|  | #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); |