add DWF benchmark

Quda/.clang-format

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

Quda/Benchmark_Quda.cpp

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+#include <algorithm>
+#include <array>
+#include <blas_quda.h>
+#include <cassert>
+#include <color_spinor_field.h>
+#include <dirac_quda.h>
+#include <gauge_tools.h>
+#include <memory>
+#include <mpi.h>
+#include <stdio.h>
+#include <stdlib.h>
+
+using namespace quda;
+
+// remove to use QUDA's own flop counting instead of Grid's convention
+#define FLOP_COUNTING_GRID
+
+// This is the MPI grid, i.e. the layout of ranks
+int nranks = -1;
+std::array<int, 4> mpi_grid = {1, 1, 1, 1};
+
+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);
+}
+
+// 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()
+{
+  int niter = 20;
+  int niter_warmup = 10;
+
+  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 : {8, 12, 16, 24, 32, 48})
+  {
+    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 tmp = ColorSpinorField(ColorSpinorParam(src));
+
+    // couple iterations without timing to warm up
+    for (int iter = 0; iter < niter_warmup; ++iter)
+      dirac.Dslash(tmp, src, QUDA_EVEN_PARITY);
+
+    // actual benchmark with timings
+    dirac.Flops(); // reset flops counter
+    device_timer_t device_timer;
+    device_timer.start();
+    for (int iter = 0; iter < niter; ++iter)
+      dirac.Dslash(tmp, src, QUDA_EVEN_PARITY);
+    device_timer.stop();
+
+    double secs = device_timer.last() / niter;
+
+#ifdef FLOP_COUNTING_GRID
+    // this is the flop counting from Benchmark_Grid
+    double Nc = 3;
+    double Nd = 4;
+    double Ns = 4;
+    double flops =
+        (Nc * (6 + (Nc - 1) * 8) * Ns * Nd + 2 * Nd * Nc * Ns + 2 * Nd * Nc * Ns * 2);
+    flops *= L * L * L * L / 2.0;
+#else
+    double flops = 1.0 * dirac.Flops() / niter;
+#endif
+
+    printfQuda("%5d %15.2f %15.2f\n", L, secs * 1e6, flops / secs * 1e-9);
+  }
+}
+
+void benchmark_dwf()
+{
+  int niter = 20;
+  int niter_warmup = 10;
+
+  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 : {8, 12, 16, 24, 32, 48})
+  {
+    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 tmp = ColorSpinorField(ColorSpinorParam(src));
+
+    // couple iterations without timing to warm up
+    for (int iter = 0; iter < niter_warmup; ++iter)
+      dirac.Dslash(tmp, src, QUDA_EVEN_PARITY);
+
+    // actual benchmark with timings
+    dirac.Flops(); // reset flops counter
+    device_timer_t device_timer;
+    device_timer.start();
+    for (int iter = 0; iter < niter; ++iter)
+      dirac.Dslash(tmp, src, QUDA_EVEN_PARITY);
+    device_timer.stop();
+
+    double secs = device_timer.last() / niter;
+
+#ifdef FLOP_COUNTING_GRID
+    // this is the flop counting from Benchmark_Grid
+    double Nc = 3;
+    double Nd = 4;
+    double Ns = 4;
+    double 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;
+#else
+    double flops = 1.0 * dirac.Flops() / niter;
+#endif
+
+    printfQuda("%5d %15.2f %15.2f\n", L, secs * 1e6, flops / secs * 1e-9);
+  }
+}
+
+void benchmark_axpy()
+{
+  // 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;
+  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");
+  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[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;
+
+    // do some iterations to to let QUDA do its internal tuning and also stabilize cache
+    // behaviour and such
+    for (int iter = 0; iter < niter_warmup; ++iter)
+      blas::axpy(1.234, fieldA, fieldB);
+
+    // running the actual benchmark
+    device_timer_t device_timer;
+    device_timer.start();
+    for (int iter = 0; iter < niter; ++iter)
+      blas::axpy(1.234, fieldA, fieldB);
+    device_timer.stop();
+    double secs = device_timer.last() / niter; // seconds per iteration
+
+    printfQuda("%5d %15.2f %15.2f %15.2f %15.2f\n", L, memory / 1024. / 1024., secs * 1e6,
+               memory / secs / 1024. / 1024. / 1024., flops / secs * 1e-9);
+  }
+}
+
+int main(int argc, char **argv)
+{
+  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();
+
+  setVerbosity(QUDA_SILENT);
+  benchmark_wilson();
+  benchmark_dwf();
+  setVerbosity(QUDA_SUMMARIZE);
+
+  printfQuda("==================== done with all benchmarks ====================\n");
+  endQuda();
+  quda::comm_finalize();
+  MPI_Finalize();
+}

Quda/build.sh

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+#!/bin/bash
+#CXX=/home/dp207/dp207/shared/env/versions/220428/spack/opt/spack/linux-rhel8-zen/gcc-8.4.1/gcc-9.4.0-g3vyv3te4ah634euh7phyokb3fiurprp/bin/g++
+QUDA_BUILD=/home/dp207/dp207/dc-burg2/quda_build
+QUDA_SRC=/home/dp207/dp207/dc-burg2/quda
+#QUDA_BUILD=
+
+FLAGS="-DMPI_COMMS -DMULTI_GPU -DQUDA_PRECISION=14 -DQUDA_RECONSTRUCT=7 -g -O3 -Wall -Wextra -std=c++17 "
+$CXX $FLAGS -I$QUDA_BUILD/include/targets/cuda -I$QUDA_SRC/include -I$QUDA_BUILD/include -isystem $QUDA_SRC/include/externals -isystem $QUDA_BUILD/_deps/eigen-src -c -o Benchmark_Quda.o  Benchmark_Quda.cpp
+LINK_FLAGS="-Wl,-rpath,$QUDA_BUILD/tests:$QUDA_BUILD/lib:/home/dp207/dp207/shared/env/versions/220428/spack/opt/spack/linux-rhel8-zen2/gcc-9.4.0/cuda-11.4.0-etxow4jb23qdbs7j6txczy44cdatpj22/lib64/stubs: $QUDA_BUILD/lib/libquda.so /home/dp207/dp207/shared/env/versions/220428/spack/opt/spack/linux-rhel8-zen2/gcc-9.4.0/cuda-11.4.0-etxow4jb23qdbs7j6txczy44cdatpj22/lib64/stubs/libcuda.so /home/dp207/dp207/shared/env/versions/220428/spack/opt/spack/linux-rhel8-zen2/gcc-9.4.0/cuda-11.4.0-etxow4jb23qdbs7j6txczy44cdatpj22/lib64/stubs/libnvidia-ml.so /home/dp207/dp207/shared/env/versions/220428/spack/opt/spack/linux-rhel8-zen2/gcc-9.4.0/cuda-11.4.0-etxow4jb23qdbs7j6txczy44cdatpj22/lib64/libcudart_static.a -ldl /usr/lib64/librt.so /home/dp207/dp207/shared/env/versions/220428/spack/opt/spack/linux-rhel8-zen2/gcc-9.4.0/cuda-11.4.0-etxow4jb23qdbs7j6txczy44cdatpj22/lib64/libcublas.so /home/dp207/dp207/shared/env/versions/220428/spack/opt/spack/linux-rhel8-zen2/gcc-9.4.0/cuda-11.4.0-etxow4jb23qdbs7j6txczy44cdatpj22/lib64/libcufft.so -lpthread"
+$CXX -g -O3 Benchmark_Quda.o -o Benchmark_Quda $LINK_FLAGS -lmpi

Quda/env.sh

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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