write(reinterpret_cast<char *>(&crc), sizeof(uint32_t) / sizeof(char));
crcWatch.Stop();
MSG << "Std I/O write: Data CRC32 " << std::hex << crc << std::dec << std::endl;
GRID_MSG << "Std I/O write: Data CRC32 " << std::hex << crc << std::dec << std::endl;
ioWatch.Start();
file.write(reinterpret_cast<char *>(vec_v.cpu_ptr), sizec);
file.flush();
@ -132,9 +126,9 @@ namespace Grid
p.size = size;
p.time = ioWatch.useconds();
p.mbytesPerSecond = size / 1024. / 1024. / (ioWatch.useconds() / 1.e6);
MSG << "Std I/O write: Wrote " << p.size << " bytes in " << ioWatch.Elapsed() << ", "
<< p.mbytesPerSecond << " MB/s" << std::endl;
MSG << "Std I/O write: checksum overhead " << crcWatch.Elapsed() << std::endl;
GRID_MSG << "Std I/O write: Wrote " << p.size << " bytes in " << ioWatch.Elapsed()
<< ", " << p.mbytesPerSecond << " MB/s" << std::endl;
GRID_MSG << "Std I/O write: checksum overhead " << crcWatch.Elapsed() << std::endl;
}
template <typename Field> void stdRead(Field &vec, const std::string filestem)
@ -163,16 +157,17 @@ namespace Grid
crcData = GridChecksum::crc32(vec_v.cpu_ptr, size);
crcWatch.Stop();
}
MSG << "Std I/O read: Data CRC32 " << std::hex << crcData << std::dec << std::endl;
GRID_MSG << "Std I/O read: Data CRC32 " << std::hex << crcData << std::dec
<< std::endl;
assert(crcData == crcRead);
size *= vec.Grid()->ProcessorCount();
auto &p = BinaryIO::lastPerf;
p.size = size;
p.time = ioWatch.useconds();
p.mbytesPerSecond = size / 1024. / 1024. / (ioWatch.useconds() / 1.e6);
MSG << "Std I/O read: Read " << p.size << " bytes in " << ioWatch.Elapsed() << ", "
<< p.mbytesPerSecond << " MB/s" << std::endl;
MSG << "Std I/O read: checksum overhead " << crcWatch.Elapsed() << std::endl;
GRID_MSG << "Std I/O read: Read " << p.size << " bytes in " << ioWatch.Elapsed()
<< ", " << p.mbytesPerSecond << " MB/s" << std::endl;
GRID_MSG << "Std I/O read: checksum overhead " << crcWatch.Elapsed() << std::endl;
}
template <typename Field> void limeWrite(const std::string filestem, Field &vec)

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@ -1,265 +0,0 @@
/*
Copyright © 2015 Peter Boyle <paboyle@ph.ed.ac.uk>
Copyright © 2022 Antonin Portelli <antonin.portelli@me.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, see <http://www.gnu.org/licenses/>.
*/
#include <Grid/Grid.h>
using namespace std;
using namespace Grid;
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 header()
{
std::cout << GridLogMessage << " L "
<< "\t"
<< " Ls "
<< "\t" << std::setw(11) << "bytes\t\t"
<< "MB/s uni"
<< "\t"
<< "MB/s bidi" << std::endl;
};
int main(int argc, char **argv)
{
Grid_init(&argc, &argv);
Coordinate simd_layout = GridDefaultSimd(Nd, vComplexD::Nsimd());
Coordinate mpi_layout = GridDefaultMpi();
int threads = GridThread::GetThreads();
std::cout << GridLogMessage << "Grid is setup to use " << threads << " threads"
<< std::endl;
int Nloop = 250;
int nmu = 0;
int maxlat = 32;
for (int mu = 0; mu < Nd; mu++)
if (mpi_layout[mu] > 1)
nmu++;
std::cout << GridLogMessage << "Number of iterations to average: " << Nloop
<< std::endl;
std::vector<double> t_time(Nloop);
// time_statistics timestat;
std::cout << GridLogMessage
<< "========================================================================="
"==========================="
<< std::endl;
std::cout << GridLogMessage
<< "= Benchmarking sequential halo exchange from host memory " << std::endl;
std::cout << GridLogMessage
<< "========================================================================="
"==========================="
<< std::endl;
header();
for (int lat = 8; lat <= maxlat; lat += 4)
{
for (int Ls = 8; Ls <= 8; Ls *= 2)
{
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<std::vector<HalfSpinColourVectorD>> xbuf(8);
std::vector<std::vector<HalfSpinColourVectorD>> rbuf(8);
for (int mu = 0; mu < 8; mu++)
{
xbuf[mu].resize(lat * lat * lat * Ls);
rbuf[mu].resize(lat * lat * lat * Ls);
}
uint64_t bytes = lat * lat * lat * Ls * sizeof(HalfSpinColourVectorD);
int ncomm;
for (int mu = 0; mu < 4; mu++)
{
if (mpi_layout[mu] > 1)
{
double start = usecond();
for (int i = 0; i < Nloop; i++)
{
ncomm = 0;
ncomm++;
int comm_proc = 1;
int xmit_to_rank;
int recv_from_rank;
{
std::vector<CommsRequest_t> requests;
Grid.ShiftedRanks(mu, comm_proc, xmit_to_rank, recv_from_rank);
Grid.SendToRecvFrom((void *)&xbuf[mu][0], xmit_to_rank,
(void *)&rbuf[mu][0], recv_from_rank, bytes);
}
comm_proc = mpi_layout[mu] - 1;
{
std::vector<CommsRequest_t> requests;
Grid.ShiftedRanks(mu, comm_proc, xmit_to_rank, recv_from_rank);
Grid.SendToRecvFrom((void *)&xbuf[mu + 4][0], xmit_to_rank,
(void *)&rbuf[mu + 4][0], recv_from_rank, bytes);
}
}
Grid.Barrier();
double stop = usecond();
double mean = (stop - start) / Nloop;
double dbytes = bytes * ppn;
double xbytes = dbytes * 2.0 * ncomm;
double rbytes = xbytes;
double bidibytes = xbytes + rbytes;
std::cout << GridLogMessage << std::setw(4) << lat << "\t" << Ls << "\t"
<< std::setw(11) << bytes << std::fixed << std::setprecision(1)
<< std::setw(7) << " " << std::right << xbytes / mean << " "
<< "\t\t" << std::setw(7) << bidibytes / mean << std::endl;
}
}
}
}
std::cout << GridLogMessage
<< "========================================================================="
"==========================="
<< std::endl;
std::cout << GridLogMessage
<< "= Benchmarking sequential halo exchange from GPU memory " << std::endl;
std::cout << GridLogMessage
<< "========================================================================="
"==========================="
<< std::endl;
header();
for (int lat = 8; lat <= maxlat; lat += 4)
{
for (int Ls = 8; Ls <= 8; Ls *= 2)
{
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);
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);
}
int ncomm;
for (int mu = 0; mu < 4; mu++)
{
if (mpi_layout[mu] > 1)
{
double start = usecond();
for (int i = 0; i < Nloop; i++)
{
ncomm = 0;
ncomm++;
int comm_proc = 1;
int xmit_to_rank;
int recv_from_rank;
{
std::vector<CommsRequest_t> requests;
Grid.ShiftedRanks(mu, comm_proc, xmit_to_rank, recv_from_rank);
Grid.SendToRecvFrom((void *)&xbuf[mu][0], xmit_to_rank,
(void *)&rbuf[mu][0], recv_from_rank, bytes);
}
comm_proc = mpi_layout[mu] - 1;
{
std::vector<CommsRequest_t> requests;
Grid.ShiftedRanks(mu, comm_proc, xmit_to_rank, recv_from_rank);
Grid.SendToRecvFrom((void *)&xbuf[mu + 4][0], xmit_to_rank,
(void *)&rbuf[mu + 4][0], recv_from_rank, bytes);
}
}
Grid.Barrier();
double stop = usecond();
double mean = (stop - start) / Nloop;
double dbytes = bytes * ppn;
double xbytes = dbytes * 2.0 * ncomm;
double rbytes = xbytes;
double bidibytes = xbytes + rbytes;
std::cout << GridLogMessage << std::setw(4) << lat << "\t" << Ls << "\t"
<< std::setw(11) << bytes << std::fixed << std::setprecision(1)
<< std::setw(7) << " " << std::right << xbytes / mean << " "
<< "\t\t" << std::setw(7) << bidibytes / mean << std::endl;
}
}
for (int d = 0; d < 8; d++)
{
acceleratorFreeDevice(xbuf[d]);
acceleratorFreeDevice(rbuf[d]);
}
}
}
std::cout << GridLogMessage
<< "========================================================================="
"==========================="
<< std::endl;
std::cout << GridLogMessage << "= All done; Bye Bye" << std::endl;
std::cout << GridLogMessage
<< "========================================================================="
"==========================="
<< std::endl;
Grid_finalize();
}

View File

@ -1,512 +0,0 @@
/*
Copyright © 2015 Peter Boyle <paboyle@ph.ed.ac.uk>
Copyright © 2022 Antonin Portelli <antonin.portelli@me.com>
Copyright © 2023 Simon Bürger <simon.buerger@rwth-aachen.de>
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License
as published by the Free Software Foundation; either version 2
of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "json.hpp"
#include <Grid/Grid.h>
#ifdef GRID_CUDA
#define CUDA_PROFILE
#endif
#ifdef CUDA_PROFILE
#include <cuda_profiler_api.h>
#endif
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};
int main(int argc, char **argv)
{
Grid_init(&argc, &argv);
int threads = GridThread::GetThreads();
Coordinate latt4 = GridDefaultLatt();
int Ls = 16;
std::string json_filename = ""; // empty indicates no json output
nlohmann::json json;
// benchmark specific command line arguments
for (int i = 0; i < argc; i++)
{
if (std::string(argv[i]) == "-Ls")
{
std::stringstream ss(argv[i + 1]);
ss >> Ls;
}
if (std::string(argv[i]) == "--json-out")
json_filename = argv[i + 1];
}
GridLogLayout();
long unsigned int single_site_flops = 8 * Nc * (7 + 16 * Nc);
json["single_site_flops"] = single_site_flops;
GridCartesian *UGrid = SpaceTimeGrid::makeFourDimGrid(
GridDefaultLatt(), GridDefaultSimd(Nd, vComplexF::Nsimd()), GridDefaultMpi());
GridRedBlackCartesian *UrbGrid = SpaceTimeGrid::makeFourDimRedBlackGrid(UGrid);
GridCartesian *FGrid = SpaceTimeGrid::makeFiveDimGrid(Ls, UGrid);
GridRedBlackCartesian *FrbGrid = SpaceTimeGrid::makeFiveDimRedBlackGrid(Ls, UGrid);
json["grid"] = FGrid->FullDimensions().toVector();
json["local_grid"] = FGrid->LocalDimensions().toVector();
std::cout << GridLogMessage << "Making s innermost grids" << std::endl;
GridCartesian *sUGrid =
SpaceTimeGrid::makeFourDimDWFGrid(GridDefaultLatt(), GridDefaultMpi());
GridRedBlackCartesian *sUrbGrid = SpaceTimeGrid::makeFourDimRedBlackGrid(sUGrid);
GridCartesian *sFGrid = SpaceTimeGrid::makeFiveDimDWFGrid(Ls, UGrid);
GridRedBlackCartesian *sFrbGrid = SpaceTimeGrid::makeFiveDimDWFRedBlackGrid(Ls, UGrid);
std::vector<int> seeds4({1, 2, 3, 4});
std::vector<int> seeds5({5, 6, 7, 8});
std::cout << GridLogMessage << "Initialising 4d RNG" << std::endl;
GridParallelRNG RNG4(UGrid);
RNG4.SeedUniqueString(std::string("The 4D RNG"));
std::cout << GridLogMessage << "Initialising 5d RNG" << std::endl;
GridParallelRNG RNG5(FGrid);
RNG5.SeedUniqueString(std::string("The 5D RNG"));
std::cout << GridLogMessage << "Initialised RNGs" << std::endl;
LatticeFermionF src(FGrid);
random(RNG5, src);
#if 0
src = Zero();
{
Coordinate origin({0,0,0,latt4[2]-1,0});
SpinColourVectorF tmp;
tmp=Zero();
tmp()(0)(0)=Complex(-2.0,0.0);
std::cout << " source site 0 " << tmp<<std::endl;
pokeSite(tmp,src,origin);
}
#else
RealD N2 = 1.0 / ::sqrt(norm2(src));
src = src * N2;
#endif
LatticeFermionF result(FGrid);
result = Zero();
LatticeFermionF ref(FGrid);
ref = Zero();
LatticeFermionF tmp(FGrid);
LatticeFermionF err(FGrid);
std::cout << GridLogMessage << "Drawing gauge field" << std::endl;
LatticeGaugeFieldF Umu(UGrid);
SU<Nc>::HotConfiguration(RNG4, Umu);
std::cout << GridLogMessage << "Random gauge initialised " << std::endl;
#if 0
Umu=1.0;
for(int mu=0;mu<Nd;mu++){
LatticeColourMatrixF ttmp(UGrid);
ttmp = PeekIndex<LorentzIndex>(Umu,mu);
// if (mu !=2 ) ttmp = 0;
// ttmp = ttmp* pow(10.0,mu);
PokeIndex<LorentzIndex>(Umu,ttmp,mu);
}
std::cout << GridLogMessage << "Forced to diagonal " << std::endl;
#endif
////////////////////////////////////
// Naive wilson implementation
////////////////////////////////////
// replicate across fifth dimension
// LatticeGaugeFieldF Umu5d(FGrid);
std::vector<LatticeColourMatrixF> U(4, UGrid);
for (int mu = 0; mu < Nd; mu++)
{
U[mu] = PeekIndex<LorentzIndex>(Umu, mu);
}
std::cout << GridLogMessage << "Setting up Cshift based reference " << std::endl;
if (1)
{
ref = Zero();
for (int mu = 0; mu < Nd; mu++)
{
tmp = Cshift(src, mu + 1, 1);
{
autoView(tmp_v, tmp, CpuWrite);
autoView(U_v, U[mu], CpuRead);
for (int ss = 0; ss < U[mu].Grid()->oSites(); ss++)
{
for (int s = 0; s < Ls; s++)
{
tmp_v[Ls * ss + s] = U_v[ss] * tmp_v[Ls * ss + s];
}
}
}
ref = ref + tmp - Gamma(Gmu[mu]) * tmp;
{
autoView(tmp_v, tmp, CpuWrite);
autoView(U_v, U[mu], CpuRead);
autoView(src_v, src, CpuRead);
for (int ss = 0; ss < U[mu].Grid()->oSites(); ss++)
{
for (int s = 0; s < Ls; s++)
{
tmp_v[Ls * ss + s] = adj(U_v[ss]) * src_v[Ls * ss + s];
}
}
}
tmp = Cshift(tmp, mu + 1, -1);
ref = ref + tmp + Gamma(Gmu[mu]) * tmp;
}
ref = -0.5 * ref;
}
RealD mass = 0.1;
RealD M5 = 1.8;
RealD NP = UGrid->_Nprocessors;
RealD NN = UGrid->NodeCount();
json["ranks"] = NP;
json["nodes"] = NN;
std::cout << GridLogMessage
<< "*****************************************************************"
<< std::endl;
std::cout << GridLogMessage
<< "* Kernel options --dslash-generic, --dslash-unroll, --dslash-asm"
<< std::endl;
std::cout << GridLogMessage
<< "*****************************************************************"
<< std::endl;
std::cout << GridLogMessage
<< "*****************************************************************"
<< std::endl;
std::cout << GridLogMessage
<< "* Benchmarking DomainWallFermionR::Dhop " << std::endl;
std::cout << GridLogMessage << "* Vectorising space-time by " << vComplexF::Nsimd()
<< std::endl;
std::cout << GridLogMessage << "* VComplexF size is " << sizeof(vComplexF) << " B"
<< std::endl;
if (sizeof(RealF) == 4)
std::cout << GridLogMessage << "* SINGLE precision " << std::endl;
if (sizeof(RealF) == 8)
std::cout << GridLogMessage << "* DOUBLE precision " << std::endl;
#ifdef GRID_OMP
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;
#endif
if (WilsonKernelsStatic::Opt == WilsonKernelsStatic::OptGeneric)
std::cout << GridLogMessage << "* Using GENERIC Nc WilsonKernels" << std::endl;
if (WilsonKernelsStatic::Opt == WilsonKernelsStatic::OptHandUnroll)
std::cout << GridLogMessage << "* Using Nc=3 WilsonKernels" << std::endl;
if (WilsonKernelsStatic::Opt == WilsonKernelsStatic::OptInlineAsm)
std::cout << GridLogMessage << "* Using Asm Nc=3 WilsonKernels" << std::endl;
std::cout << GridLogMessage
<< "*****************************************************************"
<< std::endl;
DomainWallFermionF Dw(Umu, *FGrid, *FrbGrid, *UGrid, *UrbGrid, mass, M5);
int ncall = 300;
if (1)
{
FGrid->Barrier();
Dw.ZeroCounters();
Dw.Dhop(src, result, 0);
std::cout << GridLogMessage << "Called warmup" << std::endl;
double t0 = usecond();
for (int i = 0; i < ncall; i++)
{
__SSC_START;
Dw.Dhop(src, result, 0);
__SSC_STOP;
}
double t1 = usecond();
FGrid->Barrier();
double volume = Ls;
for (int mu = 0; mu < Nd; mu++)
volume = volume * latt4[mu];
double flops = single_site_flops * volume * ncall;
auto nsimd = vComplex::Nsimd();
auto simdwidth = sizeof(vComplex);
// RF: Nd Wilson * Ls, Nd gauge * Ls, Nc colors
double data_rf = volume * ((2 * Nd + 1) * Nd * Nc + 2 * Nd * Nc * Nc) * simdwidth /
nsimd * ncall / (1024. * 1024. * 1024.);
// mem: Nd Wilson * Ls, Nd gauge, Nc colors
double data_mem =
(volume * (2 * Nd + 1) * Nd * Nc + (volume / Ls) * 2 * Nd * Nc * Nc) * simdwidth /
nsimd * ncall / (1024. * 1024. * 1024.);
json["Dw"]["calls"] = ncall;
json["Dw"]["time"] = t1 - t0;
json["Dw"]["mflops"] = flops / (t1 - t0);
json["Dw"]["mflops_per_rank"] = flops / (t1 - t0) / NP;
json["Dw"]["mflops_per_node"] = flops / (t1 - t0) / NN;
json["Dw"]["RF"] = 1000000. * data_rf / ((t1 - t0));
json["Dw"]["mem"] = 1000000. * data_mem / ((t1 - t0));
std::cout << GridLogMessage << "Called Dw " << ncall << " times in " << t1 - t0
<< " us" << std::endl;
// std::cout<<GridLogMessage << "norm result "<< norm2(result)<<std::endl;
// std::cout<<GridLogMessage << "norm ref "<< norm2(ref)<<std::endl;
std::cout << GridLogMessage << "mflop/s = " << flops / (t1 - t0) << std::endl;
std::cout << GridLogMessage << "mflop/s per rank = " << flops / (t1 - t0) / NP
<< std::endl;
std::cout << GridLogMessage << "mflop/s per node = " << flops / (t1 - t0) / NN
<< std::endl;
std::cout << GridLogMessage
<< "RF GiB/s (base 2) = " << 1000000. * data_rf / ((t1 - t0))
<< std::endl;
std::cout << GridLogMessage
<< "mem GiB/s (base 2) = " << 1000000. * data_mem / ((t1 - t0))
<< std::endl;
err = ref - result;
std::cout << GridLogMessage << "norm diff " << norm2(err) << std::endl;
// exit(0);
if ((norm2(err) > 1.0e-4))
{
/*
std::cout << "RESULT\n " << result<<std::endl;
std::cout << "REF \n " << ref <<std::endl;
std::cout << "ERR \n " << err <<std::endl;
*/
std::cout << GridLogMessage << "WRONG RESULT" << std::endl;
FGrid->Barrier();
exit(-1);
}
assert(norm2(err) < 1.0e-4);
Dw.Report();
}
if (1)
{ // Naive wilson dag implementation
ref = Zero();
for (int mu = 0; mu < Nd; mu++)
{
// ref = src - Gamma(Gamma::Algebra::GammaX)* src ; // 1+gamma_x
tmp = Cshift(src, mu + 1, 1);
{
autoView(ref_v, ref, CpuWrite);
autoView(tmp_v, tmp, CpuRead);
autoView(U_v, U[mu], CpuRead);
for (int ss = 0; ss < U[mu].Grid()->oSites(); ss++)
{
for (int s = 0; s < Ls; s++)
{
int i = s + Ls * ss;
ref_v[i] += U_v[ss] * (tmp_v[i] + Gamma(Gmu[mu]) * tmp_v[i]);
;
}
}
}
{
autoView(tmp_v, tmp, CpuWrite);
autoView(U_v, U[mu], CpuRead);
autoView(src_v, src, CpuRead);
for (int ss = 0; ss < U[mu].Grid()->oSites(); ss++)
{
for (int s = 0; s < Ls; s++)
{
tmp_v[Ls * ss + s] = adj(U_v[ss]) * src_v[Ls * ss + s];
}
}
}
// tmp =adj(U[mu])*src;
tmp = Cshift(tmp, mu + 1, -1);
{
autoView(ref_v, ref, CpuWrite);
autoView(tmp_v, tmp, CpuRead);
for (int i = 0; i < ref_v.size(); i++)
{
ref_v[i] += tmp_v[i] - Gamma(Gmu[mu]) * tmp_v[i];
;
}
}
}
ref = -0.5 * ref;
}
// dump=1;
Dw.Dhop(src, result, 1);
std::cout << GridLogMessage
<< "Compare to naive wilson implementation Dag to verify correctness"
<< std::endl;
std::cout << GridLogMessage << "Called DwDag" << std::endl;
std::cout << GridLogMessage << "norm dag result " << norm2(result) << std::endl;
std::cout << GridLogMessage << "norm dag ref " << norm2(ref) << std::endl;
err = ref - result;
std::cout << GridLogMessage << "norm dag diff " << norm2(err) << std::endl;
if ((norm2(err) > 1.0e-4))
{
/*
std::cout<< "DAG RESULT\n " <<ref << std::endl;
std::cout<< "DAG sRESULT\n " <<result << std::endl;
std::cout<< "DAG ERR \n " << err <<std::endl;
*/
}
LatticeFermionF src_e(FrbGrid);
LatticeFermionF src_o(FrbGrid);
LatticeFermionF r_e(FrbGrid);
LatticeFermionF r_o(FrbGrid);
LatticeFermionF r_eo(FGrid);
std::cout << GridLogMessage << "Calling Deo and Doe and //assert Deo+Doe == Dunprec"
<< std::endl;
pickCheckerboard(Even, src_e, src);
pickCheckerboard(Odd, src_o, src);
std::cout << GridLogMessage << "src_e" << norm2(src_e) << std::endl;
std::cout << GridLogMessage << "src_o" << norm2(src_o) << std::endl;
// S-direction is INNERMOST and takes no part in the parity.
std::cout << GridLogMessage
<< "*********************************************************" << std::endl;
std::cout << GridLogMessage
<< "* Benchmarking DomainWallFermionF::DhopEO " << std::endl;
std::cout << GridLogMessage << "* Vectorising space-time by " << vComplexF::Nsimd()
<< std::endl;
if (sizeof(RealF) == 4)
std::cout << GridLogMessage << "* SINGLE precision " << std::endl;
if (sizeof(RealF) == 8)
std::cout << GridLogMessage << "* DOUBLE precision " << std::endl;
#ifdef GRID_OMP
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;
#endif
if (WilsonKernelsStatic::Opt == WilsonKernelsStatic::OptGeneric)
std::cout << GridLogMessage << "* Using GENERIC Nc WilsonKernels" << std::endl;
if (WilsonKernelsStatic::Opt == WilsonKernelsStatic::OptHandUnroll)
std::cout << GridLogMessage << "* Using Nc=3 WilsonKernels" << std::endl;
if (WilsonKernelsStatic::Opt == WilsonKernelsStatic::OptInlineAsm)
std::cout << GridLogMessage << "* Using Asm Nc=3 WilsonKernels" << std::endl;
std::cout << GridLogMessage
<< "*********************************************************" << std::endl;
{
Dw.ZeroCounters();
FGrid->Barrier();
Dw.DhopEO(src_o, r_e, DaggerNo);
double t0 = usecond();
for (int i = 0; i < ncall; i++)
{
#ifdef CUDA_PROFILE
if (i == 10)
cudaProfilerStart();
#endif
Dw.DhopEO(src_o, r_e, DaggerNo);
#ifdef CUDA_PROFILE
if (i == 20)
cudaProfilerStop();
#endif
}
double t1 = usecond();
FGrid->Barrier();
double volume = Ls;
for (int mu = 0; mu < Nd; mu++)
volume = volume * latt4[mu];
double flops = (single_site_flops * volume * ncall) / 2.0;
json["Deo"]["calls"] = ncall;
json["Deo"]["time"] = t1 - t0;
json["Deo"]["mflops"] = flops / (t1 - t0);
json["Deo"]["mflops_per_rank"] = flops / (t1 - t0) / NP;
json["Deo"]["mflops_per_node"] = flops / (t1 - t0) / NN;
std::cout << GridLogMessage << "Deo mflop/s = " << flops / (t1 - t0) << std::endl;
std::cout << GridLogMessage << "Deo mflop/s per rank " << flops / (t1 - t0) / NP
<< std::endl;
std::cout << GridLogMessage << "Deo mflop/s per node " << flops / (t1 - t0) / NN
<< std::endl;
Dw.Report();
}
Dw.DhopEO(src_o, r_e, DaggerNo);
Dw.DhopOE(src_e, r_o, DaggerNo);
Dw.Dhop(src, result, DaggerNo);
std::cout << GridLogMessage << "r_e" << norm2(r_e) << std::endl;
std::cout << GridLogMessage << "r_o" << norm2(r_o) << std::endl;
std::cout << GridLogMessage << "res" << norm2(result) << std::endl;
setCheckerboard(r_eo, r_o);
setCheckerboard(r_eo, r_e);
err = r_eo - result;
std::cout << GridLogMessage << "norm diff " << norm2(err) << std::endl;
if ((norm2(err) > 1.0e-4))
{
/*
std::cout<< "Deo RESULT\n " <<r_eo << std::endl;
std::cout<< "Deo REF\n " <<result << std::endl;
std::cout<< "Deo ERR \n " << err <<std::endl;
*/
}
pickCheckerboard(Even, src_e, err);
pickCheckerboard(Odd, src_o, err);
std::cout << GridLogMessage << "norm diff even " << norm2(src_e) << std::endl;
std::cout << GridLogMessage << "norm diff odd " << norm2(src_o) << std::endl;
assert(norm2(src_e) < 1.0e-4);
assert(norm2(src_o) < 1.0e-4);
if (!json_filename.empty())
{
std::cout << GridLogMessage << "writing benchmark results to " << json_filename
<< std::endl;
int me = 0;
MPI_Comm_rank(MPI_COMM_WORLD, &me);
if (me == 0)
{
std::ofstream json_file(json_filename);
json_file << std::setw(4) << json;
}
}
Grid_finalize();
exit(0);
}

View File

@ -26,6 +26,20 @@ along with this program. If not, see <http://www.gnu.org/licenses/>.
#define GRID_MSG_MAXSIZE 1024
#endif
#define GRID_BIG_SEP \
"==============================================================================="
#define GRID_SMALL_SEP "------------------------------------------"
#define grid_big_sep() \
{ \
GRID_MSG << GRID_BIG_SEP << std::endl; \
}
#define grid_small_sep() \
{ \
GRID_MSG << GRID_SMALL_SEP << std::endl; \
}
#define grid_printf(...) \
{ \
char _buf[GRID_MSG_MAXSIZE]; \

View File

@ -1,12 +1,8 @@
ACLOCAL_AMFLAGS = -I .buildutils/m4
bin_PROGRAMS = \
Benchmark_comms_host_device \
Benchmark_dwf_fp32 \
Benchmark_Grid \
Benchmark_IO
Benchmark_comms_host_device_SOURCES = Benchmark_comms_host_device.cpp
Benchmark_dwf_fp32_SOURCES = Benchmark_dwf_fp32.cpp
Benchmark_Grid_SOURCES = Benchmark_Grid.cpp
Benchmark_IO_SOURCES = Benchmark_IO.cpp

View File

@ -6,6 +6,7 @@ The benchmarks can be summarised as follows
- `Benchmark_Grid`: This benchmark measure floating point performances for various fermion
matrices, as well as bandwidth measurement for different operations. Measurements are
performed for a fixed range of problem sizes.
- `Benchmark_IO`: Parallel I/O benchmark.
## TL;DR
Build and install Grid, all dependencies, and the benchmark with
@ -28,7 +29,7 @@ You should first deploy the environment for the specific system you are using, f
systems/tursa/bootstrap-env.sh ./env
```
will deploy the relevant environment for the [Tursa](https://www.epcc.ed.ac.uk/hpc-services/dirac-tursa-gpu) supercomputer in `./env`. This step might compile from source a large set
of packages, and might take some time to complete.
of packages, and take some time to complete.
After that, the environment directory (`./env` in the example above) will contain a `env.sh` file that need to be sourced to activate the environment
```bash
@ -66,4 +67,84 @@ where `<env_dir>` is the environment directory and `<config>` is the build confi
## Running the benchmarks
After building the benchmarks as above you can find the binaries in
`<env_dir>/prefix/gridbench_<config>`.
`<env_dir>/prefix/gridbench_<config>`. Depending on the system selected, the environment
directory might also contain batch script examples. More information about the benchmarks
is provided below.
### `Benchmark_Grid`
This benchmark performs flop/s measurement for typical lattice QCD sparse matrices, as
well as memory and inter-process bandwidth measurement using Grid routines. The benchmark
command accept any Grid flag (see complete list with `--help`), as well as a
`--json-out <file>` flag to save the measurement results in JSON to `<file>`. The
benchmarks are performed on a fix set of problem sizes, and the Grid flag `--grid` will
be ignored.
The resulting metrics are as follows, all data size units are in base 2
(i.e. 1 kB = 1024 B).
*Memory bandwidth*
One sub-benchmark measure the memory bandwidth using a lattice version of the `axpy` BLAS
routine, in a similar fashion to the STREAM benchmark. The JSON entries under `"axpy"`
have the form
```json
{
"GBps": 215.80653375861607, // bandwidth in GB/s/node
"GFlops": 19.310041765757834, // FP performance (double precision)
"L": 8, // local lattice volume
"size_MB": 3.0 // memory size in MB/node
}
```
A second benchmark performs site-wise SU(4) matrix multiplication, and has a higher
arithmetic intensity than the `axpy` one (although it is still memory-bound).
The JSON entries under `"SU4"` have the form
```json
{
"GBps": 394.76639187026865, // bandwidth in GB/s/node
"GFlops": 529.8464820758512, // FP performance (single precision)
"L": 8, // local lattice size
"size_MB": 6.0 // memory size in MB/node
}
```
*Inter-process bandwidth*
This sub-benchmark measures the achieved bidirectional bandwidth in threaded halo exchange
using routines in Grid. The exchange is performed in each direction on the MPI Cartesian
grid which is parallelised across at least 2 processes. The resulting bandwidth is related
to node-local transfers (inter-CPU, NVLink, ...) or network transfers depending on the MPI
decomposition. he JSON entries under `"comms"` have the form
```json
{
"L": 40, // local lattice size
"bytes": 73728000, // payload size in B/rank
"dir": 2, // direction of the exchange, 8 possible directions
// (0: +x, 1: +y, ..., 5: -x, 6: -y, ...)
"rate_GBps": {
"error": 6.474271894240327, // standard deviation across measurements (GB/s/node)
"max": 183.10546875, // maximum measured bandwidth (GB/s/node)
"mean": 175.21747026766676 // average measured bandwidth (GB/s/node)
},
"time_usec": 3135.055 // average transfer time (microseconds)
}
```
*Floating-point performances*
This sub-benchmark measures the achieved floating-point performances using the
Wilson fermion, domain-wall fermion, and staggered fermion sparse matrices from Grid.
In the `"flops"` and `"results"` section of the JSON output are recorded the best
performances, e.g.
```json
{
"Gflops_dwf4": 366.5251173474483, // domain-wall in Gflop/s/node (single precision)
"Gflops_staggered": 7.5982861018529455, // staggered in Gflop/s/node (single precision)
"Gflops_wilson": 15.221839719288932, // Wilson in Gflop/s/node (single precision)
"L": 8 // local lattice size
}
```
Here "best" means across a number of different implementations of the routines. Please
see the log of the benchmark for an additional breakdown. Finally, the JSON output
contains a "comparison point", which is the average of the L=24 and L=32 best
domain-wall performances.

View File

@ -20,8 +20,12 @@ mkdir -p "${build_dir}"
source "${env_dir}/env.sh"
entry=$(jq ".configs[]|select(.name==\"${cfg}\")" "${env_dir}"/grid-config.json)
env_script=$(echo "${entry}" | jq -r ".\"env-script\"")
cd "${build_dir}" || return
source "${env_dir}/${env_script}"
cd "${script_dir}"
if [ ! -f configure ]; then
./bootstrap.sh
fi
cd "${build_dir}"
if [ ! -f Makefile ]; then
"${script_dir}/configure" --with-grid="${env_dir}/prefix/grid_${cfg}" \
--prefix="${env_dir}/prefix/gridbench_${cfg}"

View File

@ -1,8 +1,8 @@
#!/usr/bin/env bash
# shellcheck disable=SC1091
GRIDENVDIR="$(dirname "$(readlink -f "${BASH_SOURCE:-$0}")")"
export GRIDENVDIR
export PATH="${GRIDENVDIR}/prefix/base/bin:${PATH}"
export ACLOCAL_PATH="${GRIDENVDIR}/prefix/base/share/aclocal:${ACLOCAL_PATH}"
source "${GRIDENVDIR}"/spack/share/spack/setup-env.sh
env_dir="$(dirname "$(readlink -f "${BASH_SOURCE:-$0}")")"
mkdir -p ~/.config/lattice-benchmarks
echo "${env_dir}" > ~/.config/lattice-benchmarks/grid-env
source "${env_dir}/spack/share/spack/setup-env.sh"
spack load jq git

0
Grid/systems/tursa/files/cpu-mpi-wrapper.sh Normal file → Executable file
View File

5
Grid/systems/tursa/files/gpu-mpi-wrapper.sh Normal file → Executable file
View File

@ -1,13 +1,12 @@
#!/usr/bin/env bash
lrank=$OMPI_COMM_WORLD_LOCAL_RANK
numa1=$(( 2 * lrank))
numa2=$(( 2 * lrank + 1 ))
numa1=$((lrank))
netdev=mlx5_${lrank}:1
export CUDA_VISIBLE_DEVICES=$OMPI_COMM_WORLD_LOCAL_RANK
export UCX_NET_DEVICES=${netdev}
BINDING="--interleave=$numa1,$numa2"
BINDING="--interleave=$numa1"
echo "$(hostname) - $lrank device=$CUDA_VISIBLE_DEVICES binding=$BINDING"

View File

@ -0,0 +1,17 @@
#!/usr/bin/env bash
# OpenMP/OpenMPI/UCX environment ###############################################
export OMP_NUM_THREADS=8
export OMPI_MCA_btl=^uct,openib
export OMPI_MCA_pml=ucx
export UCX_TLS=gdr_copy,rc,rc_x,sm,cuda_copy,cuda_ipc
export UCX_RNDV_SCHEME=put_zcopy
export UCX_RNDV_THRESH=16384
export UCX_IB_GPU_DIRECT_RDMA=yes
export UCX_MEMTYPE_CACHE=n
# IO environment ###############################################################
export OMPI_MCA_io=romio321
export OMPI_MCA_btl_openib_allow_ib=true
export OMPI_MCA_btl_openib_device_type=infiniband
export OMPI_MCA_btl_openib_if_exclude=mlx5_1,mlx5_2,mlx5_3

View File

@ -0,0 +1,60 @@
#!/usr/bin/env bash
# shellcheck disable=SC1091,SC2050,SC2170
#SBATCH -J benchmark-grid-16
#SBATCH -t 1:00:00
#SBATCH --nodes=16
#SBATCH --ntasks=64
#SBATCH --ntasks-per-node=4
#SBATCH --cpus-per-task=8
#SBATCH --partition=gpu
#SBATCH --gres=gpu:4
#SBATCH --output=%x.%j.out
#SBATCH --error=%x.%j.err
#SBATCH --qos=standard
#SBATCH --no-requeue
#SBATCH --gpu-freq=1410
set -euo pipefail
# load environment #############################################################
env_cfg="${HOME}/.config/lattice-benchmarks/grid-env"
if [ ! -f "${env_cfg}" ]; then
echo "error: ${env_cfg} does not exists, did you execute 'source env.sh' with your user account?"
exit 1
fi
env_dir="$(readlink -f "$(cat "${env_cfg}")")"
source "${env_dir}/env.sh" # load base Spack environment
source "${env_dir}/env-gpu.sh" # load GPU-sepcific packages
source "${env_dir}/ompi-gpu.sh" # set GPU-specific OpenMPI variables
# application and parameters ###################################################
app="${env_dir}/prefix/gridbench_gpu/bin/Benchmark_Grid"
# collect job information ######################################################
job_info_dir=job/${SLURM_JOB_NAME}.${SLURM_JOB_ID}
mkdir -p "${job_info_dir}"
date > "${job_info_dir}/start-date"
set > "${job_info_dir}/env"
ldd "${app}" > "${job_info_dir}/ldd"
md5sum "${app}" > "${job_info_dir}/app-hash"
readelf -a "${app}" > "${job_info_dir}/elf"
echo "${SLURM_JOB_NODELIST}" > "${job_info_dir}/nodes"
cp "${BASH_SOURCE[0]}" "${job_info_dir}/script"
# run! #########################################################################
mpirun -np "${SLURM_NTASKS}" -x LD_LIBRARY_PATH --bind-to none \
"${env_dir}/gpu-mpi-wrapper.sh" \
"${app}" \
--json-out "${job_info_dir}/result.json" \
--mpi 1.4.4.4 \
--accelerator-threads 8 \
--threads 8 \
--shm 2048 &> "${job_info_dir}/log"
# if we reach that point the application exited successfully ###################
touch "${job_info_dir}/success"
date > "${job_info_dir}/end-date"
################################################################################

View File

@ -0,0 +1,60 @@
#!/usr/bin/env bash
# shellcheck disable=SC1091,SC2050,SC2170
#SBATCH -J benchmark-grid-1
#SBATCH -t 1:00:00
#SBATCH --nodes=1
#SBATCH --ntasks=4
#SBATCH --ntasks-per-node=4
#SBATCH --cpus-per-task=8
#SBATCH --partition=gpu
#SBATCH --gres=gpu:4
#SBATCH --output=%x.%j.out
#SBATCH --error=%x.%j.err
#SBATCH --qos=standard
#SBATCH --no-requeue
#SBATCH --gpu-freq=1410
set -euo pipefail
# load environment #############################################################
env_cfg="${HOME}/.config/lattice-benchmarks/grid-env"
if [ ! -f "${env_cfg}" ]; then
echo "error: ${env_cfg} does not exists, did you execute 'source env.sh' with your user account?"
exit 1
fi
env_dir="$(readlink -f "$(cat "${env_cfg}")")"
source "${env_dir}/env.sh" # load base Spack environment
source "${env_dir}/env-gpu.sh" # load GPU-sepcific packages
source "${env_dir}/ompi-gpu.sh" # set GPU-specific OpenMPI variables
# application and parameters ###################################################
app="${env_dir}/prefix/gridbench_gpu/bin/Benchmark_Grid"
# collect job information ######################################################
job_info_dir=job/${SLURM_JOB_NAME}.${SLURM_JOB_ID}
mkdir -p "${job_info_dir}"
date > "${job_info_dir}/start-date"
set > "${job_info_dir}/env"
ldd "${app}" > "${job_info_dir}/ldd"
md5sum "${app}" > "${job_info_dir}/app-hash"
readelf -a "${app}" > "${job_info_dir}/elf"
echo "${SLURM_JOB_NODELIST}" > "${job_info_dir}/nodes"
cp "${BASH_SOURCE[0]}" "${job_info_dir}/script"
# run! #########################################################################
mpirun -np "${SLURM_NTASKS}" -x LD_LIBRARY_PATH --bind-to none \
"${env_dir}/gpu-mpi-wrapper.sh" \
"${app}" \
--json-out "${job_info_dir}/result.json" \
--mpi 1.1.1.4 \
--accelerator-threads 8 \
--threads 8 \
--shm 2048 &> "${job_info_dir}/log"
# if we reach that point the application exited successfully ###################
touch "${job_info_dir}/success"
date > "${job_info_dir}/end-date"
################################################################################

View File

@ -0,0 +1,60 @@
#!/usr/bin/env bash
# shellcheck disable=SC1091,SC2050,SC2170
#SBATCH -J benchmark-grid-32
#SBATCH -t 1:00:00
#SBATCH --nodes=32
#SBATCH --ntasks=128
#SBATCH --ntasks-per-node=4
#SBATCH --cpus-per-task=8
#SBATCH --partition=gpu
#SBATCH --gres=gpu:4
#SBATCH --output=%x.%j.out
#SBATCH --error=%x.%j.err
#SBATCH --qos=standard
#SBATCH --no-requeue
#SBATCH --gpu-freq=1410
set -euo pipefail
# load environment #############################################################
env_cfg="${HOME}/.config/lattice-benchmarks/grid-env"
if [ ! -f "${env_cfg}" ]; then
echo "error: ${env_cfg} does not exists, did you execute 'source env.sh' with your user account?"
exit 1
fi
env_dir="$(readlink -f "$(cat "${env_cfg}")")"
source "${env_dir}/env.sh" # load base Spack environment
source "${env_dir}/env-gpu.sh" # load GPU-sepcific packages
source "${env_dir}/ompi-gpu.sh" # set GPU-specific OpenMPI variables
# application and parameters ###################################################
app="${env_dir}/prefix/gridbench_gpu/bin/Benchmark_Grid"
# collect job information ######################################################
job_info_dir=job/${SLURM_JOB_NAME}.${SLURM_JOB_ID}
mkdir -p "${job_info_dir}"
date > "${job_info_dir}/start-date"
set > "${job_info_dir}/env"
ldd "${app}" > "${job_info_dir}/ldd"
md5sum "${app}" > "${job_info_dir}/app-hash"
readelf -a "${app}" > "${job_info_dir}/elf"
echo "${SLURM_JOB_NODELIST}" > "${job_info_dir}/nodes"
cp "${BASH_SOURCE[0]}" "${job_info_dir}/script"
# run! #########################################################################
mpirun -np "${SLURM_NTASKS}" -x LD_LIBRARY_PATH --bind-to none \
"${env_dir}/gpu-mpi-wrapper.sh" \
"${app}" \
--json-out "${job_info_dir}/result.json" \
--mpi 1.4.4.8 \
--accelerator-threads 8 \
--threads 8 \
--shm 2048 &> "${job_info_dir}/log"
# if we reach that point the application exited successfully ###################
touch "${job_info_dir}/success"
date > "${job_info_dir}/end-date"
################################################################################

View File

@ -4,7 +4,13 @@ set -euo pipefail
gcc_spec='gcc@9.4.0'
cuda_spec='cuda@11.4.0'
hdf5_spec='hdf5@1.10.7'
# hdf5 and fftw depend on OpenMPI, which we install manually. To make sure this
# dependency is picked by spack, we specify the compiler here explicitly. For
# most other packages we dont really care about the compiler (i.e. system
# compiler versus ${gcc_spec})
hdf5_spec="hdf5@1.10.7+cxx+threadsafe%${gcc_spec}"
fftw_spec="fftw%${gcc_spec}"
if (( $# != 1 )); then
echo "usage: $(basename "$0") <env dir>" 1>&2
@ -18,7 +24,7 @@ cd "${cwd}"
# General configuration ########################################################
# build with 128 tasks
echo 'config:
echo 'config:
build_jobs: 128
build_stage:
- $spack/var/spack/stage
@ -38,26 +44,23 @@ rm external.yaml
# Base compilers ###############################################################
# configure system base
spack env create base
spack env activate base
spack compiler find --scope site
# install GCC, CUDA & LLVM
spack install ${gcc_spec} ${cuda_spec} llvm
spack load llvm
# install GCC, CUDA
spack add ${gcc_spec} ${cuda_spec}
spack concretize
spack env depfile -o Makefile.tmp
make -j128 -f Makefile.tmp
spack compiler find --scope site
spack unload llvm
spack load ${gcc_spec}
spack compiler find --scope site
spack unload ${gcc_spec}
# Manual compilation of OpenMPI & UCX ##########################################
# set build directories
mkdir -p "${dir}"/build
cd "${dir}"/build
spack load ${gcc_spec} ${cuda_spec}
cuda_path=$(spack find --format "{prefix}" cuda)
gdrcopy_path=/mnt/lustre/tursafs1/apps/gdrcopy/2.3.1
@ -77,7 +80,7 @@ mkdir -p build_gpu; cd build_gpu
--enable-devel-headers --enable-examples --enable-optimizations \
--with-gdrcopy=${gdrcopy_path} --with-verbs --disable-logging \
--disable-debug --disable-assertions --enable-cma \
--with-knem=/opt/knem-1.1.4.90mlnx1/ --with-rdmacm \
--with-knem=/opt/knem-1.1.4.90mlnx2/ --with-rdmacm \
--without-rocm --without-ugni --without-java \
--enable-compiler-opt=3 --with-cuda="${cuda_path}" --without-cm \
--with-rc --with-ud --with-dc --with-mlx5-dv --with-dm \
@ -93,7 +96,7 @@ mkdir -p build_cpu; cd build_cpu
--enable-devel-headers --enable-examples --enable-optimizations \
--with-verbs --disable-logging --disable-debug \
--disable-assertions --enable-mt --enable-cma \
--with-knem=/opt/knem-1.1.4.90mlnx1/ --with-rdmacm \
--with-knem=/opt/knem-1.1.4.90mlnx2/--with-rdmacm \
--without-rocm --without-ugni --without-java \
--enable-compiler-opt=3 --without-cm --without-ugni --with-rc \
--with-ud --with-dc --with-mlx5-dv --with-dm --enable-mt --without-go
@ -119,13 +122,13 @@ mkdir build_gpu; cd build_gpu
../configure --prefix="${dir}"/prefix/ompi_gpu --without-xpmem \
--with-ucx="${dir}"/prefix/ucx_gpu \
--with-ucx-libdir="${dir}"/prefix/ucx_gpu/lib \
--with-knem=/opt/knem-1.1.4.90mlnx1/ \
--with-knem=/opt/knem-1.1.4.90mlnx2/ \
--enable-mca-no-build=btl-uct \
--with-cuda="${cuda_path}" --disable-getpwuid \
--with-verbs --with-slurm --enable-mpi-fortran=all \
--with-pmix=internal --with-libevent=internal
make -j 128
make install
make -j 128
make install
cd ..
# openmpi cpu build
@ -133,7 +136,7 @@ mkdir build_cpu; cd build_cpu
../configure --prefix="${dir}"/prefix/ompi_cpu --without-xpmem \
--with-ucx="${dir}"/prefix/ucx_cpu \
--with-ucx-libdir="${dir}"/prefix/ucx_cpu/lib \
--with-knem=/opt/knem-1.1.4.90mlnx1/ \
--with-knem=/opt/knem-1.1.4.90mlnx2/ \
--enable-mca-no-build=btl-uct --disable-getpwuid \
--with-verbs --with-slurm --enable-mpi-fortran=all \
--with-pmix=internal --with-libevent=internal
@ -141,65 +144,65 @@ make -j 128
make install
cd "${dir}"
ucx_spec_gpu="ucx@1.12.0.GPU%${gcc_spec}"
ucx_spec_cpu="ucx@1.12.0.CPU%${gcc_spec}"
openmpi_spec_gpu="openmpi@4.1.1.GPU%${gcc_spec}"
openmpi_spec_cpu="openmpi@4.1.1.CPU%${gcc_spec}"
# Add externals to spack
echo "packages:
ucx:
externals:
- spec: \"ucx@1.12.0.GPU%gcc@9.4.0\"
- spec: \"${ucx_spec_gpu}\"
prefix: ${dir}/prefix/ucx_gpu
- spec: \"ucx@1.12.0.CPU%gcc@9.4.0\"
- spec: \"${ucx_spec_cpu}\"
prefix: ${dir}/prefix/ucx_cpu
buildable: False
openmpi:
externals:
- spec: \"openmpi@4.1.1.GPU%gcc@9.4.0\"
- spec: \"${openmpi_spec_gpu}\"
prefix: ${dir}/prefix/ompi_gpu
- spec: \"openmpi@4.1.1.CPU%gcc@9.4.0\"
- spec: \"${openmpi_spec_cpu}\"
prefix: ${dir}/prefix/ompi_cpu
buildable: False" > spack.yaml
spack config --scope site add -f spack.yaml
rm spack.yaml
spack install ucx@1.12.0.GPU%gcc@9.4.0 openmpi@4.1.1.GPU%gcc@9.4.0
spack install ucx@1.12.0.CPU%gcc@9.4.0 openmpi@4.1.1.CPU%gcc@9.4.0
spack env deactivate
cd "${cwd}"
# environments #################################################################
dev_tools=("autoconf" "automake" "libtool" "jq")
ompi_gpu_hash=$(spack find --format "{hash}" openmpi@4.1.1.GPU)
ompi_cpu_hash=$(spack find --format "{hash}" openmpi@4.1.1.CPU)
dev_tools=("autoconf" "automake" "libtool" "jq" "git")
spack env create grid-gpu
spack env activate grid-gpu
spack add ${gcc_spec} ${cuda_spec} "${dev_tools[@]}"
spack add ucx@1.12.0.GPU%gcc@9.4.0 openmpi@4.1.1.GPU%gcc@9.4.0
spack add ${hdf5_spec}+cxx+threadsafe ^/"${ompi_gpu_hash}"
spack add fftw ^/"${ompi_gpu_hash}"
spack add openssl gmp mpfr c-lime
spack install
spack compiler find --scope site
spack add ${gcc_spec} ${cuda_spec} ${ucx_spec_gpu} ${openmpi_spec_gpu}
spack add ${hdf5_spec} ${fftw_spec}
spack add openssl gmp mpfr c-lime "${dev_tools[@]}"
spack concretize
spack env depfile -o Makefile.tmp
make -j128 -f Makefile.tmp
spack env deactivate
spack env create grid-cpu
spack env activate grid-cpu
spack add llvm "${dev_tools[@]}"
spack add ucx@1.12.0.CPU%gcc@9.4.0 openmpi@4.1.1.CPU%gcc@9.4.0
spack add ${hdf5_spec}+cxx+threadsafe ^/"${ompi_cpu_hash}"
spack add fftw ^/"${ompi_cpu_hash}"
spack add openssl gmp mpfr c-lime
spack install
spack compiler find --scope site
spack add ${gcc_spec} ${ucx_spec_cpu} ${openmpi_spec_cpu}
spack add ${hdf5_spec} ${fftw_spec}
spack add openssl gmp mpfr c-lime "${dev_tools[@]}"
spack concretize
spack env depfile -o Makefile.tmp
make -j128 -f Makefile.tmp
spack env deactivate
# Final setup ##################################################################
spack clean
spack gc -y
#spack gc -y # "spack gc" tends to get hung up for unknown reasons
# add more environment variables in module loading
spack config --scope site add 'modules:prefix_inspections:lib:[LD_LIBRARY_PATH,LIBRARY_PATH]'
spack config --scope site add 'modules:prefix_inspections:lib64:[LD_LIBRARY_PATH,LIBRARY_PATH]'
spack config --scope site add 'modules:prefix_inspections:include:[C_INCLUDE_PATH,CPLUS_INCLUDE_PATH,INCLUDE]'
spack module tcl refresh -y
# permission change for group access
chmod -R g+rw "${dir}/spack/var/spack/cache"
setfacl -d -R -m g::rwX "${dir}/spack/var/spack/cache"

14
Quda/.clang-format Normal file
View File

@ -0,0 +1,14 @@
{
BasedOnStyle: LLVM,
UseTab: Never,
IndentWidth: 2,
TabWidth: 2,
BreakBeforeBraces: Allman,
AllowShortIfStatementsOnASingleLine: false,
IndentCaseLabels: false,
ColumnLimit: 90,
AccessModifierOffset: -4,
NamespaceIndentation: All,
FixNamespaceComments: false,
SortIncludes: true,
}

458
Quda/Benchmark_Quda.cpp Normal file
View File

@ -0,0 +1,458 @@
#include <algorithm>
#include <array>
#include <blas_quda.h>
#include <cassert>
#include <chrono>
#include <color_spinor_field.h>
#include <communicator_quda.h>
#include <dirac_quda.h>
#include <fstream>
#include <gauge_tools.h>
#include <memory>
#include <mpi.h>
#include <stdio.h>
#include <stdlib.h>
// remove to use QUDA's own flop counting instead of Grid's convention
#define FLOP_COUNTING_GRID
#include "json.hpp"
using nlohmann::json;
json json_results;
using namespace quda;
// thanks chatGPT :)
std::string get_timestamp()
{
// Get the current time
auto now = std::chrono::system_clock::now();
// Convert the current time to a time_t object
std::time_t currentTime = std::chrono::system_clock::to_time_t(now);
// Format the time using std::put_time
std::stringstream ss;
ss << std::put_time(std::localtime(&currentTime), "%Y%m%d %H:%M:%S");
return ss.str();
}
// This is the MPI grid, i.e. the layout of ranks
int nranks = -1;
std::array<int, 4> mpi_grid = {1, 1, 1, 1};
// run f() in a loop for roughly target_time seconds
// returns seconds per iteration it took
template <class F> double bench(F const &f, double target_time, int niter_warmup = 5)
{
device_timer_t timer;
timer.start();
for (int iter = 0; iter < niter_warmup; ++iter)
f();
timer.stop();
double secs = timer.last() / niter_warmup;
int niter = std::max(1, int(target_time / secs));
// niter = std::min(1000, niter);
// printfQuda("during warmup took %f s/iter, deciding on %d iters\n", secs, niter);
// important: each rank has its own timer, so their measurements can slightly vary. But
// 'niter' needs to be consistent (bug took me a couple hours to track down)
comm_broadcast_global(&niter, sizeof(niter), 0);
timer.reset(__FUNCTION__, __FILE__, __LINE__);
timer.start();
for (int iter = 0; iter < niter; ++iter)
f();
timer.stop();
return timer.last() / niter;
}
void initComms(int argc, char **argv)
{
// init MPI communication
MPI_Init(&argc, &argv);
MPI_Comm_size(MPI_COMM_WORLD, &nranks);
assert(1 <= nranks && nranks <= 100000);
mpi_grid[3] = nranks;
// this maps coordinates to rank number
auto lex_rank_from_coords = [](int const *coords, void *)
{
int rank = coords[0];
for (int i = 1; i < 4; i++)
rank = mpi_grid[i] * rank + coords[i];
return rank;
};
initCommsGridQuda(4, mpi_grid.data(), lex_rank_from_coords, nullptr);
for (int d = 0; d < 4; d++)
if (mpi_grid[d] > 1)
commDimPartitionedSet(d);
json_results["geometry"]["ranks"] = nranks;
json_results["geometry"]["mpi"] = mpi_grid;
}
// creates a random gauge field. L = local(!) size
cudaGaugeField make_gauge_field(int L)
{
GaugeFieldParam param;
// dimension and type of the lattice object
param.nDim = 4;
param.x[0] = L;
param.x[1] = L;
param.x[2] = L;
param.x[3] = L;
// number of colors. potentially confusingly, QUDA sometimes uses the word "color" to
// things unrelated with physical color. things like "nColor=32" do pop up in deflation
// solvers where it (to my understanding) refers to the number of (parallely processed)
// deflation vectors.
param.nColor = 3;
// boundary conditions (dont really care for benchmark)
param.t_boundary = QUDA_PERIODIC_T;
// for this benchmark we only need "SINGLE" and/or "DOUBLE" precision. But smaller
// precisions are available in QUDA too
param.setPrecision(QUDA_SINGLE_PRECISION);
// no even/odd subset, we want a full lattice
param.siteSubset = QUDA_FULL_SITE_SUBSET;
// what kind of 3x3 matrices the field contains. A proper gauge field has SU(3)
// matrices, but (for example) smeared/thick links could have non-unitary links.
param.link_type = QUDA_SU3_LINKS;
// "NULL" does not initialize the field upon creation, "ZERO" would set everything to 0
param.create = QUDA_NULL_FIELD_CREATE;
// field should be allocated directly on the accelerator/GPU
param.location = QUDA_CUDA_FIELD_LOCATION;
// "reconstruct" here means reconstructing a SU(3) matrix from fewer than 18 real
// numbers (=3x3 complex numbers). Great feature in production (saving
// memory/cache/network bandwidth), not used for this benchmark.
param.reconstruct = QUDA_RECONSTRUCT_NO;
// "ghostExchange" would often be called "halo exchange" outside of Quda. This has
// nothing to do with ghost fields from continuum/perturbative qcd.
param.ghostExchange = QUDA_GHOST_EXCHANGE_NO;
// This controls the physical order of elements. "float2" is the the default
param.order = QUDA_FLOAT2_GAUGE_ORDER;
// this means the field is a LORENTZ vector (which a gauge field must be). Has nothing
// to do with spin.
param.geometry = QUDA_VECTOR_GEOMETRY;
// create the field and fill with random SU(3) matrices
// std::cout << param << std::endl; // double-check parameters
auto U = cudaGaugeField(param);
gaugeGauss(U, /*seed=*/1234, 1.0);
return U;
}
// create a random source vector (L = local size)
ColorSpinorField make_source(int L, int Ls = 1)
{
// NOTE: `param.x` directly determines the size of the (local, per rank) memory
// allocation. Thus for checkerboarding, we have to specifly x=(L/2,L,L,L) to get a
// physical local volume of L^4, thus implicity choosing a dimension for the
// checkerboarding (shouldnt really matter of course which one).
ColorSpinorParam param;
param.nColor = 3;
param.nSpin = 4;
param.nVec = 1; // only a single vector
param.pad = 0;
param.siteSubset = QUDA_PARITY_SITE_SUBSET;
param.nDim = Ls == 1 ? 4 : 5;
param.x[0] = L / 2;
param.x[1] = L;
param.x[2] = L;
param.x[3] = L;
param.x[4] = Ls;
param.pc_type = QUDA_4D_PC;
param.siteOrder = QUDA_EVEN_ODD_SITE_ORDER;
// somewhat surprisingly, the DiracWilson::Dslash(...) function only works with the
// UKQCD_GAMMA_BASIS
param.gammaBasis = QUDA_UKQCD_GAMMA_BASIS;
param.create = QUDA_NULL_FIELD_CREATE; // do not (zero-) initilize the field
param.setPrecision(QUDA_SINGLE_PRECISION);
param.location = QUDA_CUDA_FIELD_LOCATION;
// create the field and fill it with random values
auto src = ColorSpinorField(param);
quda::RNG rng(src, 1234);
spinorNoise(src, rng, QUDA_NOISE_GAUSS);
/*printfQuda(
"created src with norm = %f (sanity check: should be close to %f) and %f bytes\n",
blas::norm2(src), 2.0 * 12 * geom[0] * geom[1] * geom[2] * geom[3],
src.Bytes() * 1.0);*/
// src.PrintDims();
return src;
}
void benchmark_wilson(std::vector<int> const &L_list, double target_time)
{
printfQuda("==================== wilson dirac operator ====================\n");
#ifdef FLOP_COUNTING_GRID
printfQuda("IMPORTANT: flop counting as in Benchmark_Grid\n");
#else
printfQuda("IMPORTANT: flop counting by QUDA's own convention (different from "
"Benchmark_Grid)\n");
#endif
printfQuda("%5s %15s %15s\n", "L", "time (usec)", "Gflop/s/rank");
for (int L : L_list)
{
// printfQuda("starting wilson L=%d\n", L);
auto U = make_gauge_field(L);
auto src = make_source(L);
// create (Wilson) dirac operator
DiracParam param;
param.kappa = 0.10;
param.dagger = QUDA_DAG_NO;
param.matpcType = QUDA_MATPC_EVEN_EVEN;
auto dirac = DiracWilson(param);
// insert gauge field into the dirac operator
// (the additional nullptr's are for smeared links and fancy preconditioners and such.
// Not used for simple Wilson fermions)
dirac.updateFields(&U, nullptr, nullptr, nullptr);
auto res = ColorSpinorField(ColorSpinorParam(src));
auto f = [&]() { dirac.Dslash(res, src, QUDA_EVEN_PARITY); };
// first run to get the quda tuning out of the way
dirac.Flops(); // reset flops counter
f();
double flops = 1.0 * dirac.Flops();
// actual benchmarking
auto start_time = get_timestamp();
double secs = bench(f, target_time);
auto end_time = get_timestamp();
#ifdef FLOP_COUNTING_GRID
// this is the flop counting from Benchmark_Grid
double Nc = 3;
double Nd = 4;
double Ns = 4;
flops = (Nc * (6 + (Nc - 1) * 8) * Ns * Nd + 2 * Nd * Nc * Ns + 2 * Nd * Nc * Ns * 2);
flops *= L * L * L * L / 2.0;
#endif
printfQuda("%5d %15.2f %15.2f\n", L, secs * 1e6, flops / secs * 1e-9);
json tmp;
tmp["L"] = L;
tmp["Gflops_wilson"] = flops / secs * 1e-9;
tmp["start_time"] = start_time;
tmp["end_time"] = end_time;
json_results["flops"]["results"].push_back(tmp);
}
}
void benchmark_dwf(std::vector<int> const &L_list, double target_time)
{
printfQuda("==================== domain wall dirac operator ====================\n");
#ifdef FLOP_COUNTING_GRID
printfQuda("IMPORTANT: flop counting as in Benchmark_Grid\n");
#else
printfQuda("IMPORTANT: flop counting by QUDA's own convention (different from "
"Benchmark_Grid)\n");
#endif
printfQuda("%5s %15s %15s\n", "L", "time (usec)", "Gflop/s/rank");
int Ls = 12;
for (int L : L_list)
{
// printfQuda("starting dwf L=%d\n", L);
auto U = make_gauge_field(L);
auto src = make_source(L, Ls);
// create dirac operator
DiracParam param;
param.kappa = 0.10;
param.Ls = Ls;
param.m5 = 0.1;
param.dagger = QUDA_DAG_NO;
param.matpcType = QUDA_MATPC_EVEN_EVEN;
auto dirac = DiracDomainWall(param);
// insert gauge field into the dirac operator
// (the additional nullptr's are for smeared links and fancy preconditioners and such)
dirac.updateFields(&U, nullptr, nullptr, nullptr);
auto res = ColorSpinorField(ColorSpinorParam(src));
auto f = [&]() { dirac.Dslash(res, src, QUDA_EVEN_PARITY); };
// first run to get the quda tuning out of the way
dirac.Flops(); // reset flops counter
f();
double flops = 1.0 * dirac.Flops();
// actual benchmarking
auto start_time = get_timestamp();
double secs = bench(f, target_time);
auto end_time = get_timestamp();
#ifdef FLOP_COUNTING_GRID
// this is the flop counting from Benchmark_Grid
double Nc = 3;
double Nd = 4;
double Ns = 4;
flops = (Nc * (6 + (Nc - 1) * 8) * Ns * Nd + 2 * Nd * Nc * Ns + 2 * Nd * Nc * Ns * 2);
flops *= L * L * L * L * Ls / 2.0;
#endif
printfQuda("%5d %15.2f %15.2f\n", L, secs * 1e6, flops / secs * 1e-9);
json tmp;
tmp["L"] = L;
tmp["Gflops_dwf4"] = flops / secs * 1e-9;
tmp["start_time"] = start_time;
tmp["end_time"] = end_time;
json_results["flops"]["results"].push_back(tmp);
}
}
void benchmark_axpy(std::vector<int> const &L_list, double target_time)
{
// number of iterations for warmup / measurement
// (feel free to change for noise/time tradeoff)
constexpr int niter_warmup = 5;
printfQuda("==================== axpy / memory ====================\n");
ColorSpinorParam param;
param.nDim = 4; // 4-dimensional lattice
param.x[4] = 1; // no fifth dimension
param.nColor = 3; // supported values for nSpin/nColor are configured when compiling
// QUDA. "3*4" will probably always be enabled, so we stick with this
param.nSpin = 4;
param.nVec = 1; // just a single vector
param.siteSubset = QUDA_FULL_SITE_SUBSET; // full lattice = no odd/even
param.pad = 0; // no padding
param.create = QUDA_NULL_FIELD_CREATE; // do not (zero-) initilize the field
param.location = QUDA_CUDA_FIELD_LOCATION; // field should reside on GPU
param.setPrecision(QUDA_SINGLE_PRECISION);
// the following dont matter for an axpy benchmark, but need to choose something
param.pc_type = QUDA_4D_PC;
param.siteOrder = QUDA_EVEN_ODD_SITE_ORDER;
param.gammaBasis = QUDA_DEGRAND_ROSSI_GAMMA_BASIS;
printfQuda("%5s %15s %15s %15s %15s\n", "L", "size (MiB/rank)", "time (usec)",
"GiB/s/rank", "Gflop/s/rank");
for (int L : L_list)
{
// printfQuda("starting axpy L=%d\n", L);
// IMPORTANT: all of `param.x`, `field_elements`, `field.Bytes()`
// are LOCAL, i.e. per rank / per GPU
param.x[0] = L;
param.x[1] = L;
param.x[2] = L;
param.x[3] = L;
// number of (real) elements in one (local) field
size_t field_elements = 2 * param.x[0] * param.x[1] * param.x[2] * param.x[3] *
param.nColor * param.nSpin;
// create the field(s)
auto fieldA = ColorSpinorField(param);
auto fieldB = ColorSpinorField(param);
assert(fieldA.Bytes() == sizeof(float) * field_elements); // sanity check
assert(fieldB.Bytes() == sizeof(float) * field_elements); // sanity check
// fill fields with random values
quda::RNG rng(fieldA, 1234);
spinorNoise(fieldA, rng, QUDA_NOISE_GAUSS);
spinorNoise(fieldB, rng, QUDA_NOISE_GAUSS);
// number of operations / bytes per iteration
// axpy is one addition, one multiplication, two read, one write
double flops = 2 * field_elements;
double memory = 3 * sizeof(float) * field_elements;
auto f = [&]() { blas::axpy(1.234, fieldA, fieldB); };
// first run to get the quda tuning out of the way
f();
// actual benchmarking
auto start_time = get_timestamp();
double secs = bench(f, target_time);
auto end_time = get_timestamp();
double mem_MiB = memory / 1024. / 1024.;
double GBps = mem_MiB / 1024 / secs;
printfQuda("%5d %15.2f %15.2f %15.2f %15.2f\n", L, mem_MiB, secs * 1e6, GBps,
flops / secs * 1e-9);
json tmp;
tmp["L"] = L;
tmp["size_MB"] = mem_MiB;
tmp["GBps"] = GBps;
tmp["GFlops"] = flops / secs * 1e-9;
tmp["start_time"] = start_time;
tmp["end_time"] = end_time;
json_results["axpy"].push_back(tmp);
}
}
int main(int argc, char **argv)
{
std::string json_filename = ""; // empty indicates no json output
for (int i = 0; i < argc; i++)
{
if (std::string(argv[i]) == "--json-out")
json_filename = argv[i + 1];
}
initComms(argc, argv);
initQuda(-1); // -1 for multi-gpu. otherwise this selects the device to be used
// verbosity options are:
// SILENT, SUMMARIZE, VERBOSE, DEBUG_VERBOSE
setVerbosity(QUDA_SUMMARIZE);
printfQuda("MPI layout = %d %d %d %d\n", mpi_grid[0], mpi_grid[1], mpi_grid[2],
mpi_grid[3]);
benchmark_axpy({8, 12, 16, 24, 32, 48}, 1.0);
setVerbosity(QUDA_SILENT);
benchmark_wilson({8, 12, 16, 24, 32, 48}, 1.0);
benchmark_dwf({8, 12, 16, 24, 32}, 1.0);
setVerbosity(QUDA_SUMMARIZE);
printfQuda("==================== done with all benchmarks ====================\n");
if (!json_filename.empty())
{
printfQuda("writing benchmark results to %s\n", json_filename.c_str());
int me = 0;
MPI_Comm_rank(MPI_COMM_WORLD, &me);
if (me == 0)
{
std::ofstream json_file(json_filename);
json_file << std::setw(2) << json_results;
}
}
endQuda();
quda::comm_finalize();
MPI_Finalize();
}

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# QUDA benchmarks
This folder contains benchmarks for the [QUDA](https://github.com/lattice/quda) library.
- `Benchmark_Quda`: This benchmark measure floating point performances of fermion
matrices (Wilson and DWF), as well as memory bandwidth (using a simple `axpy` operation). Measurements are
performed for a fixed range of problem sizes.
## Building
After setting up your compilation environment (Tursa: `source /home/dp207/dp207/shared/env/production/env-{base,gpu}.sh`):
```bash
./build-quda.sh <env_dir> # build Quda
./build-benchmark.sh <env_dir> # build benchmark
```
where `<env_dir>` is an arbitrary directory where every product will be stored.
## Running the Benchmark
The benchmark should be run as
```bash
mpirun -np <ranks> <env_dir>/prefix/qudabench/Benchmark_Quda
```
where `<ranks>` is the total number of GPU's to use. On Tursa this is 4 times the number of nodes.
Note:
- on Tursa, the `wrapper.sh` script that is typically used with Grid is not necessary.
- due to Qudas automatic tuning, the benchmark might take significantly longer to run than `Benchmark_Grid` (even though it does fewer things).
- setting `QUDA_ENABLE_TUNING=0` disables all tuning (degrades performance severely). By default, it is turned on.
- setting `QUDA_RESOURCE_PATH=<some folder>` enables Quda to save and reuse optimal tuning parameters, making repeated runs much faster

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#!/usr/bin/env bash
# shellcheck disable=SC1090,SC1091
set -euo pipefail
if (( $# != 1 )); then
echo "usage: $(basename "$0") <environment directory>" 1>&2
exit 1
fi
env_dir=$1
# TODO: this is Tursa specific. have not figured out the correct way to do this.
EXTRA_LIBS="/home/dp207/dp207/shared/env/versions/220428/spack/opt/spack/linux-rhel8-zen2/gcc-9.4.0/cuda-11.4.0-etxow4jb23qdbs7j6txczy44cdatpj22/lib64/stubs/libcuda.so /home/dp207/dp207/shared/env/versions/220428/spack/opt/spack/linux-rhel8-zen2/gcc-9.4.0/cuda-11.4.0-etxow4jb23qdbs7j6txczy44cdatpj22/lib64/stubs/libnvidia-ml.so"
# NOTE: these flags need to be in sync with Qudas compilation options (see build-quda.sh)
BUILD_FLAGS="-O3 -std=c++17 -DMPI_COMMS -DMULTI_GPU -DQUDA_PRECISION=12 -DQUDA_RECONSTRUCT=4"
call_dir=$(pwd -P)
script_dir="$(dirname "$(readlink -f "${BASH_SOURCE:-$0}")")"
cd "${env_dir}"
env_dir=$(pwd -P)
cd "${call_dir}"
BUILD_DIR="${env_dir}/build/Quda-benchmarks"
PREFIX_DIR="${env_dir}/prefix/qudabench"
QUDA_DIR=${env_dir}/prefix/quda
mkdir -p "${BUILD_DIR}"
mkdir -p "${PREFIX_DIR}"
LINK_FLAGS="-Wl,-rpath,$QUDA_DIR/lib: $QUDA_DIR/lib/libquda.so $EXTRA_LIBS -lpthread -lmpi"
g++ $BUILD_FLAGS -I$QUDA_DIR/include/targets/cuda -I$QUDA_DIR/include -c -o $BUILD_DIR/Benchmark_Quda.o $script_dir/Benchmark_Quda.cpp
g++ -g -O3 $BUILD_DIR/Benchmark_Quda.o -o $PREFIX_DIR/Benchmark_Quda $LINK_FLAGS -lmpi

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#!/usr/bin/env bash
# shellcheck disable=SC1090,SC1091
BUILD_FLAGS="-O3 -std=c++17"
QUDA_FLAGS="-DQUDA_MPI=ON -DQUDA_PRECISION=14 -DQUDA_RECONSTRUCT=4 -DQUDA_GPU_ARCH=sm_80"
set -euo pipefail
if (( $# != 1 )); then
echo "usage: $(basename "$0") <environment directory>" 1>&2
exit 1
fi
env_dir=$1
call_dir=$(pwd -P)
mkdir -p ${env_dir}
cd "${env_dir}"
env_dir=$(pwd -P)
cd "${call_dir}"
build_dir="${env_dir}/build/quda"
if [ -d "${build_dir}" ]; then
echo "error: directory '${build_dir}' exists"
exit 1
fi
mkdir -p "${build_dir}"
git clone https://github.com/lattice/quda.git "${build_dir}"
cd "${build_dir}"
mkdir build; cd build
cmake .. $QUDA_FLAGS -DCMAKE_INSTALL_PREFIX=${env_dir}/prefix/quda
make -j128
make install
cd "${call_dir}"

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module load gcc/9.3.0
module load cuda/11.4.1
module load openmpi/4.1.1-cuda11.4
export QUDA_RESOURCE_PATH=$(pwd)/tuning
export OMP_NUM_THREADS=4
export OMPI_MCA_btl=^uct,openib
export OMPI_MCA_pml=ucx # by fabian. no idea what this is
#export UCX_TLS=rc,rc_x,sm,cuda_copy,cuda_ipc,gdr_copy
export UCX_TLS=gdr_copy,rc,rc_x,sm,cuda_copy,cuda_ipc
export UCX_RNDV_THRESH=16384
export UCX_RNDV_SCHEME=put_zcopy
export UCX_IB_GPU_DIRECT_RDMA=yes
export UCX_MEMTYPE_CACHE=n
export OMPI_MCA_io=romio321
export OMPI_MCA_btl_openib_allow_ib=true
export OMPI_MCA_btl_openib_device_type=infiniband
export OMPI_MCA_btl_openib_if_exclude=mlx5_1,mlx5_2,mlx5_3
export QUDA_REORDER_LOCATION=GPU # this is the default anyway