Marat Dukhan | 346a9e5 | 2019-11-15 09:06:30 -0800 | [diff] [blame] | 1 | // Copyright 2019 Google LLC |
| 2 | // |
| 3 | // This source code is licensed under the BSD-style license found in the |
| 4 | // LICENSE file in the root directory of this source tree. |
| 5 | |
| 6 | #include <algorithm> |
| 7 | #include <cfloat> |
| 8 | #include <cmath> |
| 9 | #include <functional> |
| 10 | #include <random> |
| 11 | #include <vector> |
| 12 | |
| 13 | #include <benchmark/benchmark.h> |
| 14 | #include <fp16/fp16.h> |
| 15 | |
| 16 | #include <xnnpack/AlignedAllocator.h> |
| 17 | #include <xnnpack/common.h> |
| 18 | #include <xnnpack/math-stubs.h> |
| 19 | |
| 20 | |
| 21 | static void SigmoidError(benchmark::State& state, |
| 22 | xnn_f32_unary_math_function sigmoid, |
| 23 | size_t tile_size) |
| 24 | { |
| 25 | // The smallest x for which sigmoidf(x) is normalized (-0x1.5D589Ep+6f). |
| 26 | const uint32_t min_input = 0xC2AEAC4F; |
| 27 | // The largest x for which sigmoidf(x) is not 1.0f (0x1.154244p+4f). |
| 28 | const uint32_t max_input = 0x418AA122; |
| 29 | // Number of tiles in one block of inputs/outputs. Combining multiple tiles in a block reduce function call overhead. |
| 30 | const size_t num_tiles = 100; |
| 31 | |
| 32 | double max_ulp_error = 0.0; |
| 33 | std::vector<float, AlignedAllocator<float, 64>> x(tile_size * num_tiles); |
| 34 | std::vector<float, AlignedAllocator<float, 64>> y(tile_size * num_tiles); |
| 35 | for (auto _ : state) { |
| 36 | for (uint32_t n = min_input; int32_t(n) < 0; n -= tile_size * num_tiles) { |
| 37 | for (uint32_t i = 0; i < tile_size * num_tiles; i++) { |
| 38 | x[i] = fp32_from_bits(std::max<uint32_t>(n - i, 0x80000000)); |
| 39 | } |
| 40 | std::fill(y.begin(), y.end(), std::nanf("")); |
| 41 | |
| 42 | sigmoid(tile_size * num_tiles * sizeof(float), x.data(), y.data()); |
| 43 | |
| 44 | for (uint32_t i = 0; i < tile_size * num_tiles; i++) { |
| 45 | const double e_ref = std::exp(double(x[i])); |
| 46 | const double y_ref = e_ref / (e_ref + 1.0); |
| 47 | const double abs_error = std::abs(y_ref - double(y[i])); |
| 48 | const float y_abs = std::abs(y_ref); |
| 49 | const float y_ulp = fp32_from_bits(fp32_to_bits(y_abs) + 1) - y_abs; |
| 50 | max_ulp_error = std::max<double>(max_ulp_error, abs_error / y_ulp); |
| 51 | } |
| 52 | } |
| 53 | for (uint32_t n = 0; n < max_input; n += tile_size * num_tiles) { |
| 54 | for (uint32_t i = 0; i < tile_size * num_tiles; i++) { |
| 55 | x[i] = fp32_from_bits(std::min<uint32_t>(n + i, max_input)); |
| 56 | } |
| 57 | std::fill(y.begin(), y.end(), std::nanf("")); |
| 58 | |
| 59 | sigmoid(tile_size * num_tiles * sizeof(float), x.data(), y.data()); |
| 60 | |
| 61 | for (uint32_t i = 0; i < tile_size * num_tiles; i++) { |
| 62 | const double y_ref = 1.0 / (1.0 + std::exp(-double(x[i]))); |
| 63 | const double abs_error = std::abs(y_ref - double(y[i])); |
| 64 | const float y_abs = std::abs(y_ref); |
| 65 | const float y_ulp = fp32_from_bits(fp32_to_bits(y_abs) + 1) - y_abs; |
| 66 | max_ulp_error = std::max<double>(max_ulp_error, abs_error / y_ulp); |
| 67 | } |
| 68 | } |
| 69 | } |
| 70 | |
| 71 | state.counters["ULPERROR"] = benchmark::Counter(max_ulp_error); |
| 72 | } |
| 73 | |
| 74 | #if XNN_ARCH_ARM || XNN_ARCH_ARM64 |
Marat Dukhan | 91f8d86 | 2019-11-27 12:25:42 -0800 | [diff] [blame^] | 75 | static void f32_sigmoid__neonfma_lut2048_p1_nr1recps1fma(benchmark::State& state) { |
| 76 | SigmoidError(state, xnn_math_f32_sigmoid__neonfma_lut2048_p1_nr1recps1fma, 4); |
| 77 | } |
| 78 | static void f32_sigmoid__neonfma_lut2048_p1_nr2recps(benchmark::State& state) { |
| 79 | SigmoidError(state, xnn_math_f32_sigmoid__neonfma_lut2048_p1_nr2recps, 4); |
| 80 | } |
| 81 | static void f32_sigmoid__neonfma_lut2048_p1_nr2fma(benchmark::State& state) { |
| 82 | SigmoidError(state, xnn_math_f32_sigmoid__neonfma_lut2048_p1_nr2fma, 4); |
| 83 | } |
| 84 | |
Marat Dukhan | 22aae13 | 2019-11-22 17:10:29 -0800 | [diff] [blame] | 85 | static void f32_sigmoid__neonfma_p5_nr1recps1fma(benchmark::State& state) { |
| 86 | SigmoidError(state, xnn_math_f32_sigmoid__neonfma_p5_nr1recps1fma, 4); |
| 87 | } |
Marat Dukhan | 22aae13 | 2019-11-22 17:10:29 -0800 | [diff] [blame] | 88 | static void f32_sigmoid__neonfma_p5_nr2recps(benchmark::State& state) { |
| 89 | SigmoidError(state, xnn_math_f32_sigmoid__neonfma_p5_nr2recps, 4); |
| 90 | } |
Marat Dukhan | 80bafd2 | 2019-11-18 10:16:01 -0800 | [diff] [blame] | 91 | static void f32_sigmoid__neonfma_p5_nr2fma(benchmark::State& state) { |
| 92 | SigmoidError(state, xnn_math_f32_sigmoid__neonfma_p5_nr2fma, 4); |
Marat Dukhan | 346a9e5 | 2019-11-15 09:06:30 -0800 | [diff] [blame] | 93 | } |
| 94 | |
Marat Dukhan | 91f8d86 | 2019-11-27 12:25:42 -0800 | [diff] [blame^] | 95 | BENCHMARK(f32_sigmoid__neonfma_lut2048_p1_nr1recps1fma)->Unit(benchmark::kMillisecond)->Iterations(1); |
| 96 | BENCHMARK(f32_sigmoid__neonfma_lut2048_p1_nr2recps)->Unit(benchmark::kMillisecond)->Iterations(1); |
| 97 | BENCHMARK(f32_sigmoid__neonfma_lut2048_p1_nr2fma)->Unit(benchmark::kMillisecond)->Iterations(1); |
| 98 | |
Marat Dukhan | 22aae13 | 2019-11-22 17:10:29 -0800 | [diff] [blame] | 99 | BENCHMARK(f32_sigmoid__neonfma_p5_nr1recps1fma)->Unit(benchmark::kMillisecond)->Iterations(1); |
| 100 | BENCHMARK(f32_sigmoid__neonfma_p5_nr2recps)->Unit(benchmark::kMillisecond)->Iterations(1); |
Marat Dukhan | 80bafd2 | 2019-11-18 10:16:01 -0800 | [diff] [blame] | 101 | BENCHMARK(f32_sigmoid__neonfma_p5_nr2fma)->Unit(benchmark::kMillisecond)->Iterations(1); |
Marat Dukhan | 346a9e5 | 2019-11-15 09:06:30 -0800 | [diff] [blame] | 102 | #endif // XNN_ARCH_ARM || XNN_ARCH_ARM64 |
| 103 | |
Marat Dukhan | 22aae13 | 2019-11-22 17:10:29 -0800 | [diff] [blame] | 104 | #if XNN_ARCH_ARM64 |
Marat Dukhan | 91f8d86 | 2019-11-27 12:25:42 -0800 | [diff] [blame^] | 105 | static void f32_sigmoid__neonfma_lut2048_p1_div(benchmark::State& state) { |
| 106 | SigmoidError(state, xnn_math_f32_sigmoid__neonfma_lut2048_p1_div, 4); |
| 107 | } |
Marat Dukhan | 22aae13 | 2019-11-22 17:10:29 -0800 | [diff] [blame] | 108 | static void f32_sigmoid__neonfma_p5_div(benchmark::State& state) { |
| 109 | SigmoidError(state, xnn_math_f32_sigmoid__neonfma_p5_div, 4); |
| 110 | } |
| 111 | |
Marat Dukhan | 91f8d86 | 2019-11-27 12:25:42 -0800 | [diff] [blame^] | 112 | BENCHMARK(f32_sigmoid__neonfma_lut2048_p1_div)->Unit(benchmark::kMillisecond)->Iterations(1); |
Marat Dukhan | 22aae13 | 2019-11-22 17:10:29 -0800 | [diff] [blame] | 113 | BENCHMARK(f32_sigmoid__neonfma_p5_div)->Unit(benchmark::kMillisecond)->Iterations(1); |
| 114 | #endif // XNN_ARCH_ARM64 |
| 115 | |
Marat Dukhan | 80bafd2 | 2019-11-18 10:16:01 -0800 | [diff] [blame] | 116 | #if XNN_ARCH_X86 || XNN_ARCH_X86_64 |
| 117 | static void f32_sigmoid__sse2_p5_div(benchmark::State& state) { |
| 118 | SigmoidError(state, xnn_math_f32_sigmoid__sse2_p5_div, 4); |
| 119 | } |
| 120 | |
| 121 | BENCHMARK(f32_sigmoid__sse2_p5_div)->Unit(benchmark::kMillisecond)->Iterations(1); |
| 122 | #endif // XNN_ARCH_X86 || XNN_ARCH_X86_64 |
| 123 | |
Marat Dukhan | 346a9e5 | 2019-11-15 09:06:30 -0800 | [diff] [blame] | 124 | #ifndef XNNPACK_BENCHMARK_NO_MAIN |
| 125 | BENCHMARK_MAIN(); |
| 126 | #endif |