blob: 32bd94351cebee12fe23cc6d6e9b4d696d0c8005 [file] [log] [blame]
Marat Dukhan98ba4412019-10-23 02:14:28 -07001// 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
21static void ExpError(benchmark::State& state,
22 xnn_f32_ext_unary_math_function extexp,
23 size_t tile_size)
24{
25 // The smallest x for which exp(x) (double-precision) is normal (-0x1.6232BCp9f).
26 const uint32_t min_input = 0xC431195E;
27 // The largest x for which exp(x) (double-precision) is finite (0x1.62E42Ep9).
28 const uint32_t max_input = 0x44317217;
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>> m(tile_size * num_tiles);
35 std::vector<float, AlignedAllocator<float, 64>> e(tile_size * num_tiles);
36 for (auto _ : state) {
37 for (uint32_t n = min_input; int32_t(n) < 0; n -= tile_size * num_tiles) {
38 for (uint32_t i = 0; i < tile_size * num_tiles; i++) {
39 x[i] = fp32_from_bits(std::max<uint32_t>(n - i, 0x80000000));
40 }
41 std::fill(m.begin(), m.end(), std::nanf(""));
42 std::fill(e.begin(), e.end(), std::nanf(""));
43
44 extexp(tile_size * num_tiles * sizeof(float), x.data(), m.data(), e.data());
45
46 for (uint32_t i = 0; i < tile_size * num_tiles; i++) {
47 const double y_ref = std::exp(double(x[i]));
48 int y_ref_e;
49 const double y_ref_m = std::frexp(y_ref, &y_ref_e);
50 const double ulp_error = std::abs(y_ref_m - std::ldexp(double(m[i]), int(e[i]) - y_ref_e)) * 0x1.0p+24;
51 max_ulp_error = std::max<double>(max_ulp_error, ulp_error);
52 }
53 }
54 for (uint32_t n = 0; n < max_input; n += tile_size * num_tiles) {
55 for (uint32_t i = 0; i < tile_size * num_tiles; i++) {
56 x[i] = fp32_from_bits(std::min<uint32_t>(n + i, max_input));
57 }
58 std::fill(m.begin(), m.end(), std::nanf(""));
59 std::fill(e.begin(), e.end(), std::nanf(""));
60
61 extexp(tile_size * num_tiles * sizeof(float), x.data(), m.data(), e.data());
62
63 for (uint32_t i = 0; i < tile_size * num_tiles; i++) {
64 const double y_ref = std::exp(double(x[i]));
65 int y_ref_e;
66 const double y_ref_m = std::frexp(y_ref, &y_ref_e);
67 const double ulp_error = std::abs(y_ref_m - std::ldexp(double(m[i]), int(e[i]) - y_ref_e)) * 0x1.0p+24;
68 max_ulp_error = std::max<double>(max_ulp_error, ulp_error);
69 }
70 }
71 }
72
73 state.counters["ULPERROR"] = benchmark::Counter(max_ulp_error);
74}
75
76#if XNN_ARCH_X86 || XNN_ARCH_X86_64
77 static void f32_extexp__avx512f_p5(benchmark::State& state) {
78 ExpError(state, xnn_math_f32_extexp__avx512f_p5, 16);
79 }
80 static void f32_extexp__avx2_p5(benchmark::State& state) {
81 ExpError(state, xnn_math_f32_extexp__avx2_p5, 8);
82 }
83
84 BENCHMARK(f32_extexp__avx512f_p5)->Unit(benchmark::kMillisecond)->Iterations(1);
85 BENCHMARK(f32_extexp__avx2_p5)->Unit(benchmark::kMillisecond)->Iterations(1);
86#endif // XNN_ARCH_X86 || XNN_ARCH_X86_64
87
88#ifndef XNNPACK_BENCHMARK_NO_MAIN
89BENCHMARK_MAIN();
90#endif