1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
|
// 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
|
