| // Copyright 2019 Google LLC |
| // |
| // This source code is licensed under the BSD-style license found in the |
| // LICENSE file in the root directory of this source tree. |
| |
| #include <algorithm> |
| #include <cfloat> |
| #include <cmath> |
| #include <functional> |
| #include <random> |
| #include <vector> |
| |
| #include <benchmark/benchmark.h> |
| #include <fp16/fp16.h> |
| |
| #include <xnnpack/AlignedAllocator.h> |
| #include <xnnpack/common.h> |
| #include <xnnpack/math-stubs.h> |
| |
| |
| static void ExpError(benchmark::State& state, |
| xnn_f32_unary_math_function exp, |
| size_t tile_size) |
| { |
| // The smallest x for which expf(x) is non-zero (-0x1.9FE368p+6f). |
| const uint32_t min_input = 0xC2CFF1B4; |
| // The largest x for which expf(x) is finite (0x1.62E42Ep6f). |
| const uint32_t max_input = 0x42B17217; |
| // Number of tiles in one block of inputs/outputs. Combining multiple tiles in a block reduce function call overhead. |
| const size_t num_tiles = 100; |
| |
| double max_ulp_error = 0.0; |
| std::vector<float, AlignedAllocator<float, 64>> x(tile_size * num_tiles); |
| std::vector<float, AlignedAllocator<float, 64>> y(tile_size * num_tiles); |
| for (auto _ : state) { |
| for (uint32_t n = min_input; int32_t(n) < 0; n -= tile_size * num_tiles) { |
| for (uint32_t i = 0; i < tile_size * num_tiles; i++) { |
| x[i] = fp32_from_bits(std::max<uint32_t>(n - i, 0x80000000)); |
| } |
| std::fill(y.begin(), y.end(), std::nanf("")); |
| |
| exp(tile_size * num_tiles * sizeof(float), x.data(), y.data()); |
| |
| for (uint32_t i = 0; i < tile_size * num_tiles; i++) { |
| const double y_ref = std::exp(double(x[i])); |
| const double abs_error = std::abs(y_ref - double(y[i])); |
| const float y_abs = std::abs(y_ref); |
| const float y_ulp = fp32_from_bits(fp32_to_bits(y_abs) + 1) - y_abs; |
| max_ulp_error = std::max<double>(max_ulp_error, abs_error / y_ulp); |
| } |
| } |
| for (uint32_t n = 0; n < max_input; n += tile_size * num_tiles) { |
| for (uint32_t i = 0; i < tile_size * num_tiles; i++) { |
| x[i] = fp32_from_bits(std::min<uint32_t>(n + i, max_input)); |
| } |
| std::fill(y.begin(), y.end(), std::nanf("")); |
| |
| exp(tile_size * num_tiles * sizeof(float), x.data(), y.data()); |
| |
| for (uint32_t i = 0; i < tile_size * num_tiles; i++) { |
| const double y_ref = std::exp(double(x[i])); |
| const double abs_error = std::abs(y_ref - double(y[i])); |
| const float y_abs = std::abs(y_ref); |
| const float y_ulp = fp32_from_bits(fp32_to_bits(y_abs) + 1) - y_abs; |
| max_ulp_error = std::max<double>(max_ulp_error, abs_error / y_ulp); |
| } |
| } |
| } |
| |
| state.counters["ULPERROR"] = benchmark::Counter(max_ulp_error); |
| } |
| |
| #if XNN_ARCH_X86 || XNN_ARCH_X86_64 |
| static void f32_exp__sse2_p5(benchmark::State& state) { |
| ExpError(state, xnn_math_f32_exp__sse2_p5, 4); |
| } |
| static void f32_exp__avx2_perm_p3(benchmark::State& state) { |
| ExpError(state, xnn_math_f32_exp__avx2_perm_p3, 8); |
| } |
| static void f32_exp__avx2_perm_p4(benchmark::State& state) { |
| ExpError(state, xnn_math_f32_exp__avx2_perm_p4, 8); |
| } |
| static void f32_exp__avx2_p5(benchmark::State& state) { |
| ExpError(state, xnn_math_f32_exp__avx2_p5, 8); |
| } |
| static void f32_exp__avx512f_perm2_p2(benchmark::State& state) { |
| ExpError(state, xnn_math_f32_exp__avx512f_perm2_p2, 16); |
| } |
| static void f32_exp__avx512f_perm_p3(benchmark::State& state) { |
| ExpError(state, xnn_math_f32_exp__avx512f_perm_p3, 16); |
| } |
| static void f32_exp__avx512f_p5_scalef(benchmark::State& state) { |
| ExpError(state, xnn_math_f32_exp__avx512f_p5_scalef, 16); |
| } |
| static void f32_exp__avx512f_p5(benchmark::State& state) { |
| ExpError(state, xnn_math_f32_exp__avx512f_p5, 16); |
| } |
| |
| BENCHMARK(f32_exp__sse2_p5)->Unit(benchmark::kMillisecond)->Iterations(1); |
| BENCHMARK(f32_exp__avx2_perm_p4)->Unit(benchmark::kMillisecond)->Iterations(1); |
| BENCHMARK(f32_exp__avx2_perm_p3)->Unit(benchmark::kMillisecond)->Iterations(1); |
| BENCHMARK(f32_exp__avx2_p5)->Unit(benchmark::kMillisecond)->Iterations(1); |
| BENCHMARK(f32_exp__avx512f_perm2_p2)->Unit(benchmark::kMillisecond)->Iterations(1); |
| BENCHMARK(f32_exp__avx512f_perm_p3)->Unit(benchmark::kMillisecond)->Iterations(1); |
| BENCHMARK(f32_exp__avx512f_p5_scalef)->Unit(benchmark::kMillisecond)->Iterations(1); |
| BENCHMARK(f32_exp__avx512f_p5)->Unit(benchmark::kMillisecond)->Iterations(1); |
| #endif // XNN_ARCH_X86 || XNN_ARCH_X86_64 |
| |
| #if XNN_ARCH_ARM || XNN_ARCH_ARM64 |
| static void f32_exp__neonfma_lut64_p2(benchmark::State& state) { |
| ExpError(state, xnn_math_f32_exp__neonfma_lut64_p2, 4); |
| } |
| static void f32_exp__neonfma_p5(benchmark::State& state) { |
| ExpError(state, xnn_math_f32_exp__neonfma_p5, 4); |
| } |
| |
| BENCHMARK(f32_exp__neonfma_lut64_p2)->Unit(benchmark::kMillisecond)->Iterations(1); |
| BENCHMARK(f32_exp__neonfma_p5)->Unit(benchmark::kMillisecond)->Iterations(1); |
| #endif // XNN_ARCH_ARM || XNN_ARCH_ARM64 |
| |
| #ifndef XNNPACK_BENCHMARK_NO_MAIN |
| BENCHMARK_MAIN(); |
| #endif |