benchmark-quda #3
@ -1,56 +1,58 @@
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#include <algorithm>
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#include <array>
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#include <blas_quda.h>
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#include <cassert>
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#include <color_spinor_field.h>
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#include <mpi.h>
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// #include <quda_internal.h>
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#include <dirac_quda.h>
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#include <gauge_tools.h>
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#include <memory>
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#include <mpi.h>
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#include <stdio.h>
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#include <stdlib.h>
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#include <cassert>
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#include <dirac_quda.h>
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#include <gauge_tools.h>
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using namespace quda;
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QudaPrecision smoother_halo_prec = QUDA_INVALID_PRECISION;
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// This is the MPI grid, i.e. the layout of ranks
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int nranks = -1;
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std::array<int, 4> mpi_grid = {1, 1, 1, 1};
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// This is the MPI grid, i.e. the layout of ranks, not the lattice volume
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std::array<int, 4> gridsize = {1, 1, 1, 4};
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void initComms(int argc, char **argv, std::array<int, 4> const &commDims)
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void initComms(int argc, char **argv)
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{
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// init MPI communication
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MPI_Init(&argc, &argv);
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MPI_Comm_size(MPI_COMM_WORLD, &nranks);
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assert(1 <= nranks && nranks <= 100000);
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mpi_grid[3] = nranks;
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// this maps coordinates to rank number
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auto lex_rank_from_coords = [](int const *coords, void *)
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{
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int rank = coords[0];
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for (int i = 1; i < 4; i++)
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rank = gridsize[i] * rank + coords[i];
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rank = mpi_grid[i] * rank + coords[i];
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return rank;
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};
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initCommsGridQuda(4, commDims.data(), lex_rank_from_coords, nullptr);
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initCommsGridQuda(4, mpi_grid.data(), lex_rank_from_coords, nullptr);
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for (int d = 0; d < 4; d++)
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if (gridsize[d] > 1)
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if (mpi_grid[d] > 1)
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commDimPartitionedSet(d);
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}
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// creates a random gauge field
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cudaGaugeField make_gauge_field(std::array<int, 4> const &geom)
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// creates a random gauge field. L = local(!) size
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cudaGaugeField make_gauge_field(int L)
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{
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GaugeFieldParam param;
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// dimension and type of the lattice object
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param.nDim = 4;
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param.x[0] = geom[0];
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param.x[1] = geom[1];
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param.x[2] = geom[2];
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param.x[3] = geom[3];
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param.x[0] = L;
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param.x[1] = L;
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param.x[2] = L;
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param.x[3] = L;
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// number of colors. potentially confusingly, QUDA sometimes uses the word "color" to
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// things unrelated with physical color. things like "nColor=32" do pop up in deflation
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@ -101,8 +103,8 @@ cudaGaugeField make_gauge_field(std::array<int, 4> const &geom)
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return U;
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}
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// create a random source vector
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ColorSpinorField make_source(std::array<int, 4> const &geom)
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// create a random source vector (L = local size)
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ColorSpinorField make_source(int L)
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{
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ColorSpinorParam param;
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param.nColor = 3;
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@ -111,10 +113,10 @@ ColorSpinorField make_source(std::array<int, 4> const &geom)
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param.pad = 0;
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param.siteSubset = QUDA_FULL_SITE_SUBSET;
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param.nDim = 4;
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param.x[0] = geom[0];
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param.x[1] = geom[1];
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param.x[2] = geom[2];
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param.x[3] = geom[3];
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param.x[0] = L;
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param.x[1] = L;
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param.x[2] = L;
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param.x[3] = L;
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param.x[4] = 1; // no fifth dimension
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param.pc_type = QUDA_4D_PC;
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param.siteOrder = QUDA_EVEN_ODD_SITE_ORDER;
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@ -136,20 +138,19 @@ ColorSpinorField make_source(std::array<int, 4> const &geom)
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return src;
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}
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void benchmark(int L, int niter)
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void benchmark_wilson()
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{
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std::array<int, 4> geom = {L, L, L, L};
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int niter = 20;
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int niter_warmup = 10;
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printfQuda("======================= benchmarking L=%d =======================\n", L);
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printfQuda("==================== wilson dirac operator ====================\n");
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printfQuda("IMPORTANT: QUDAs own flop counting. Probably not the same as in Grid.\n");
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printfQuda("%5s %15s %15s\n", "L", "time (usec)", "Gflop/s/rank");
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auto U = make_gauge_field(geom);
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printfQuda("created random gauge field, %.3f GiB (sanity check: should be %.3f)\n",
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U.Bytes() / 1024. / 1024. / 1024.,
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1.0 * L * L * L * L * 4 * 18 * 8 / 1024. / 1024. / 1024.);
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auto src = make_source(geom);
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printfQuda("created random source, %.3f GiB (sanity check: should be %.3f)\n",
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src.Bytes() / 1024. / 1024. / 1024.,
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1.0 * L * L * L * L * 12 * 2 * 8 / 1024. / 1024. / 1024.);
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for (int L : {8, 12, 16, 24, 32})
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{
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auto U = make_gauge_field(L);
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auto src = make_source(L);
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// create (Wilson) dirac operator
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DiracParam param;
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@ -165,15 +166,11 @@ void benchmark(int L, int niter)
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auto tmp = ColorSpinorField(ColorSpinorParam(src));
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printfQuda("benchmarking Dirac operator. geom=(%d,%d,%d,%d), niter=%d\n", geom[0],
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geom[1], geom[2], geom[3], niter);
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// couple iterations without timing to warm up
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printfQuda("warmup...\n");
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for (int iter = 0; iter < 20; ++iter)
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for (int iter = 0; iter < niter_warmup; ++iter)
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dirac.M(tmp, src);
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printfQuda("running...\n");
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// actual benchmark with timings
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dirac.Flops(); // reset flops counter
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device_timer_t device_timer;
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device_timer.start();
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@ -181,85 +178,111 @@ void benchmark(int L, int niter)
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dirac.M(tmp, src);
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device_timer.stop();
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double secs = device_timer.last();
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double gflops = (dirac.Flops() * 1e-9) / secs;
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printfQuda("Gflops = %6.2f\n", gflops);
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double secs = device_timer.last() / niter;
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double flops = 1.0 * dirac.Flops() / niter;
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printfQuda("%5d %15.2f %15.2f\n", L, secs * 1e6, flops / secs * 1e-9);
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}
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}
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void benchmark_axpy(int L)
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void benchmark_axpy()
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{
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printfQuda("================ axpy L=%d ==============\n", L);
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// number of iterations for warmup / measurement
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// (feel free to change for noise/time tradeoff)
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constexpr int niter_warmup = 10;
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constexpr int niter = 20;
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printfQuda("==================== axpy / memory ====================\n");
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ColorSpinorParam param;
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param.nColor = 3;
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param.nDim = 4; // 4-dimensional lattice
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param.x[4] = 1; // no fifth dimension
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param.nColor = 3; // supported values for nSpin/nColor are configured when compiling
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// QUDA. "3*4" will probably always be enabled, so we stick with this
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param.nSpin = 4;
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param.nVec = 1;
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param.pad = 0;
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param.siteSubset = QUDA_FULL_SITE_SUBSET;
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param.nDim = 4;
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param.nVec = 1; // just a single vector
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param.siteSubset = QUDA_FULL_SITE_SUBSET; // full lattice = no odd/even
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param.pad = 0; // no padding
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param.create = QUDA_NULL_FIELD_CREATE; // do not (zero-) initilize the field
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param.location = QUDA_CUDA_FIELD_LOCATION; // field should reside on GPU
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param.setPrecision(QUDA_DOUBLE_PRECISION);
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// the following dont matter for an axpy benchmark, but need to choose something
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param.pc_type = QUDA_4D_PC;
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param.siteOrder = QUDA_EVEN_ODD_SITE_ORDER;
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param.gammaBasis = QUDA_DEGRAND_ROSSI_GAMMA_BASIS;
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printfQuda("%5s %15s %15s %15s %15s\n", "L", "size (MiB/rank)", "time (usec)",
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"GiB/s/rank", "Gflop/s/rank");
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std::vector L_list = {8, 12, 16, 24, 32};
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for (int L : L_list)
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{
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// IMPORTANT: all of `param.x`, `field_elements`, `field.Bytes()`
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// are LOCAL, i.e. per rank / per GPU
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param.x[0] = L;
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param.x[1] = L;
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param.x[2] = L;
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param.x[3] = L;
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param.x[4] = 1; // no fifth dimension
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param.pc_type = QUDA_4D_PC;
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param.siteOrder = QUDA_EVEN_ODD_SITE_ORDER;
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param.gammaBasis = QUDA_DEGRAND_ROSSI_GAMMA_BASIS;
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param.create = QUDA_NULL_FIELD_CREATE; // do not (zero-) initilize the field
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param.setPrecision(QUDA_DOUBLE_PRECISION);
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param.location = QUDA_CUDA_FIELD_LOCATION;
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// create the field and fill it with random values
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// number of (real) elements in one (local) field
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size_t field_elements = 2 * param.x[0] * param.x[1] * param.x[2] * param.x[3] *
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param.nColor * param.nSpin;
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// create the field(s)
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auto fieldA = ColorSpinorField(param);
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auto fieldB = ColorSpinorField(param);
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assert(fieldA.Bytes() == sizeof(double) * field_elements); // sanity check
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assert(fieldB.Bytes() == sizeof(double) * field_elements); // sanity check
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// fill fields with random values
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quda::RNG rng(fieldA, 1234);
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auto size_bytes = size_t(8) * 2 * param.x[0] * param.x[1] * param.x[2] * param.x[3] *
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param.nColor * param.nSpin;
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assert(fieldA.Bytes() == size_bytes); // sanity check
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assert(fieldB.Bytes() == size_bytes); // sanity check
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spinorNoise(fieldA, rng, QUDA_NOISE_GAUSS);
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spinorNoise(fieldB, rng, QUDA_NOISE_GAUSS);
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// number of (real) elements in the field = number of fma instructions to do
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double flops_per_iter =
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2 * param.x[0] * param.x[1] * param.x[2] * param.x[3] * param.nColor * param.nSpin;
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// number of operations / bytes per iteration
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// axpy is one addition, one multiplication, two read, one write
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double flops = 2 * field_elements;
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double memory = 3 * sizeof(double) * field_elements;
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int niter = 20;
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printfQuda("warmup...\n");
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for (int iter = 0; iter < 10; ++iter)
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// do some iterations to to let QUDA do its internal tuning and also stabilize cache
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// behaviour and such
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for (int iter = 0; iter < niter_warmup; ++iter)
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blas::axpy(1.234, fieldA, fieldB);
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printfQuda("running...\n");
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// running the actual benchmark
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device_timer_t device_timer;
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device_timer.start();
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for (int iter = 0; iter < niter; ++iter)
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blas::axpy(1.234, fieldA, fieldB); // fieldB += 1.234*fieldA
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blas::axpy(1.234, fieldA, fieldB);
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device_timer.stop();
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double secs = device_timer.last() / niter; // seconds per iteration
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double secs = device_timer.last();
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double gflops = (flops_per_iter * niter) * 1e-9 / secs;
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printfQuda("Gflops = %6.2f\n", gflops);
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printfQuda("bytes = %6.2f GiB\n", 3. * fieldA.Bytes() / 1024. / 1024. / 1024.);
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printfQuda("bandwidth = %6.2f GiB/s\n",
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fieldA.Bytes() * 3 / 1024. / 1024. / 1024. * niter / secs);
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printfQuda("%5d %15.2f %15.2f %15.2f %15.2f\n", L, memory / 1024. / 1024., secs * 1e6,
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memory / secs / 1024. / 1024. / 1024., flops / secs * 1e-9);
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}
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}
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int main(int argc, char **argv)
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{
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initComms(argc, argv, gridsize);
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initComms(argc, argv);
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initQuda(-1); // -1 for multi-gpu. otherwise this selects the device to be used
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// verbosity options are:
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// SILENT, SUMMARIZE, VERBOSE, DEBUG_VERBOSE
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setVerbosity(QUDA_VERBOSE);
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setVerbosity(QUDA_SUMMARIZE);
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for (int L : {8, 12, 16, 24, 32})
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benchmark_axpy(L);
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for (int L : {16, 24, 32, 48, 64})
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benchmark(L, 100);
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printfQuda("MPI layout = %d %d %d %d\n", mpi_grid[0], mpi_grid[1], mpi_grid[2],
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mpi_grid[3]);
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benchmark_axpy();
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setVerbosity(QUDA_SILENT);
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benchmark_wilson();
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setVerbosity(QUDA_SUMMARIZE);
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printfQuda("==================== done with all benchmarks ====================\n");
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endQuda();
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quda::comm_finalize();
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MPI_Finalize();
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