benchmark-quda #3
@ -12,6 +12,9 @@
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using namespace quda;
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using namespace quda;
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// remove to use QUDA's own flop counting instead of Grid's convention
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#define FLOP_COUNTING_GRID
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// This is the MPI grid, i.e. the layout of ranks
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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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int nranks = -1;
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std::array<int, 4> mpi_grid = {1, 1, 1, 1};
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std::array<int, 4> mpi_grid = {1, 1, 1, 1};
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@ -65,7 +68,7 @@ cudaGaugeField make_gauge_field(int L)
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// for this benchmark we only need "SINGLE" and/or "DOUBLE" precision. But smaller
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// for this benchmark we only need "SINGLE" and/or "DOUBLE" precision. But smaller
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// precisions are available in QUDA too
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// precisions are available in QUDA too
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param.setPrecision(QUDA_DOUBLE_PRECISION);
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param.setPrecision(QUDA_SINGLE_PRECISION);
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// no even/odd subset, we want a full lattice
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// no even/odd subset, we want a full lattice
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param.siteSubset = QUDA_FULL_SITE_SUBSET;
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param.siteSubset = QUDA_FULL_SITE_SUBSET;
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@ -104,7 +107,7 @@ cudaGaugeField make_gauge_field(int L)
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}
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}
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// create a random source vector (L = local size)
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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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ColorSpinorField make_source(int L, int Ls = 1)
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{
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{
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// NOTE: `param.x` directly determines the size of the (local, per rank) memory
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// NOTE: `param.x` directly determines the size of the (local, per rank) memory
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// allocation. Thus for checkerboarding, we have to specifly x=(L/2,L,L,L) to get a
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// allocation. Thus for checkerboarding, we have to specifly x=(L/2,L,L,L) to get a
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@ -116,12 +119,12 @@ ColorSpinorField make_source(int L)
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param.nVec = 1; // only a single vector
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param.nVec = 1; // only a single vector
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param.pad = 0;
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param.pad = 0;
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param.siteSubset = QUDA_PARITY_SITE_SUBSET;
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param.siteSubset = QUDA_PARITY_SITE_SUBSET;
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param.nDim = 4;
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param.nDim = Ls == 1 ? 4 : 5;
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param.x[0] = L / 2;
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param.x[0] = L / 2;
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param.x[1] = L;
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param.x[1] = L;
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param.x[2] = L;
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param.x[2] = L;
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param.x[3] = 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.x[4] = Ls;
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param.pc_type = QUDA_4D_PC;
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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.siteOrder = QUDA_EVEN_ODD_SITE_ORDER;
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@ -130,7 +133,7 @@ ColorSpinorField make_source(int L)
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param.gammaBasis = QUDA_UKQCD_GAMMA_BASIS;
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param.gammaBasis = QUDA_UKQCD_GAMMA_BASIS;
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param.create = QUDA_NULL_FIELD_CREATE; // do not (zero-) initilize the field
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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.setPrecision(QUDA_SINGLE_PRECISION);
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param.location = QUDA_CUDA_FIELD_LOCATION;
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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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// create the field and fill it with random values
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@ -152,10 +155,15 @@ void benchmark_wilson()
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int niter_warmup = 10;
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int niter_warmup = 10;
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printfQuda("==================== wilson dirac operator ====================\n");
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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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#ifdef FLOP_COUNTING_GRID
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printfQuda("IMPORTANT: flop counting as in Benchmark_Grid\n");
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#else
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printfQuda("IMPORTANT: flop counting by QUDA's own convention (different from "
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"Benchmark_Grid)\n");
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#endif
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printfQuda("%5s %15s %15s\n", "L", "time (usec)", "Gflop/s/rank");
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printfQuda("%5s %15s %15s\n", "L", "time (usec)", "Gflop/s/rank");
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for (int L : {8, 12, 16, 24, 32})
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for (int L : {8, 12, 16, 24, 32, 48})
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{
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{
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auto U = make_gauge_field(L);
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auto U = make_gauge_field(L);
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auto src = make_source(L);
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auto src = make_source(L);
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@ -187,7 +195,82 @@ void benchmark_wilson()
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device_timer.stop();
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device_timer.stop();
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double secs = device_timer.last() / niter;
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double secs = device_timer.last() / niter;
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#ifdef FLOP_COUNTING_GRID
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// this is the flop counting from Benchmark_Grid
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double Nc = 3;
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double Nd = 4;
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double Ns = 4;
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double flops =
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(Nc * (6 + (Nc - 1) * 8) * Ns * Nd + 2 * Nd * Nc * Ns + 2 * Nd * Nc * Ns * 2);
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flops *= L * L * L * L / 2.0;
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#else
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double flops = 1.0 * dirac.Flops() / niter;
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double flops = 1.0 * dirac.Flops() / niter;
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#endif
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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_dwf()
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{
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int niter = 20;
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int niter_warmup = 10;
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printfQuda("==================== domain wall dirac operator ====================\n");
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#ifdef FLOP_COUNTING_GRID
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printfQuda("IMPORTANT: flop counting as in Benchmark_Grid\n");
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#else
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printfQuda("IMPORTANT: flop counting by QUDA's own convention (different from "
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"Benchmark_Grid)\n");
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#endif
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printfQuda("%5s %15s %15s\n", "L", "time (usec)", "Gflop/s/rank");
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int Ls = 12;
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for (int L : {8, 12, 16, 24, 32, 48})
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{
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auto U = make_gauge_field(L);
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auto src = make_source(L, Ls);
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// create dirac operator
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DiracParam param;
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param.kappa = 0.10;
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param.Ls = Ls;
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param.m5 = 0.1;
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param.dagger = QUDA_DAG_NO;
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param.matpcType = QUDA_MATPC_EVEN_EVEN;
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auto dirac = DiracDomainWall(param);
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// insert gauge field into the dirac operator
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// (the additional nullptr's are for smeared links and fancy preconditioners and such)
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dirac.updateFields(&U, nullptr, nullptr, nullptr);
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auto tmp = ColorSpinorField(ColorSpinorParam(src));
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// couple iterations without timing to warm up
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for (int iter = 0; iter < niter_warmup; ++iter)
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dirac.Dslash(tmp, src, QUDA_EVEN_PARITY);
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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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for (int iter = 0; iter < niter; ++iter)
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dirac.Dslash(tmp, src, QUDA_EVEN_PARITY);
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device_timer.stop();
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double secs = device_timer.last() / niter;
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#ifdef FLOP_COUNTING_GRID
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// this is the flop counting from Benchmark_Grid
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double Nc = 3;
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double Nd = 4;
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double Ns = 4;
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double flops =
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(Nc * (6 + (Nc - 1) * 8) * Ns * Nd + 2 * Nd * Nc * Ns + 2 * Nd * Nc * Ns * 2);
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flops *= L * L * L * L * Ls / 2.0;
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#else
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double flops = 1.0 * dirac.Flops() / niter;
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#endif
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printfQuda("%5d %15.2f %15.2f\n", L, secs * 1e6, flops / secs * 1e-9);
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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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@ -213,7 +296,7 @@ void benchmark_axpy()
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param.pad = 0; // no padding
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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.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.location = QUDA_CUDA_FIELD_LOCATION; // field should reside on GPU
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param.setPrecision(QUDA_DOUBLE_PRECISION);
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param.setPrecision(QUDA_SINGLE_PRECISION);
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// the following dont matter for an axpy benchmark, but need to choose something
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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.pc_type = QUDA_4D_PC;
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@ -240,8 +323,8 @@ void benchmark_axpy()
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// create the field(s)
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// create the field(s)
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auto fieldA = ColorSpinorField(param);
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auto fieldA = ColorSpinorField(param);
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auto fieldB = 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(fieldA.Bytes() == sizeof(float) * field_elements); // sanity check
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assert(fieldB.Bytes() == sizeof(double) * field_elements); // sanity check
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assert(fieldB.Bytes() == sizeof(float) * field_elements); // sanity check
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// fill fields with random values
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// fill fields with random values
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quda::RNG rng(fieldA, 1234);
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quda::RNG rng(fieldA, 1234);
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@ -251,7 +334,7 @@ void benchmark_axpy()
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// number of operations / bytes per iteration
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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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// axpy is one addition, one multiplication, two read, one write
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double flops = 2 * field_elements;
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double flops = 2 * field_elements;
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double memory = 3 * sizeof(double) * field_elements;
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double memory = 3 * sizeof(float) * field_elements;
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// do some iterations to to let QUDA do its internal tuning and also stabilize cache
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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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// behaviour and such
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@ -288,6 +371,7 @@ int main(int argc, char **argv)
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setVerbosity(QUDA_SILENT);
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setVerbosity(QUDA_SILENT);
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benchmark_wilson();
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benchmark_wilson();
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benchmark_dwf();
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setVerbosity(QUDA_SUMMARIZE);
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setVerbosity(QUDA_SUMMARIZE);
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printfQuda("==================== done with all benchmarks ====================\n");
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printfQuda("==================== done with all benchmarks ====================\n");
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@ -2,6 +2,7 @@ module load gcc/9.3.0
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module load cuda/11.4.1
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module load cuda/11.4.1
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module load openmpi/4.1.1-cuda11.4
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module load openmpi/4.1.1-cuda11.4
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export QUDA_RESOURCE_PATH=$(pwd)/tuning
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export OMP_NUM_THREADS=4
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export OMP_NUM_THREADS=4
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export OMPI_MCA_btl=^uct,openib
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export OMPI_MCA_btl=^uct,openib
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export OMPI_MCA_pml=ucx # by fabian. no idea what this is
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export OMPI_MCA_pml=ucx # by fabian. no idea what this is
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