mirror of
https://gitlab.com/libeigen/eigen.git
synced 2024-12-21 07:19:46 +08:00
d3e81db6c5
This commit applies the following changes:
- Moving the `scamLauncher` specialization inside internal namespace to fix compiler crash on TensorScan for SYCL backend.
- Replacing `SYCL/sycl.hpp` to `CL/sycl.hpp` in order to follow SYCL 1.2.1 standard.
- minor fixes: commenting out an unused variable to avoid compiler warnings.
141 lines
6.1 KiB
C++
141 lines
6.1 KiB
C++
#ifdef EIGEN_USE_SYCL
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#include <CL/sycl.hpp>
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#include <iostream>
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#include "tensor_benchmarks.h"
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cl::sycl::gpu_selector selector;
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Eigen::QueueInterface queue(selector);
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#define BM_FuncWithInput2DimsGPU(FUNC, D1, D2) \
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static void BM_##FUNC##_##D1##x##D2(int iters, int N) { \
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StopBenchmarkTiming(); \
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Eigen::SyclDevice device(&queue); \
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BenchmarkSuite<Eigen::SyclDevice, float> suite(device, D1, D2); \
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suite.FUNC(iters); \
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} \
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BENCHMARK_RANGE(BM_##FUNC##_##D1##x##D2, 10, 10);
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BM_FuncWithInput2DimsGPU(rowReduction, 256, 100352);
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BM_FuncWithInput2DimsGPU(rowReduction, 64, 100352);
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BM_FuncWithInput2DimsGPU(rowReduction, 512, 25088);
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BM_FuncWithInput2DimsGPU(rowReduction, 128, 25088);
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BM_FuncWithInput2DimsGPU(rowReduction, 102, 6272);
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BM_FuncWithInput2DimsGPU(rowReduction, 256, 6272);
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BM_FuncWithInput2DimsGPU(rowReduction, 204, 1568);
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BM_FuncWithInput2DimsGPU(rowReduction, 512, 1568);
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BM_FuncWithInput2DimsGPU(rowReduction, 1024, 1568);
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BM_FuncWithInput2DimsGPU(rowReduction, 2048, 1568);
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BM_FuncWithInput2DimsGPU(colReduction, 100352, 256);
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BM_FuncWithInput2DimsGPU(colReduction, 100352, 64);
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BM_FuncWithInput2DimsGPU(colReduction, 25088, 512);
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BM_FuncWithInput2DimsGPU(colReduction, 6272, 102);
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BM_FuncWithInput2DimsGPU(colReduction, 25088, 128);
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BM_FuncWithInput2DimsGPU(colReduction, 6272, 256);
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BM_FuncWithInput2DimsGPU(colReduction, 1568, 204);
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BM_FuncWithInput2DimsGPU(colReduction, 1568, 512);
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BM_FuncWithInput2DimsGPU(colReduction, 1568, 1024);
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BM_FuncWithInput2DimsGPU(colReduction, 1568, 2048);
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BM_FuncWithInput2DimsGPU(fullReduction, 1001, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 2050048, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 2097152, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 2048, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 262144, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 256, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 589824, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 1024, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 524288, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 512, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 2359296, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 1048576, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 131072, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 16384, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 9408, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 64, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 4096, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 36864, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 32768, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 128, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 147456, 1);
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BM_FuncWithInput2DimsGPU(fullReduction, 65536, 1);
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#define BM_FuncGPU(FUNC) \
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static void BM_##FUNC(int iters, int N) { \
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StopBenchmarkTiming(); \
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Eigen::SyclDevice device(&queue); \
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BenchmarkSuite<Eigen::SyclDevice, float> suite(device, N); \
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suite.FUNC(iters); \
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} \
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BENCHMARK_RANGE(BM_##FUNC, 10, 5000);
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BM_FuncGPU(rowReduction);
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BM_FuncGPU(colReduction);
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BM_FuncGPU(fullReduction);
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BM_FuncGPU(memcpy);
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BM_FuncGPU(typeCasting);
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BM_FuncGPU(random);
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BM_FuncGPU(slicing);
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BM_FuncGPU(rowChip);
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BM_FuncGPU(colChip);
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BM_FuncGPU(shuffling);
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BM_FuncGPU(padding);
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BM_FuncGPU(striding);
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BM_FuncGPU(broadcasting);
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BM_FuncGPU(coeffWiseOp);
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BM_FuncGPU(algebraicFunc);
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BM_FuncGPU(transcendentalFunc);
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// Contractions
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#define BM_FuncWithInputDimsGPU(FUNC, D1, D2, D3) \
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static void BM_##FUNC##_##D1##x##D2##x##D3(int iters, int N) { \
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StopBenchmarkTiming(); \
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Eigen::SyclDevice device(&queue); \
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BenchmarkSuite<Eigen::SyclDevice, float> suite(device, D1, D2, D3); \
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suite.FUNC(iters); \
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} \
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BENCHMARK_RANGE(BM_##FUNC##_##D1##x##D2##x##D3, 10, 5000);
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BM_FuncWithInputDimsGPU(contraction, N, N, N);
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BM_FuncWithInputDimsGPU(contraction, 64, N, N);
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BM_FuncWithInputDimsGPU(contraction, N, 64, N);
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BM_FuncWithInputDimsGPU(contraction, N, N, 64);
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BM_FuncWithInputDimsGPU(contractionRowMajor, N, N, N);
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BM_FuncWithInputDimsGPU(contractionRowMajor, 64, N, N);
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BM_FuncWithInputDimsGPU(contractionRowMajor, N, 64, N);
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BM_FuncWithInputDimsGPU(contractionRowMajor, N, N, 64);
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BM_FuncWithInputDimsGPU(contractionRowMajorAT, N, N, N);
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BM_FuncWithInputDimsGPU(contractionRowMajorAT, 64, N, N);
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BM_FuncWithInputDimsGPU(contractionRowMajorAT, N, 64, N);
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BM_FuncWithInputDimsGPU(contractionRowMajorAT, N, N, 64);
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BM_FuncWithInputDimsGPU(contractionRowMajorBT, N, N, N);
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BM_FuncWithInputDimsGPU(contractionRowMajorBT, 64, N, N);
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BM_FuncWithInputDimsGPU(contractionRowMajorBT, N, 64, N);
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BM_FuncWithInputDimsGPU(contractionRowMajorBT, N, N, 64);
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BM_FuncWithInputDimsGPU(contractionRowMajorABT, N, N, N);
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BM_FuncWithInputDimsGPU(contractionRowMajorABT, 64, N, N);
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BM_FuncWithInputDimsGPU(contractionRowMajorABT, N, 64, N);
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BM_FuncWithInputDimsGPU(contractionRowMajorABT, N, N, 64);
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// Convolutions
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#define BM_FuncWithKernelDimsGPU(FUNC, DIM1, DIM2) \
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static void BM_##FUNC##_##DIM1##x##DIM2(int iters, int N) { \
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StopBenchmarkTiming(); \
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Eigen::SyclDevice device(&queue); \
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BenchmarkSuite<Eigen::SyclDevice, float> suite(device, N); \
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suite.FUNC(iters, DIM1, DIM2); \
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} \
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BENCHMARK_RANGE(BM_##FUNC##_##DIM1##x##DIM2, 128, 5000);
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BM_FuncWithKernelDimsGPU(convolution, 7, 1);
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BM_FuncWithKernelDimsGPU(convolution, 1, 7);
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BM_FuncWithKernelDimsGPU(convolution, 7, 4);
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BM_FuncWithKernelDimsGPU(convolution, 4, 7);
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BM_FuncWithKernelDimsGPU(convolution, 7, 64);
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BM_FuncWithKernelDimsGPU(convolution, 64, 7);
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#endif
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