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https://gitlab.com/libeigen/eigen.git
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157 lines
6.0 KiB
C++
157 lines
6.0 KiB
C++
#define EIGEN_USE_THREADS
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#include "base/sysinfo.h"
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#include "strings/strcat.h"
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#include "third_party/eigen3/tensor_benchmarks.h"
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#include "thread/threadpool.h"
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#ifdef __ANDROID__
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#define CREATE_THREAD_POOL(threads) \
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Eigen::ThreadPoolDevice device(threads);
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#else
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#define CREATE_THREAD_POOL(threads) \
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ThreadPool tp(threads); \
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tp.StartWorkers(); \
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Eigen::ThreadPoolDevice device(&tp, threads);
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#endif
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// Simple functions
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#define BM_FuncCPU(FUNC, THREADS) \
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static void BM_##FUNC##_##THREADS##T(int iters, int N) { \
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StopBenchmarkTiming(); \
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CREATE_THREAD_POOL(THREADS); \
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BenchmarkSuite<Eigen::ThreadPoolDevice> suite(device, N); \
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suite.FUNC(iters); \
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SetBenchmarkLabel(StrCat("using ", THREADS, " threads")); \
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} \
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BENCHMARK_RANGE(BM_##FUNC##_##THREADS##T, 10, 5000);
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BM_FuncCPU(memcpy, 4);
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BM_FuncCPU(memcpy, 8);
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BM_FuncCPU(memcpy, 12);
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BM_FuncCPU(random, 4);
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BM_FuncCPU(random, 8);
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BM_FuncCPU(random, 12);
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BM_FuncCPU(slicing, 4);
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BM_FuncCPU(slicing, 8);
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BM_FuncCPU(slicing, 12);
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BM_FuncCPU(shuffling, 4);
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BM_FuncCPU(shuffling, 8);
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BM_FuncCPU(shuffling, 12);
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BM_FuncCPU(padding, 4);
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BM_FuncCPU(padding, 8);
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BM_FuncCPU(padding, 12);
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BM_FuncCPU(striding, 4);
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BM_FuncCPU(striding, 8);
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BM_FuncCPU(striding, 12);
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BM_FuncCPU(broadcasting, 4);
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BM_FuncCPU(broadcasting, 8);
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BM_FuncCPU(broadcasting, 12);
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BM_FuncCPU(coeffWiseOp, 4);
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BM_FuncCPU(coeffWiseOp, 8);
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BM_FuncCPU(coeffWiseOp, 12);
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BM_FuncCPU(algebraicFunc, 4);
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BM_FuncCPU(algebraicFunc, 8);
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BM_FuncCPU(algebraicFunc, 12);
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BM_FuncCPU(transcendentalFunc, 4);
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BM_FuncCPU(transcendentalFunc, 8);
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BM_FuncCPU(transcendentalFunc, 12);
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BM_FuncCPU(reduction, 4);
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BM_FuncCPU(reduction, 8);
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BM_FuncCPU(reduction, 12);
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// Contractions
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#define BM_FuncWithInputDimsCPU(FUNC, D1, D2, D3, THREADS) \
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static void BM_##FUNC##_##D1##x##D2##x##D3##_##THREADS##T(int iters, int N) {\
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StopBenchmarkTiming(); \
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if (THREADS == 1) { \
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Eigen::DefaultDevice device; \
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BenchmarkSuite<Eigen::DefaultDevice> suite(device, D1, D2, D3); \
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suite.FUNC(iters); \
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} else { \
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CREATE_THREAD_POOL(THREADS); \
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BenchmarkSuite<Eigen::ThreadPoolDevice> suite(device, D1, D2, D3); \
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suite.FUNC(iters); \
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} \
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SetBenchmarkLabel(StrCat("using ", THREADS, " threads")); \
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} \
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BENCHMARK_RANGE(BM_##FUNC##_##D1##x##D2##x##D3##_##THREADS##T, 10, 5000);
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BM_FuncWithInputDimsCPU(contraction, N, N, N, 1);
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BM_FuncWithInputDimsCPU(contraction, N, N, N, 4);
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BM_FuncWithInputDimsCPU(contraction, N, N, N, 8);
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BM_FuncWithInputDimsCPU(contraction, N, N, N, 12);
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BM_FuncWithInputDimsCPU(contraction, N, N, N, 16);
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BM_FuncWithInputDimsCPU(contraction, 64, N, N, 1);
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BM_FuncWithInputDimsCPU(contraction, 64, N, N, 4);
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BM_FuncWithInputDimsCPU(contraction, 64, N, N, 8);
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BM_FuncWithInputDimsCPU(contraction, 64, N, N, 12);
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BM_FuncWithInputDimsCPU(contraction, 64, N, N, 16);
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BM_FuncWithInputDimsCPU(contraction, N, 64, N, 1);
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BM_FuncWithInputDimsCPU(contraction, N, 64, N, 4);
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BM_FuncWithInputDimsCPU(contraction, N, 64, N, 8);
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BM_FuncWithInputDimsCPU(contraction, N, 64, N, 12);
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BM_FuncWithInputDimsCPU(contraction, N, 64, N, 16);
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BM_FuncWithInputDimsCPU(contraction, 1, N, N, 1);
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BM_FuncWithInputDimsCPU(contraction, 1, N, N, 4);
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BM_FuncWithInputDimsCPU(contraction, 1, N, N, 8);
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BM_FuncWithInputDimsCPU(contraction, 1, N, N, 12);
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BM_FuncWithInputDimsCPU(contraction, 1, N, N, 16);
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BM_FuncWithInputDimsCPU(contraction, N, N, 1, 1);
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BM_FuncWithInputDimsCPU(contraction, N, N, 1, 4);
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BM_FuncWithInputDimsCPU(contraction, N, N, 1, 8);
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BM_FuncWithInputDimsCPU(contraction, N, N, 1, 12);
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BM_FuncWithInputDimsCPU(contraction, N, N, 1, 16);
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// Convolutions
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#define BM_FuncWithKernelDimsCPU(FUNC, DIM1, DIM2, THREADS) \
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static void BM_##FUNC##_##DIM1##x##DIM2##_##THREADS##T(int iters, int N) { \
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StopBenchmarkTiming(); \
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CREATE_THREAD_POOL(THREADS); \
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BenchmarkSuite<Eigen::ThreadPoolDevice> suite(device, N); \
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suite.FUNC(iters, DIM1, DIM2); \
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SetBenchmarkLabel(StrCat("using ", THREADS, " threads")); \
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} \
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BENCHMARK_RANGE(BM_##FUNC##_##DIM1##x##DIM2##_##THREADS##T, 128, 5000);
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BM_FuncWithKernelDimsCPU(convolution, 7, 1, 4);
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BM_FuncWithKernelDimsCPU(convolution, 7, 1, 8);
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BM_FuncWithKernelDimsCPU(convolution, 7, 1, 12);
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BM_FuncWithKernelDimsCPU(convolution, 1, 7, 4);
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BM_FuncWithKernelDimsCPU(convolution, 1, 7, 8);
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BM_FuncWithKernelDimsCPU(convolution, 1, 7, 12);
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BM_FuncWithKernelDimsCPU(convolution, 7, 4, 4);
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BM_FuncWithKernelDimsCPU(convolution, 7, 4, 8);
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BM_FuncWithKernelDimsCPU(convolution, 7, 4, 12);
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BM_FuncWithKernelDimsCPU(convolution, 4, 7, 4);
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BM_FuncWithKernelDimsCPU(convolution, 4, 7, 8);
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BM_FuncWithKernelDimsCPU(convolution, 4, 7, 12);
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BM_FuncWithKernelDimsCPU(convolution, 7, 64, 4);
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BM_FuncWithKernelDimsCPU(convolution, 7, 64, 8);
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BM_FuncWithKernelDimsCPU(convolution, 7, 64, 12);
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BM_FuncWithKernelDimsCPU(convolution, 64, 7, 4);
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BM_FuncWithKernelDimsCPU(convolution, 64, 7, 8);
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BM_FuncWithKernelDimsCPU(convolution, 64, 7, 12);
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