Quelle tensor_benchmarks_cpu.cc Sprache: C

#define EIGEN_USE_THREADS

#include <string>

#include "tensor_benchmarks.h"

#define CREATE_THREAD_POOL(threads)             \
Eigen::ThreadPool pool(threads);                \
Eigen::ThreadPoolDevice device(&pool, threads);

// Simple functions
#define BM_FuncCPU(FUNC, THREADS)                                    \
  static void BM_##FUNC##_##THREADS##T(int iters, int N) {           \
    StopBenchmarkTiming();                                           \
    CREATE_THREAD_POOL(THREADS);                                     \
    BenchmarkSuite<Eigen::ThreadPoolDevice, float> suite(device, N); \
    suite.FUNC(iters);                                               \
  }                                                                  \
  BENCHMARK_RANGE(BM_##FUNC##_##THREADS##T, 10, 5000);

BM_FuncCPU(memcpy, 4);
BM_FuncCPU(memcpy, 8);
BM_FuncCPU(memcpy, 12);

BM_FuncCPU(typeCasting, 4);
BM_FuncCPU(typeCasting, 8);
BM_FuncCPU(typeCasting, 12);

BM_FuncCPU(random, 4);
BM_FuncCPU(random, 8);
BM_FuncCPU(random, 12);

BM_FuncCPU(slicing, 4);
BM_FuncCPU(slicing, 8);
BM_FuncCPU(slicing, 12);

BM_FuncCPU(rowChip, 4);
BM_FuncCPU(rowChip, 8);
BM_FuncCPU(rowChip, 12);

BM_FuncCPU(colChip, 4);
BM_FuncCPU(colChip, 8);
BM_FuncCPU(colChip, 12);

BM_FuncCPU(shuffling, 4);
BM_FuncCPU(shuffling, 8);
BM_FuncCPU(shuffling, 12);

BM_FuncCPU(padding, 4);
BM_FuncCPU(padding, 8);
BM_FuncCPU(padding, 12);

BM_FuncCPU(striding, 4);
BM_FuncCPU(striding, 8);
BM_FuncCPU(striding, 12);

BM_FuncCPU(broadcasting, 4);
BM_FuncCPU(broadcasting, 8);
BM_FuncCPU(broadcasting, 12);

BM_FuncCPU(coeffWiseOp, 4);
BM_FuncCPU(coeffWiseOp, 8);
BM_FuncCPU(coeffWiseOp, 12);

BM_FuncCPU(algebraicFunc, 4);
BM_FuncCPU(algebraicFunc, 8);
BM_FuncCPU(algebraicFunc, 12);

BM_FuncCPU(transcendentalFunc, 4);
BM_FuncCPU(transcendentalFunc, 8);
BM_FuncCPU(transcendentalFunc, 12);

BM_FuncCPU(rowReduction, 4);
BM_FuncCPU(rowReduction, 8);
BM_FuncCPU(rowReduction, 12);

BM_FuncCPU(colReduction, 4);
BM_FuncCPU(colReduction, 8);
BM_FuncCPU(colReduction, 12);

// Contractions
#define BM_FuncWithInputDimsCPU(FUNC, D1, D2, D3, THREADS)                      \
  static void BM_##FUNC##_##D1##x##D2##x##D3##_##THREADS##T(int iters, int N) { \
    StopBenchmarkTiming();                                                      \
    if (THREADS == 1) {                                                         \
      Eigen::DefaultDevice device;                                              \
      BenchmarkSuite<Eigen::DefaultDevice, float> suite(device, D1, D2, D3);    \
      suite.FUNC(iters);                                                        \
    } else {                                                                    \
      CREATE_THREAD_POOL(THREADS);                                              \
      BenchmarkSuite<Eigen::ThreadPoolDevice, float> suite(device, D1, D2, D3); \
      suite.FUNC(iters);                                                        \
    }                                                                           \
  }                                                                             \
  BENCHMARK_RANGE(BM_##FUNC##_##D1##x##D2##x##D3##_##THREADS##T, 10, 5000);

BM_FuncWithInputDimsCPU(contraction, N, N, N, 1);
BM_FuncWithInputDimsCPU(contraction, N, N, N, 4);
BM_FuncWithInputDimsCPU(contraction, N, N, N, 8);
BM_FuncWithInputDimsCPU(contraction, N, N, N, 12);
BM_FuncWithInputDimsCPU(contraction, N, N, N, 16);

BM_FuncWithInputDimsCPU(contraction, 64, N, N, 1);
BM_FuncWithInputDimsCPU(contraction, 64, N, N, 4);
BM_FuncWithInputDimsCPU(contraction, 64, N, N, 8);
BM_FuncWithInputDimsCPU(contraction, 64, N, N, 12);
BM_FuncWithInputDimsCPU(contraction, 64, N, N, 16);

BM_FuncWithInputDimsCPU(contraction, N, 64, N, 1);
BM_FuncWithInputDimsCPU(contraction, N, 64, N, 4);
BM_FuncWithInputDimsCPU(contraction, N, 64, N, 8);
BM_FuncWithInputDimsCPU(contraction, N, 64, N, 12);
BM_FuncWithInputDimsCPU(contraction, N, 64, N, 16);

BM_FuncWithInputDimsCPU(contraction, N, N, 64, 1);
BM_FuncWithInputDimsCPU(contraction, N, N, 64, 4);
BM_FuncWithInputDimsCPU(contraction, N, N, 64, 8);
BM_FuncWithInputDimsCPU(contraction, N, N, 64, 12);
BM_FuncWithInputDimsCPU(contraction, N, N, 64, 16);

BM_FuncWithInputDimsCPU(contraction, 1, N, N, 1);
BM_FuncWithInputDimsCPU(contraction, 1, N, N, 4);
BM_FuncWithInputDimsCPU(contraction, 1, N, N, 8);
BM_FuncWithInputDimsCPU(contraction, 1, N, N, 12);
BM_FuncWithInputDimsCPU(contraction, 1, N, N, 16);

BM_FuncWithInputDimsCPU(contraction, N, N, 1, 1);
BM_FuncWithInputDimsCPU(contraction, N, N, 1, 4);
BM_FuncWithInputDimsCPU(contraction, N, N, 1, 8);
BM_FuncWithInputDimsCPU(contraction, N, N, 1, 12);
BM_FuncWithInputDimsCPU(contraction, N, N, 1, 16);

// Convolutions
#define BM_FuncWithKernelDimsCPU(FUNC, DIM1, DIM2, THREADS)                    \
  static void BM_##FUNC##_##DIM1##x##DIM2##_##THREADS##T(int iters, int N) {   \
    StopBenchmarkTiming();                                                     \
    CREATE_THREAD_POOL(THREADS);                                               \
    BenchmarkSuite<Eigen::ThreadPoolDevice, float> suite(device, N);        \
    suite.FUNC(iters, DIM1, DIM2);                                             \
  }                                                                            \
  BENCHMARK_RANGE(BM_##FUNC##_##DIM1##x##DIM2##_##THREADS##T, 128, 5000);

BM_FuncWithKernelDimsCPU(convolution, 7, 1, 4);
BM_FuncWithKernelDimsCPU(convolution, 7, 1, 8);
BM_FuncWithKernelDimsCPU(convolution, 7, 1, 12);

BM_FuncWithKernelDimsCPU(convolution, 1, 7, 4);
BM_FuncWithKernelDimsCPU(convolution, 1, 7, 8);
BM_FuncWithKernelDimsCPU(convolution, 1, 7, 12);

BM_FuncWithKernelDimsCPU(convolution, 7, 4, 4);
BM_FuncWithKernelDimsCPU(convolution, 7, 4, 8);
BM_FuncWithKernelDimsCPU(convolution, 7, 4, 12);

BM_FuncWithKernelDimsCPU(convolution, 4, 7, 4);
BM_FuncWithKernelDimsCPU(convolution, 4, 7, 8);
BM_FuncWithKernelDimsCPU(convolution, 4, 7, 12);

BM_FuncWithKernelDimsCPU(convolution, 7, 64, 4);
BM_FuncWithKernelDimsCPU(convolution, 7, 64, 8);
BM_FuncWithKernelDimsCPU(convolution, 7, 64, 12);

BM_FuncWithKernelDimsCPU(convolution, 64, 7, 4);
BM_FuncWithKernelDimsCPU(convolution, 64, 7, 8);
BM_FuncWithKernelDimsCPU(convolution, 64, 7, 12);

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