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/*
* Copyright (c) 2017 The WebRTC project authors. All Rights Reserved.
*
* Use of this source code is governed by a BSD-style license
* that can be found in the LICENSE file in the root of the source
* tree. An additional intellectual property rights grant can be found
* in the file PATENTS. All contributing project authors may
* be found in the AUTHORS file in the root of the source tree.
*/
#ifndef MODULES_AUDIO_PROCESSING_AEC3_VECTOR_MATH_H_
#define MODULES_AUDIO_PROCESSING_AEC3_VECTOR_MATH_H_
// Defines WEBRTC_ARCH_X86_FAMILY, used below.
#include "rtc_base/system/arch.h"
#if defined(WEBRTC_HAS_NEON)
#include <arm_neon.h>
#endif
#if defined(WEBRTC_ARCH_X86_FAMILY)
#include <emmintrin.h>
#endif
#include <math.h>
#include <algorithm>
#include <array>
#include <functional>
#include "api/array_view.h"
#include "modules/audio_processing/aec3/aec3_common.h"
#include "rtc_base/checks.h"
namespace webrtc {
namespace aec3 {
// Provides optimizations for mathematical operations based on vectors.
class VectorMath {
public:
explicit VectorMath(Aec3Optimization optimization)
: optimization_(optimization) {}
// Elementwise square root.
void SqrtAVX2(rtc::ArrayView<float> x);
void Sqrt(rtc::ArrayView<float> x) {
switch (optimization_) {
#if defined(WEBRTC_ARCH_X86_FAMILY)
case Aec3Optimization::kSse2: {
const int x_size = static_cast<int>(x.size());
const int vector_limit = x_size >> 2;
int j = 0;
for (; j < vector_limit * 4; j += 4) {
__m128 g = _mm_loadu_ps(&x[j]);
g = _mm_sqrt_ps(g);
_mm_storeu_ps(&x[j], g);
}
for (; j < x_size; ++j) {
x[j] = sqrtf(x[j]);
}
} break;
case Aec3Optimization::kAvx2:
SqrtAVX2(x);
break;
#endif
#if defined(WEBRTC_HAS_NEON)
case Aec3Optimization::kNeon: {
const int x_size = static_cast<int>(x.size());
const int vector_limit = x_size >> 2;
int j = 0;
for (; j < vector_limit * 4; j += 4) {
float32x4_t g = vld1q_f32(&x[j]);
#if !defined(WEBRTC_ARCH_ARM64)
float32x4_t y = vrsqrteq_f32(g);
// Code to handle sqrt(0).
// If the input to sqrtf() is zero, a zero will be returned.
// If the input to vrsqrteq_f32() is zero, positive infinity is
// returned.
const uint32x4_t vec_p_inf = vdupq_n_u32(0x7F800000);
// check for divide by zero
const uint32x4_t div_by_zero =
vceqq_u32(vec_p_inf, vreinterpretq_u32_f32(y));
// zero out the positive infinity results
y = vreinterpretq_f32_u32(
vandq_u32(vmvnq_u32(div_by_zero), vreinterpretq_u32_f32(y)));
// from arm documentation
// The Newton-Raphson iteration:
// y[n+1] = y[n] * (3 - d * (y[n] * y[n])) / 2)
// converges to (1/√d) if y0 is the result of VRSQRTE applied to d.
//
// Note: The precision did not improve after 2 iterations.
for (int i = 0; i < 2; i++) {
y = vmulq_f32(vrsqrtsq_f32(vmulq_f32(y, y), g), y);
}
// sqrt(g) = g * 1/sqrt(g)
g = vmulq_f32(g, y);
#else
g = vsqrtq_f32(g);
#endif
vst1q_f32(&x[j], g);
}
for (; j < x_size; ++j) {
x[j] = sqrtf(x[j]);
}
}
#endif
break;
default:
std::for_each(x.begin(), x.end(), [](float& a) { a = sqrtf(a); });
}
}
// Elementwise vector multiplication z = x * y.
void MultiplyAVX2(rtc::ArrayView<const float> x,
rtc::ArrayView<const float> y,
rtc::ArrayView<float> z);
void Multiply(rtc::ArrayView<const float> x,
rtc::ArrayView<const float> y,
rtc::ArrayView<float> z) {
RTC_DCHECK_EQ(z.size(), x.size());
RTC_DCHECK_EQ(z.size(), y.size());
switch (optimization_) {
#if defined(WEBRTC_ARCH_X86_FAMILY)
case Aec3Optimization::kSse2: {
const int x_size = static_cast<int>(x.size());
const int vector_limit = x_size >> 2;
int j = 0;
for (; j < vector_limit * 4; j += 4) {
const __m128 x_j = _mm_loadu_ps(&x[j]);
const __m128 y_j = _mm_loadu_ps(&y[j]);
const __m128 z_j = _mm_mul_ps(x_j, y_j);
_mm_storeu_ps(&z[j], z_j);
}
for (; j < x_size; ++j) {
z[j] = x[j] * y[j];
}
} break;
case Aec3Optimization::kAvx2:
MultiplyAVX2(x, y, z);
break;
#endif
#if defined(WEBRTC_HAS_NEON)
case Aec3Optimization::kNeon: {
const int x_size = static_cast<int>(x.size());
const int vector_limit = x_size >> 2;
int j = 0;
for (; j < vector_limit * 4; j += 4) {
const float32x4_t x_j = vld1q_f32(&x[j]);
const float32x4_t y_j = vld1q_f32(&y[j]);
const float32x4_t z_j = vmulq_f32(x_j, y_j);
vst1q_f32(&z[j], z_j);
}
for (; j < x_size; ++j) {
z[j] = x[j] * y[j];
}
} break;
#endif
default:
std::transform(x.begin(), x.end(), y.begin(), z.begin(),
std::multiplies<float>());
}
}
// Elementwise vector accumulation z += x.
void AccumulateAVX2(rtc::ArrayView<const float> x, rtc::ArrayView<float> z);
void Accumulate(rtc::ArrayView<const float> x, rtc::ArrayView<float> z) {
RTC_DCHECK_EQ(z.size(), x.size());
switch (optimization_) {
#if defined(WEBRTC_ARCH_X86_FAMILY)
case Aec3Optimization::kSse2: {
const int x_size = static_cast<int>(x.size());
const int vector_limit = x_size >> 2;
int j = 0;
for (; j < vector_limit * 4; j += 4) {
const __m128 x_j = _mm_loadu_ps(&x[j]);
__m128 z_j = _mm_loadu_ps(&z[j]);
z_j = _mm_add_ps(x_j, z_j);
_mm_storeu_ps(&z[j], z_j);
}
for (; j < x_size; ++j) {
z[j] += x[j];
}
} break;
case Aec3Optimization::kAvx2:
AccumulateAVX2(x, z);
break;
#endif
#if defined(WEBRTC_HAS_NEON)
case Aec3Optimization::kNeon: {
const int x_size = static_cast<int>(x.size());
const int vector_limit = x_size >> 2;
int j = 0;
for (; j < vector_limit * 4; j += 4) {
const float32x4_t x_j = vld1q_f32(&x[j]);
float32x4_t z_j = vld1q_f32(&z[j]);
z_j = vaddq_f32(z_j, x_j);
vst1q_f32(&z[j], z_j);
}
for (; j < x_size; ++j) {
z[j] += x[j];
}
} break;
#endif
default:
std::transform(x.begin(), x.end(), z.begin(), z.begin(),
std::plus<float>());
}
}
private:
Aec3Optimization optimization_;
};
} // namespace aec3
} // namespace webrtc
#endif // MODULES_AUDIO_PROCESSING_AEC3_VECTOR_MATH_H_
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