benchmark-quda #3

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simon.buerger wants to merge 16 commits from simon.buerger/lattice-benchmarks:benchmark-quda into main
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@ -1,56 +1,58 @@
#include <algorithm> #include <algorithm>
#include <array> #include <array>
#include <blas_quda.h> #include <blas_quda.h>
#include <cassert>
#include <color_spinor_field.h> #include <color_spinor_field.h>
#include <mpi.h> #include <dirac_quda.h>
// #include <quda_internal.h> #include <gauge_tools.h>
#include <memory> #include <memory>
#include <mpi.h>
#include <stdio.h> #include <stdio.h>
#include <stdlib.h> #include <stdlib.h>
#include <cassert>
#include <dirac_quda.h>
#include <gauge_tools.h>
using namespace quda; using namespace quda;
QudaPrecision smoother_halo_prec = QUDA_INVALID_PRECISION; // This is the MPI grid, i.e. the layout of ranks
int nranks = -1;
std::array<int, 4> mpi_grid = {1, 1, 1, 1};
// This is the MPI grid, i.e. the layout of ranks, not the lattice volume void initComms(int argc, char **argv)
std::array<int, 4> gridsize = {1, 1, 1, 4};
void initComms(int argc, char **argv, std::array<int, 4> const &commDims)
{ {
// init MPI communication // init MPI communication
MPI_Init(&argc, &argv); 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 // this maps coordinates to rank number
auto lex_rank_from_coords = [](int const *coords, void *) auto lex_rank_from_coords = [](int const *coords, void *)
{ {
int rank = coords[0]; int rank = coords[0];
for (int i = 1; i < 4; i++) for (int i = 1; i < 4; i++)
rank = gridsize[i] * rank + coords[i]; rank = mpi_grid[i] * rank + coords[i];
return rank; return rank;
}; };
initCommsGridQuda(4, commDims.data(), lex_rank_from_coords, nullptr); initCommsGridQuda(4, mpi_grid.data(), lex_rank_from_coords, nullptr);
for (int d = 0; d < 4; d++) for (int d = 0; d < 4; d++)
if (gridsize[d] > 1) if (mpi_grid[d] > 1)
commDimPartitionedSet(d); commDimPartitionedSet(d);
} }
// creates a random gauge field // creates a random gauge field. L = local(!) size
cudaGaugeField make_gauge_field(std::array<int, 4> const &geom) cudaGaugeField make_gauge_field(int L)
{ {
GaugeFieldParam param; GaugeFieldParam param;
// dimension and type of the lattice object // dimension and type of the lattice object
param.nDim = 4; param.nDim = 4;
param.x[0] = geom[0]; param.x[0] = L;
param.x[1] = geom[1]; param.x[1] = L;
param.x[2] = geom[2]; param.x[2] = L;
param.x[3] = geom[3]; param.x[3] = L;
// number of colors. potentially confusingly, QUDA sometimes uses the word "color" to // 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 // things unrelated with physical color. things like "nColor=32" do pop up in deflation
@ -101,8 +103,8 @@ cudaGaugeField make_gauge_field(std::array<int, 4> const &geom)
return U; return U;
} }
// create a random source vector // create a random source vector (L = local size)
ColorSpinorField make_source(std::array<int, 4> const &geom) ColorSpinorField make_source(int L)
{ {
ColorSpinorParam param; ColorSpinorParam param;
param.nColor = 3; param.nColor = 3;
@ -111,10 +113,10 @@ ColorSpinorField make_source(std::array<int, 4> const &geom)
param.pad = 0; param.pad = 0;
param.siteSubset = QUDA_FULL_SITE_SUBSET; param.siteSubset = QUDA_FULL_SITE_SUBSET;
param.nDim = 4; param.nDim = 4;
param.x[0] = geom[0]; param.x[0] = L;
param.x[1] = geom[1]; param.x[1] = L;
param.x[2] = geom[2]; param.x[2] = L;
param.x[3] = geom[3]; param.x[3] = L;
param.x[4] = 1; // no fifth dimension param.x[4] = 1; // no fifth dimension
param.pc_type = QUDA_4D_PC; param.pc_type = QUDA_4D_PC;
param.siteOrder = QUDA_EVEN_ODD_SITE_ORDER; param.siteOrder = QUDA_EVEN_ODD_SITE_ORDER;
@ -136,20 +138,19 @@ ColorSpinorField make_source(std::array<int, 4> const &geom)
return src; return src;
} }
void benchmark(int L, int niter) void benchmark_wilson()
{ {
std::array<int, 4> geom = {L, L, L, L}; int niter = 20;
int niter_warmup = 10;
printfQuda("======================= benchmarking L=%d =======================\n", L); printfQuda("==================== wilson dirac operator ====================\n");
printfQuda("IMPORTANT: QUDAs own flop counting. Probably not the same as in Grid.\n");
printfQuda("%5s %15s %15s\n", "L", "time (usec)", "Gflop/s/rank");
auto U = make_gauge_field(geom); for (int L : {8, 12, 16, 24, 32})
printfQuda("created random gauge field, %.3f GiB (sanity check: should be %.3f)\n", {
U.Bytes() / 1024. / 1024. / 1024., auto U = make_gauge_field(L);
1.0 * L * L * L * L * 4 * 18 * 8 / 1024. / 1024. / 1024.); auto src = make_source(L);
auto src = make_source(geom);
printfQuda("created random source, %.3f GiB (sanity check: should be %.3f)\n",
src.Bytes() / 1024. / 1024. / 1024.,
1.0 * L * L * L * L * 12 * 2 * 8 / 1024. / 1024. / 1024.);
// create (Wilson) dirac operator // create (Wilson) dirac operator
DiracParam param; DiracParam param;
@ -165,15 +166,11 @@ void benchmark(int L, int niter)
auto tmp = ColorSpinorField(ColorSpinorParam(src)); auto tmp = ColorSpinorField(ColorSpinorParam(src));
printfQuda("benchmarking Dirac operator. geom=(%d,%d,%d,%d), niter=%d\n", geom[0],
geom[1], geom[2], geom[3], niter);
// couple iterations without timing to warm up // couple iterations without timing to warm up
printfQuda("warmup...\n"); for (int iter = 0; iter < niter_warmup; ++iter)
for (int iter = 0; iter < 20; ++iter)
dirac.M(tmp, src); dirac.M(tmp, src);
printfQuda("running...\n"); // actual benchmark with timings
dirac.Flops(); // reset flops counter dirac.Flops(); // reset flops counter
device_timer_t device_timer; device_timer_t device_timer;
device_timer.start(); device_timer.start();
@ -181,85 +178,111 @@ void benchmark(int L, int niter)
dirac.M(tmp, src); dirac.M(tmp, src);
device_timer.stop(); device_timer.stop();
double secs = device_timer.last(); double secs = device_timer.last() / niter;
double gflops = (dirac.Flops() * 1e-9) / secs; double flops = 1.0 * dirac.Flops() / niter;
printfQuda("Gflops = %6.2f\n", gflops);
printfQuda("%5d %15.2f %15.2f\n", L, secs * 1e6, flops / secs * 1e-9);
}
} }
void benchmark_axpy(int L) void benchmark_axpy()
{ {
printfQuda("================ axpy L=%d ==============\n", L); // number of iterations for warmup / measurement
// (feel free to change for noise/time tradeoff)
constexpr int niter_warmup = 10;
constexpr int niter = 20;
printfQuda("==================== axpy / memory ====================\n");
ColorSpinorParam param; ColorSpinorParam param;
param.nColor = 3; 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.nSpin = 4;
param.nVec = 1; param.nVec = 1; // just a single vector
param.pad = 0; param.siteSubset = QUDA_FULL_SITE_SUBSET; // full lattice = no odd/even
param.siteSubset = QUDA_FULL_SITE_SUBSET; param.pad = 0; // no padding
param.nDim = 4; 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_DOUBLE_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");
std::vector L_list = {8, 12, 16, 24, 32};
for (int L : L_list)
{
// IMPORTANT: all of `param.x`, `field_elements`, `field.Bytes()`
// are LOCAL, i.e. per rank / per GPU
param.x[0] = L; param.x[0] = L;
param.x[1] = L; param.x[1] = L;
param.x[2] = L; param.x[2] = L;
param.x[3] = L; param.x[3] = L;
param.x[4] = 1; // no fifth dimension
param.pc_type = QUDA_4D_PC;
param.siteOrder = QUDA_EVEN_ODD_SITE_ORDER;
param.gammaBasis = QUDA_DEGRAND_ROSSI_GAMMA_BASIS;
param.create = QUDA_NULL_FIELD_CREATE; // do not (zero-) initilize the field
param.setPrecision(QUDA_DOUBLE_PRECISION);
param.location = QUDA_CUDA_FIELD_LOCATION;
// create the field and fill it with random values // 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 fieldA = ColorSpinorField(param);
auto fieldB = ColorSpinorField(param); auto fieldB = ColorSpinorField(param);
assert(fieldA.Bytes() == sizeof(double) * field_elements); // sanity check
assert(fieldB.Bytes() == sizeof(double) * field_elements); // sanity check
// fill fields with random values
quda::RNG rng(fieldA, 1234); quda::RNG rng(fieldA, 1234);
auto size_bytes = size_t(8) * 2 * param.x[0] * param.x[1] * param.x[2] * param.x[3] *
param.nColor * param.nSpin;
assert(fieldA.Bytes() == size_bytes); // sanity check
assert(fieldB.Bytes() == size_bytes); // sanity check
spinorNoise(fieldA, rng, QUDA_NOISE_GAUSS); spinorNoise(fieldA, rng, QUDA_NOISE_GAUSS);
spinorNoise(fieldB, rng, QUDA_NOISE_GAUSS); spinorNoise(fieldB, rng, QUDA_NOISE_GAUSS);
// number of (real) elements in the field = number of fma instructions to do // number of operations / bytes per iteration
double flops_per_iter = // axpy is one addition, one multiplication, two read, one write
2 * param.x[0] * param.x[1] * param.x[2] * param.x[3] * param.nColor * param.nSpin; double flops = 2 * field_elements;
double memory = 3 * sizeof(double) * field_elements;
int niter = 20; // do some iterations to to let QUDA do its internal tuning and also stabilize cache
// behaviour and such
printfQuda("warmup...\n"); for (int iter = 0; iter < niter_warmup; ++iter)
for (int iter = 0; iter < 10; ++iter)
blas::axpy(1.234, fieldA, fieldB); blas::axpy(1.234, fieldA, fieldB);
printfQuda("running...\n"); // running the actual benchmark
device_timer_t device_timer; device_timer_t device_timer;
device_timer.start(); device_timer.start();
for (int iter = 0; iter < niter; ++iter) for (int iter = 0; iter < niter; ++iter)
blas::axpy(1.234, fieldA, fieldB); // fieldB += 1.234*fieldA blas::axpy(1.234, fieldA, fieldB);
device_timer.stop(); device_timer.stop();
double secs = device_timer.last() / niter; // seconds per iteration
double secs = device_timer.last(); printfQuda("%5d %15.2f %15.2f %15.2f %15.2f\n", L, memory / 1024. / 1024., secs * 1e6,
double gflops = (flops_per_iter * niter) * 1e-9 / secs; memory / secs / 1024. / 1024. / 1024., flops / secs * 1e-9);
printfQuda("Gflops = %6.2f\n", gflops); }
printfQuda("bytes = %6.2f GiB\n", 3. * fieldA.Bytes() / 1024. / 1024. / 1024.);
printfQuda("bandwidth = %6.2f GiB/s\n",
fieldA.Bytes() * 3 / 1024. / 1024. / 1024. * niter / secs);
} }
int main(int argc, char **argv) int main(int argc, char **argv)
{ {
initComms(argc, argv, gridsize); initComms(argc, argv);
initQuda(-1); // -1 for multi-gpu. otherwise this selects the device to be used initQuda(-1); // -1 for multi-gpu. otherwise this selects the device to be used
// verbosity options are: // verbosity options are:
// SILENT, SUMMARIZE, VERBOSE, DEBUG_VERBOSE // SILENT, SUMMARIZE, VERBOSE, DEBUG_VERBOSE
setVerbosity(QUDA_VERBOSE); setVerbosity(QUDA_SUMMARIZE);
for (int L : {8, 12, 16, 24, 32}) printfQuda("MPI layout = %d %d %d %d\n", mpi_grid[0], mpi_grid[1], mpi_grid[2],
benchmark_axpy(L); mpi_grid[3]);
for (int L : {16, 24, 32, 48, 64})
benchmark(L, 100);
benchmark_axpy();
setVerbosity(QUDA_SILENT);
benchmark_wilson();
setVerbosity(QUDA_SUMMARIZE);
printfQuda("==================== done with all benchmarks ====================\n");
endQuda(); endQuda();
quda::comm_finalize(); quda::comm_finalize();
MPI_Finalize(); MPI_Finalize();