blob: e4d1381ae1769031451b3c334a12b68629518cb1 [file] [log] [blame]
peah5e79b292017-04-12 01:20:45 -07001/*
2 * Copyright (c) 2017 The WebRTC project authors. All Rights Reserved.
3 *
4 * Use of this source code is governed by a BSD-style license
5 * that can be found in the LICENSE file in the root of the source
6 * tree. An additional intellectual property rights grant can be found
7 * in the file PATENTS. All contributing project authors may
8 * be found in the AUTHORS file in the root of the source tree.
9 */
10
Mirko Bonadei92ea95e2017-09-15 06:47:31 +020011#ifndef MODULES_AUDIO_PROCESSING_AEC3_VECTOR_MATH_H_
12#define MODULES_AUDIO_PROCESSING_AEC3_VECTOR_MATH_H_
peah5e79b292017-04-12 01:20:45 -070013
Niels Möllera12c42a2018-07-25 16:05:48 +020014// Defines WEBRTC_ARCH_X86_FAMILY, used below.
15#include "rtc_base/system/arch.h"
16
peah5d153c72017-05-03 06:45:44 -070017#if defined(WEBRTC_HAS_NEON)
18#include <arm_neon.h>
19#endif
peah5e79b292017-04-12 01:20:45 -070020#if defined(WEBRTC_ARCH_X86_FAMILY)
21#include <emmintrin.h>
22#endif
23#include <math.h>
Jonas Olssona4d87372019-07-05 19:08:33 +020024
peah5e79b292017-04-12 01:20:45 -070025#include <algorithm>
26#include <array>
27#include <functional>
28
Mirko Bonadei92ea95e2017-09-15 06:47:31 +020029#include "api/array_view.h"
30#include "modules/audio_processing/aec3/aec3_common.h"
31#include "rtc_base/checks.h"
peah5e79b292017-04-12 01:20:45 -070032
33namespace webrtc {
34namespace aec3 {
35
36// Provides optimizations for mathematical operations based on vectors.
37class VectorMath {
38 public:
39 explicit VectorMath(Aec3Optimization optimization)
40 : optimization_(optimization) {}
41
42 // Elementwise square root.
Zhaoliang Mae537e9c2020-08-31 10:20:47 +080043 void SqrtAVX2(rtc::ArrayView<float> x);
peah5e79b292017-04-12 01:20:45 -070044 void Sqrt(rtc::ArrayView<float> x) {
45 switch (optimization_) {
46#if defined(WEBRTC_ARCH_X86_FAMILY)
47 case Aec3Optimization::kSse2: {
48 const int x_size = static_cast<int>(x.size());
49 const int vector_limit = x_size >> 2;
50
51 int j = 0;
52 for (; j < vector_limit * 4; j += 4) {
53 __m128 g = _mm_loadu_ps(&x[j]);
54 g = _mm_sqrt_ps(g);
55 _mm_storeu_ps(&x[j], g);
56 }
57
58 for (; j < x_size; ++j) {
59 x[j] = sqrtf(x[j]);
60 }
61 } break;
Zhaoliang Mae537e9c2020-08-31 10:20:47 +080062 case Aec3Optimization::kAvx2:
63 SqrtAVX2(x);
64 break;
peah5e79b292017-04-12 01:20:45 -070065#endif
peah5d153c72017-05-03 06:45:44 -070066#if defined(WEBRTC_HAS_NEON)
67 case Aec3Optimization::kNeon: {
68 const int x_size = static_cast<int>(x.size());
69 const int vector_limit = x_size >> 2;
70
71 int j = 0;
72 for (; j < vector_limit * 4; j += 4) {
73 float32x4_t g = vld1q_f32(&x[j]);
74#if !defined(WEBRTC_ARCH_ARM64)
75 float32x4_t y = vrsqrteq_f32(g);
76
77 // Code to handle sqrt(0).
78 // If the input to sqrtf() is zero, a zero will be returned.
79 // If the input to vrsqrteq_f32() is zero, positive infinity is
80 // returned.
81 const uint32x4_t vec_p_inf = vdupq_n_u32(0x7F800000);
82 // check for divide by zero
83 const uint32x4_t div_by_zero =
84 vceqq_u32(vec_p_inf, vreinterpretq_u32_f32(y));
85 // zero out the positive infinity results
86 y = vreinterpretq_f32_u32(
87 vandq_u32(vmvnq_u32(div_by_zero), vreinterpretq_u32_f32(y)));
88 // from arm documentation
89 // The Newton-Raphson iteration:
90 // y[n+1] = y[n] * (3 - d * (y[n] * y[n])) / 2)
91 // converges to (1/√d) if y0 is the result of VRSQRTE applied to d.
92 //
93 // Note: The precision did not improve after 2 iterations.
94 for (int i = 0; i < 2; i++) {
95 y = vmulq_f32(vrsqrtsq_f32(vmulq_f32(y, y), g), y);
96 }
97 // sqrt(g) = g * 1/sqrt(g)
98 g = vmulq_f32(g, y);
99#else
100 g = vsqrtq_f32(g);
101#endif
102 vst1q_f32(&x[j], g);
103 }
104
105 for (; j < x_size; ++j) {
106 x[j] = sqrtf(x[j]);
107 }
108 }
109#endif
110 break;
peah5e79b292017-04-12 01:20:45 -0700111 default:
112 std::for_each(x.begin(), x.end(), [](float& a) { a = sqrtf(a); });
113 }
114 }
115
116 // Elementwise vector multiplication z = x * y.
Zhaoliang Mae537e9c2020-08-31 10:20:47 +0800117 void MultiplyAVX2(rtc::ArrayView<const float> x,
118 rtc::ArrayView<const float> y,
119 rtc::ArrayView<float> z);
peah5e79b292017-04-12 01:20:45 -0700120 void Multiply(rtc::ArrayView<const float> x,
121 rtc::ArrayView<const float> y,
122 rtc::ArrayView<float> z) {
123 RTC_DCHECK_EQ(z.size(), x.size());
124 RTC_DCHECK_EQ(z.size(), y.size());
125 switch (optimization_) {
126#if defined(WEBRTC_ARCH_X86_FAMILY)
127 case Aec3Optimization::kSse2: {
128 const int x_size = static_cast<int>(x.size());
129 const int vector_limit = x_size >> 2;
130
131 int j = 0;
132 for (; j < vector_limit * 4; j += 4) {
133 const __m128 x_j = _mm_loadu_ps(&x[j]);
134 const __m128 y_j = _mm_loadu_ps(&y[j]);
135 const __m128 z_j = _mm_mul_ps(x_j, y_j);
136 _mm_storeu_ps(&z[j], z_j);
137 }
138
139 for (; j < x_size; ++j) {
140 z[j] = x[j] * y[j];
141 }
142 } break;
Zhaoliang Mae537e9c2020-08-31 10:20:47 +0800143 case Aec3Optimization::kAvx2:
144 MultiplyAVX2(x, y, z);
145 break;
peah5e79b292017-04-12 01:20:45 -0700146#endif
peah5d153c72017-05-03 06:45:44 -0700147#if defined(WEBRTC_HAS_NEON)
148 case Aec3Optimization::kNeon: {
149 const int x_size = static_cast<int>(x.size());
150 const int vector_limit = x_size >> 2;
151
152 int j = 0;
153 for (; j < vector_limit * 4; j += 4) {
154 const float32x4_t x_j = vld1q_f32(&x[j]);
155 const float32x4_t y_j = vld1q_f32(&y[j]);
156 const float32x4_t z_j = vmulq_f32(x_j, y_j);
157 vst1q_f32(&z[j], z_j);
158 }
159
160 for (; j < x_size; ++j) {
161 z[j] = x[j] * y[j];
162 }
163 } break;
164#endif
peah5e79b292017-04-12 01:20:45 -0700165 default:
166 std::transform(x.begin(), x.end(), y.begin(), z.begin(),
167 std::multiplies<float>());
168 }
169 }
170
171 // Elementwise vector accumulation z += x.
Zhaoliang Mae537e9c2020-08-31 10:20:47 +0800172 void AccumulateAVX2(rtc::ArrayView<const float> x, rtc::ArrayView<float> z);
peah5e79b292017-04-12 01:20:45 -0700173 void Accumulate(rtc::ArrayView<const float> x, rtc::ArrayView<float> z) {
174 RTC_DCHECK_EQ(z.size(), x.size());
175 switch (optimization_) {
176#if defined(WEBRTC_ARCH_X86_FAMILY)
177 case Aec3Optimization::kSse2: {
178 const int x_size = static_cast<int>(x.size());
179 const int vector_limit = x_size >> 2;
180
181 int j = 0;
182 for (; j < vector_limit * 4; j += 4) {
183 const __m128 x_j = _mm_loadu_ps(&x[j]);
184 __m128 z_j = _mm_loadu_ps(&z[j]);
185 z_j = _mm_add_ps(x_j, z_j);
186 _mm_storeu_ps(&z[j], z_j);
187 }
188
189 for (; j < x_size; ++j) {
190 z[j] += x[j];
191 }
192 } break;
Zhaoliang Mae537e9c2020-08-31 10:20:47 +0800193 case Aec3Optimization::kAvx2:
194 AccumulateAVX2(x, z);
195 break;
peah5e79b292017-04-12 01:20:45 -0700196#endif
peah5d153c72017-05-03 06:45:44 -0700197#if defined(WEBRTC_HAS_NEON)
198 case Aec3Optimization::kNeon: {
199 const int x_size = static_cast<int>(x.size());
200 const int vector_limit = x_size >> 2;
201
202 int j = 0;
203 for (; j < vector_limit * 4; j += 4) {
204 const float32x4_t x_j = vld1q_f32(&x[j]);
205 float32x4_t z_j = vld1q_f32(&z[j]);
206 z_j = vaddq_f32(z_j, x_j);
207 vst1q_f32(&z[j], z_j);
208 }
209
210 for (; j < x_size; ++j) {
211 z[j] += x[j];
212 }
213 } break;
214#endif
peah5e79b292017-04-12 01:20:45 -0700215 default:
216 std::transform(x.begin(), x.end(), z.begin(), z.begin(),
217 std::plus<float>());
218 }
219 }
220
221 private:
222 Aec3Optimization optimization_;
223};
224
225} // namespace aec3
226
227} // namespace webrtc
228
Mirko Bonadei92ea95e2017-09-15 06:47:31 +0200229#endif // MODULES_AUDIO_PROCESSING_AEC3_VECTOR_MATH_H_