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/*
* Copyright (c) 2011 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.
*/
/*
* The core AEC algorithm, SSE2 version of speed-critical functions.
*/
#include <emmintrin.h>
#include <math.h>
#include <string.h> // memset
extern "C" {
#include "common_audio/signal_processing/include/signal_processing_library.h"
}
#include "modules/audio_processing/aec/aec_common.h"
#include "modules/audio_processing/aec/aec_core_optimized_methods.h"
#include "modules/audio_processing/utility/ooura_fft.h"
namespace webrtc {
__inline static float MulRe(float aRe, float aIm, float bRe, float bIm) {
return aRe * bRe - aIm * bIm;
}
__inline static float MulIm(float aRe, float aIm, float bRe, float bIm) {
return aRe * bIm + aIm * bRe;
}
static void FilterFarSSE2(
int num_partitions,
int x_fft_buf_block_pos,
float x_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
float h_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
float y_fft[2][PART_LEN1]) {
int i;
for (i = 0; i < num_partitions; i++) {
int j;
int xPos = (i + x_fft_buf_block_pos) * PART_LEN1;
int pos = i * PART_LEN1;
// Check for wrap
if (i + x_fft_buf_block_pos >= num_partitions) {
xPos -= num_partitions * (PART_LEN1);
}
// vectorized code (four at once)
for (j = 0; j + 3 < PART_LEN1; j += 4) {
const __m128 x_fft_buf_re = _mm_loadu_ps(&x_fft_buf[0][xPos + j]);
const __m128 x_fft_buf_im = _mm_loadu_ps(&x_fft_buf[1][xPos + j]);
const __m128 h_fft_buf_re = _mm_loadu_ps(&h_fft_buf[0][pos + j]);
const __m128 h_fft_buf_im = _mm_loadu_ps(&h_fft_buf[1][pos + j]);
const __m128 y_fft_re = _mm_loadu_ps(&y_fft[0][j]);
const __m128 y_fft_im = _mm_loadu_ps(&y_fft[1][j]);
const __m128 a = _mm_mul_ps(x_fft_buf_re, h_fft_buf_re);
const __m128 b = _mm_mul_ps(x_fft_buf_im, h_fft_buf_im);
const __m128 c = _mm_mul_ps(x_fft_buf_re, h_fft_buf_im);
const __m128 d = _mm_mul_ps(x_fft_buf_im, h_fft_buf_re);
const __m128 e = _mm_sub_ps(a, b);
const __m128 f = _mm_add_ps(c, d);
const __m128 g = _mm_add_ps(y_fft_re, e);
const __m128 h = _mm_add_ps(y_fft_im, f);
_mm_storeu_ps(&y_fft[0][j], g);
_mm_storeu_ps(&y_fft[1][j], h);
}
// scalar code for the remaining items.
for (; j < PART_LEN1; j++) {
y_fft[0][j] += MulRe(x_fft_buf[0][xPos + j], x_fft_buf[1][xPos + j],
h_fft_buf[0][pos + j], h_fft_buf[1][pos + j]);
y_fft[1][j] += MulIm(x_fft_buf[0][xPos + j], x_fft_buf[1][xPos + j],
h_fft_buf[0][pos + j], h_fft_buf[1][pos + j]);
}
}
}
static void ScaleErrorSignalSSE2(float mu,
float error_threshold,
float x_pow[PART_LEN1],
float ef[2][PART_LEN1]) {
const __m128 k1e_10f = _mm_set1_ps(1e-10f);
const __m128 kMu = _mm_set1_ps(mu);
const __m128 kThresh = _mm_set1_ps(error_threshold);
int i;
// vectorized code (four at once)
for (i = 0; i + 3 < PART_LEN1; i += 4) {
const __m128 x_pow_local = _mm_loadu_ps(&x_pow[i]);
const __m128 ef_re_base = _mm_loadu_ps(&ef[0][i]);
const __m128 ef_im_base = _mm_loadu_ps(&ef[1][i]);
const __m128 xPowPlus = _mm_add_ps(x_pow_local, k1e_10f);
__m128 ef_re = _mm_div_ps(ef_re_base, xPowPlus);
__m128 ef_im = _mm_div_ps(ef_im_base, xPowPlus);
const __m128 ef_re2 = _mm_mul_ps(ef_re, ef_re);
const __m128 ef_im2 = _mm_mul_ps(ef_im, ef_im);
const __m128 ef_sum2 = _mm_add_ps(ef_re2, ef_im2);
const __m128 absEf = _mm_sqrt_ps(ef_sum2);
const __m128 bigger = _mm_cmpgt_ps(absEf, kThresh);
__m128 absEfPlus = _mm_add_ps(absEf, k1e_10f);
const __m128 absEfInv = _mm_div_ps(kThresh, absEfPlus);
__m128 ef_re_if = _mm_mul_ps(ef_re, absEfInv);
__m128 ef_im_if = _mm_mul_ps(ef_im, absEfInv);
ef_re_if = _mm_and_ps(bigger, ef_re_if);
ef_im_if = _mm_and_ps(bigger, ef_im_if);
ef_re = _mm_andnot_ps(bigger, ef_re);
ef_im = _mm_andnot_ps(bigger, ef_im);
ef_re = _mm_or_ps(ef_re, ef_re_if);
ef_im = _mm_or_ps(ef_im, ef_im_if);
ef_re = _mm_mul_ps(ef_re, kMu);
ef_im = _mm_mul_ps(ef_im, kMu);
_mm_storeu_ps(&ef[0][i], ef_re);
_mm_storeu_ps(&ef[1][i], ef_im);
}
// scalar code for the remaining items.
{
for (; i < (PART_LEN1); i++) {
float abs_ef;
ef[0][i] /= (x_pow[i] + 1e-10f);
ef[1][i] /= (x_pow[i] + 1e-10f);
abs_ef = sqrtf(ef[0][i] * ef[0][i] + ef[1][i] * ef[1][i]);
if (abs_ef > error_threshold) {
abs_ef = error_threshold / (abs_ef + 1e-10f);
ef[0][i] *= abs_ef;
ef[1][i] *= abs_ef;
}
// Stepsize factor
ef[0][i] *= mu;
ef[1][i] *= mu;
}
}
}
static void FilterAdaptationSSE2(
const OouraFft& ooura_fft,
int num_partitions,
int x_fft_buf_block_pos,
float x_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
float e_fft[2][PART_LEN1],
float h_fft_buf[2][kExtendedNumPartitions * PART_LEN1]) {
float fft[PART_LEN2];
int i, j;
for (i = 0; i < num_partitions; i++) {
int xPos = (i + x_fft_buf_block_pos) * (PART_LEN1);
int pos = i * PART_LEN1;
// Check for wrap
if (i + x_fft_buf_block_pos >= num_partitions) {
xPos -= num_partitions * PART_LEN1;
}
// Process the whole array...
for (j = 0; j < PART_LEN; j += 4) {
// Load x_fft_buf and e_fft.
const __m128 x_fft_buf_re = _mm_loadu_ps(&x_fft_buf[0][xPos + j]);
const __m128 x_fft_buf_im = _mm_loadu_ps(&x_fft_buf[1][xPos + j]);
const __m128 e_fft_re = _mm_loadu_ps(&e_fft[0][j]);
const __m128 e_fft_im = _mm_loadu_ps(&e_fft[1][j]);
// Calculate the product of conjugate(x_fft_buf) by e_fft.
// re(conjugate(a) * b) = aRe * bRe + aIm * bIm
// im(conjugate(a) * b)= aRe * bIm - aIm * bRe
const __m128 a = _mm_mul_ps(x_fft_buf_re, e_fft_re);
const __m128 b = _mm_mul_ps(x_fft_buf_im, e_fft_im);
const __m128 c = _mm_mul_ps(x_fft_buf_re, e_fft_im);
const __m128 d = _mm_mul_ps(x_fft_buf_im, e_fft_re);
const __m128 e = _mm_add_ps(a, b);
const __m128 f = _mm_sub_ps(c, d);
// Interleave real and imaginary parts.
const __m128 g = _mm_unpacklo_ps(e, f);
const __m128 h = _mm_unpackhi_ps(e, f);
// Store
_mm_storeu_ps(&fft[2 * j + 0], g);
_mm_storeu_ps(&fft[2 * j + 4], h);
}
// ... and fixup the first imaginary entry.
fft[1] =
MulRe(x_fft_buf[0][xPos + PART_LEN], -x_fft_buf[1][xPos + PART_LEN],
e_fft[0][PART_LEN], e_fft[1][PART_LEN]);
ooura_fft.InverseFft(fft);
memset(fft + PART_LEN, 0, sizeof(float) * PART_LEN);
// fft scaling
{
float scale = 2.0f / PART_LEN2;
const __m128 scale_ps = _mm_load_ps1(&scale);
for (j = 0; j < PART_LEN; j += 4) {
const __m128 fft_ps = _mm_loadu_ps(&fft[j]);
const __m128 fft_scale = _mm_mul_ps(fft_ps, scale_ps);
_mm_storeu_ps(&fft[j], fft_scale);
}
}
ooura_fft.Fft(fft);
{
float wt1 = h_fft_buf[1][pos];
h_fft_buf[0][pos + PART_LEN] += fft[1];
for (j = 0; j < PART_LEN; j += 4) {
__m128 wtBuf_re = _mm_loadu_ps(&h_fft_buf[0][pos + j]);
__m128 wtBuf_im = _mm_loadu_ps(&h_fft_buf[1][pos + j]);
const __m128 fft0 = _mm_loadu_ps(&fft[2 * j + 0]);
const __m128 fft4 = _mm_loadu_ps(&fft[2 * j + 4]);
const __m128 fft_re =
_mm_shuffle_ps(fft0, fft4, _MM_SHUFFLE(2, 0, 2, 0));
const __m128 fft_im =
_mm_shuffle_ps(fft0, fft4, _MM_SHUFFLE(3, 1, 3, 1));
wtBuf_re = _mm_add_ps(wtBuf_re, fft_re);
wtBuf_im = _mm_add_ps(wtBuf_im, fft_im);
_mm_storeu_ps(&h_fft_buf[0][pos + j], wtBuf_re);
_mm_storeu_ps(&h_fft_buf[1][pos + j], wtBuf_im);
}
h_fft_buf[1][pos] = wt1;
}
}
}
static __m128 mm_pow_ps(__m128 a, __m128 b) {
// a^b = exp2(b * log2(a))
// exp2(x) and log2(x) are calculated using polynomial approximations.
__m128 log2_a, b_log2_a, a_exp_b;
// Calculate log2(x), x = a.
{
// To calculate log2(x), we decompose x like this:
// x = y * 2^n
// n is an integer
// y is in the [1.0, 2.0) range
//
// log2(x) = log2(y) + n
// n can be evaluated by playing with float representation.
// log2(y) in a small range can be approximated, this code uses an order
// five polynomial approximation. The coefficients have been
// estimated with the Remez algorithm and the resulting
// polynomial has a maximum relative error of 0.00086%.
// Compute n.
// This is done by masking the exponent, shifting it into the top bit of
// the mantissa, putting eight into the biased exponent (to shift/
// compensate the fact that the exponent has been shifted in the top/
// fractional part and finally getting rid of the implicit leading one
// from the mantissa by substracting it out.
static const ALIGN16_BEG int float_exponent_mask[4] ALIGN16_END = {
0x7F800000, 0x7F800000, 0x7F800000, 0x7F800000};
static const ALIGN16_BEG int eight_biased_exponent[4] ALIGN16_END = {
0x43800000, 0x43800000, 0x43800000, 0x43800000};
static const ALIGN16_BEG int implicit_leading_one[4] ALIGN16_END = {
0x43BF8000, 0x43BF8000, 0x43BF8000, 0x43BF8000};
static const int shift_exponent_into_top_mantissa = 8;
const __m128 two_n =
_mm_and_ps(a, *(reinterpret_cast<const __m128*>(float_exponent_mask)));
const __m128 n_1 = _mm_castsi128_ps(_mm_srli_epi32(
_mm_castps_si128(two_n), shift_exponent_into_top_mantissa));
const __m128 n_0 = _mm_or_ps(
n_1, *(reinterpret_cast<const __m128*>(eight_biased_exponent)));
const __m128 n = _mm_sub_ps(
n_0, *(reinterpret_cast<const __m128*>(implicit_leading_one)));
// Compute y.
static const ALIGN16_BEG int mantissa_mask[4] ALIGN16_END = {
0x007FFFFF, 0x007FFFFF, 0x007FFFFF, 0x007FFFFF};
static const ALIGN16_BEG int zero_biased_exponent_is_one[4] ALIGN16_END = {
0x3F800000, 0x3F800000, 0x3F800000, 0x3F800000};
const __m128 mantissa =
_mm_and_ps(a, *(reinterpret_cast<const __m128*>(mantissa_mask)));
const __m128 y = _mm_or_ps(
mantissa,
*(reinterpret_cast<const __m128*>(zero_biased_exponent_is_one)));
// Approximate log2(y) ~= (y - 1) * pol5(y).
// pol5(y) = C5 * y^5 + C4 * y^4 + C3 * y^3 + C2 * y^2 + C1 * y + C0
static const ALIGN16_BEG float ALIGN16_END C5[4] = {
-3.4436006e-2f, -3.4436006e-2f, -3.4436006e-2f, -3.4436006e-2f};
static const ALIGN16_BEG float ALIGN16_END C4[4] = {
3.1821337e-1f, 3.1821337e-1f, 3.1821337e-1f, 3.1821337e-1f};
static const ALIGN16_BEG float ALIGN16_END C3[4] = {
-1.2315303f, -1.2315303f, -1.2315303f, -1.2315303f};
static const ALIGN16_BEG float ALIGN16_END C2[4] = {2.5988452f, 2.5988452f,
2.5988452f, 2.5988452f};
static const ALIGN16_BEG float ALIGN16_END C1[4] = {
-3.3241990f, -3.3241990f, -3.3241990f, -3.3241990f};
static const ALIGN16_BEG float ALIGN16_END C0[4] = {3.1157899f, 3.1157899f,
3.1157899f, 3.1157899f};
const __m128 pol5_y_0 =
_mm_mul_ps(y, *(reinterpret_cast<const __m128*>(C5)));
const __m128 pol5_y_1 =
_mm_add_ps(pol5_y_0, *(reinterpret_cast<const __m128*>(C4)));
const __m128 pol5_y_2 = _mm_mul_ps(pol5_y_1, y);
const __m128 pol5_y_3 =
_mm_add_ps(pol5_y_2, *(reinterpret_cast<const __m128*>(C3)));
const __m128 pol5_y_4 = _mm_mul_ps(pol5_y_3, y);
const __m128 pol5_y_5 =
_mm_add_ps(pol5_y_4, *(reinterpret_cast<const __m128*>(C2)));
const __m128 pol5_y_6 = _mm_mul_ps(pol5_y_5, y);
const __m128 pol5_y_7 =
_mm_add_ps(pol5_y_6, *(reinterpret_cast<const __m128*>(C1)));
const __m128 pol5_y_8 = _mm_mul_ps(pol5_y_7, y);
const __m128 pol5_y =
_mm_add_ps(pol5_y_8, *(reinterpret_cast<const __m128*>(C0)));
const __m128 y_minus_one = _mm_sub_ps(
y, *(reinterpret_cast<const __m128*>(zero_biased_exponent_is_one)));
const __m128 log2_y = _mm_mul_ps(y_minus_one, pol5_y);
// Combine parts.
log2_a = _mm_add_ps(n, log2_y);
}
// b * log2(a)
b_log2_a = _mm_mul_ps(b, log2_a);
// Calculate exp2(x), x = b * log2(a).
{
// To calculate 2^x, we decompose x like this:
// x = n + y
// n is an integer, the value of x - 0.5 rounded down, therefore
// y is in the [0.5, 1.5) range
//
// 2^x = 2^n * 2^y
// 2^n can be evaluated by playing with float representation.
// 2^y in a small range can be approximated, this code uses an order two
// polynomial approximation. The coefficients have been estimated
// with the Remez algorithm and the resulting polynomial has a
// maximum relative error of 0.17%.
// To avoid over/underflow, we reduce the range of input to ]-127, 129].
static const ALIGN16_BEG float max_input[4] ALIGN16_END = {129.f, 129.f,
129.f, 129.f};
static const ALIGN16_BEG float min_input[4] ALIGN16_END = {
-126.99999f, -126.99999f, -126.99999f, -126.99999f};
const __m128 x_min =
_mm_min_ps(b_log2_a, *(reinterpret_cast<const __m128*>(max_input)));
const __m128 x_max =
_mm_max_ps(x_min, *(reinterpret_cast<const __m128*>(min_input)));
// Compute n.
static const ALIGN16_BEG float half[4] ALIGN16_END = {0.5f, 0.5f, 0.5f,
0.5f};
const __m128 x_minus_half =
_mm_sub_ps(x_max, *(reinterpret_cast<const __m128*>(half)));
const __m128i x_minus_half_floor = _mm_cvtps_epi32(x_minus_half);
// Compute 2^n.
static const ALIGN16_BEG int float_exponent_bias[4] ALIGN16_END = {
127, 127, 127, 127};
static const int float_exponent_shift = 23;
const __m128i two_n_exponent =
_mm_add_epi32(x_minus_half_floor,
*(reinterpret_cast<const __m128i*>(float_exponent_bias)));
const __m128 two_n =
_mm_castsi128_ps(_mm_slli_epi32(two_n_exponent, float_exponent_shift));
// Compute y.
const __m128 y = _mm_sub_ps(x_max, _mm_cvtepi32_ps(x_minus_half_floor));
// Approximate 2^y ~= C2 * y^2 + C1 * y + C0.
static const ALIGN16_BEG float C2[4] ALIGN16_END = {
3.3718944e-1f, 3.3718944e-1f, 3.3718944e-1f, 3.3718944e-1f};
static const ALIGN16_BEG float C1[4] ALIGN16_END = {
6.5763628e-1f, 6.5763628e-1f, 6.5763628e-1f, 6.5763628e-1f};
static const ALIGN16_BEG float C0[4] ALIGN16_END = {1.0017247f, 1.0017247f,
1.0017247f, 1.0017247f};
const __m128 exp2_y_0 =
_mm_mul_ps(y, *(reinterpret_cast<const __m128*>(C2)));
const __m128 exp2_y_1 =
_mm_add_ps(exp2_y_0, *(reinterpret_cast<const __m128*>(C1)));
const __m128 exp2_y_2 = _mm_mul_ps(exp2_y_1, y);
const __m128 exp2_y =
_mm_add_ps(exp2_y_2, *(reinterpret_cast<const __m128*>(C0)));
// Combine parts.
a_exp_b = _mm_mul_ps(exp2_y, two_n);
}
return a_exp_b;
}
static void OverdriveSSE2(float overdrive_scaling,
float hNlFb,
float hNl[PART_LEN1]) {
int i;
const __m128 vec_hNlFb = _mm_set1_ps(hNlFb);
const __m128 vec_one = _mm_set1_ps(1.0f);
const __m128 vec_overdrive_scaling = _mm_set1_ps(overdrive_scaling);
// vectorized code (four at once)
for (i = 0; i + 3 < PART_LEN1; i += 4) {
// Weight subbands
__m128 vec_hNl = _mm_loadu_ps(&hNl[i]);
const __m128 vec_weightCurve = _mm_loadu_ps(&WebRtcAec_weightCurve[i]);
const __m128 bigger = _mm_cmpgt_ps(vec_hNl, vec_hNlFb);
const __m128 vec_weightCurve_hNlFb = _mm_mul_ps(vec_weightCurve, vec_hNlFb);
const __m128 vec_one_weightCurve = _mm_sub_ps(vec_one, vec_weightCurve);
const __m128 vec_one_weightCurve_hNl =
_mm_mul_ps(vec_one_weightCurve, vec_hNl);
const __m128 vec_if0 = _mm_andnot_ps(bigger, vec_hNl);
const __m128 vec_if1 = _mm_and_ps(
bigger, _mm_add_ps(vec_weightCurve_hNlFb, vec_one_weightCurve_hNl));
vec_hNl = _mm_or_ps(vec_if0, vec_if1);
const __m128 vec_overDriveCurve =
_mm_loadu_ps(&WebRtcAec_overDriveCurve[i]);
const __m128 vec_overDriveSm_overDriveCurve =
_mm_mul_ps(vec_overdrive_scaling, vec_overDriveCurve);
vec_hNl = mm_pow_ps(vec_hNl, vec_overDriveSm_overDriveCurve);
_mm_storeu_ps(&hNl[i], vec_hNl);
}
// scalar code for the remaining items.
for (; i < PART_LEN1; i++) {
// Weight subbands
if (hNl[i] > hNlFb) {
hNl[i] = WebRtcAec_weightCurve[i] * hNlFb +
(1 - WebRtcAec_weightCurve[i]) * hNl[i];
}
hNl[i] = powf(hNl[i], overdrive_scaling * WebRtcAec_overDriveCurve[i]);
}
}
static void SuppressSSE2(const float hNl[PART_LEN1], float efw[2][PART_LEN1]) {
int i;
const __m128 vec_minus_one = _mm_set1_ps(-1.0f);
// vectorized code (four at once)
for (i = 0; i + 3 < PART_LEN1; i += 4) {
// Suppress error signal
__m128 vec_hNl = _mm_loadu_ps(&hNl[i]);
__m128 vec_efw_re = _mm_loadu_ps(&efw[0][i]);
__m128 vec_efw_im = _mm_loadu_ps(&efw[1][i]);
vec_efw_re = _mm_mul_ps(vec_efw_re, vec_hNl);
vec_efw_im = _mm_mul_ps(vec_efw_im, vec_hNl);
// Ooura fft returns incorrect sign on imaginary component. It matters
// here because we are making an additive change with comfort noise.
vec_efw_im = _mm_mul_ps(vec_efw_im, vec_minus_one);
_mm_storeu_ps(&efw[0][i], vec_efw_re);
_mm_storeu_ps(&efw[1][i], vec_efw_im);
}
// scalar code for the remaining items.
for (; i < PART_LEN1; i++) {
// Suppress error signal
efw[0][i] *= hNl[i];
efw[1][i] *= hNl[i];
// Ooura fft returns incorrect sign on imaginary component. It matters
// here because we are making an additive change with comfort noise.
efw[1][i] *= -1;
}
}
__inline static void _mm_add_ps_4x1(__m128 sum, float* dst) {
// A+B C+D
sum = _mm_add_ps(sum, _mm_shuffle_ps(sum, sum, _MM_SHUFFLE(0, 0, 3, 2)));
// A+B+C+D A+B+C+D
sum = _mm_add_ps(sum, _mm_shuffle_ps(sum, sum, _MM_SHUFFLE(1, 1, 1, 1)));
_mm_store_ss(dst, sum);
}
static int PartitionDelaySSE2(
int num_partitions,
float h_fft_buf[2][kExtendedNumPartitions * PART_LEN1]) {
// Measures the energy in each filter partition and returns the partition with
// highest energy.
// TODO(bjornv): Spread computational cost by computing one partition per
// block?
float wfEnMax = 0;
int i;
int delay = 0;
for (i = 0; i < num_partitions; i++) {
int j;
int pos = i * PART_LEN1;
float wfEn = 0;
__m128 vec_wfEn = _mm_set1_ps(0.0f);
// vectorized code (four at once)
for (j = 0; j + 3 < PART_LEN1; j += 4) {
const __m128 vec_wfBuf0 = _mm_loadu_ps(&h_fft_buf[0][pos + j]);
const __m128 vec_wfBuf1 = _mm_loadu_ps(&h_fft_buf[1][pos + j]);
vec_wfEn = _mm_add_ps(vec_wfEn, _mm_mul_ps(vec_wfBuf0, vec_wfBuf0));
vec_wfEn = _mm_add_ps(vec_wfEn, _mm_mul_ps(vec_wfBuf1, vec_wfBuf1));
}
_mm_add_ps_4x1(vec_wfEn, &wfEn);
// scalar code for the remaining items.
for (; j < PART_LEN1; j++) {
wfEn += h_fft_buf[0][pos + j] * h_fft_buf[0][pos + j] +
h_fft_buf[1][pos + j] * h_fft_buf[1][pos + j];
}
if (wfEn > wfEnMax) {
wfEnMax = wfEn;
delay = i;
}
}
return delay;
}
// Updates the following smoothed Power Spectral Densities (PSD):
// - sd : near-end
// - se : residual echo
// - sx : far-end
// - sde : cross-PSD of near-end and residual echo
// - sxd : cross-PSD of near-end and far-end
//
// In addition to updating the PSDs, also the filter diverge state is determined
// upon actions are taken.
static void UpdateCoherenceSpectraSSE2(int mult,
bool extended_filter_enabled,
float efw[2][PART_LEN1],
float dfw[2][PART_LEN1],
float xfw[2][PART_LEN1],
CoherenceState* coherence_state,
short* filter_divergence_state,
int* extreme_filter_divergence) {
// Power estimate smoothing coefficients.
const float* ptrGCoh =
extended_filter_enabled
? WebRtcAec_kExtendedSmoothingCoefficients[mult - 1]
: WebRtcAec_kNormalSmoothingCoefficients[mult - 1];
int i;
float sdSum = 0, seSum = 0;
const __m128 vec_15 = _mm_set1_ps(WebRtcAec_kMinFarendPSD);
const __m128 vec_GCoh0 = _mm_set1_ps(ptrGCoh[0]);
const __m128 vec_GCoh1 = _mm_set1_ps(ptrGCoh[1]);
__m128 vec_sdSum = _mm_set1_ps(0.0f);
__m128 vec_seSum = _mm_set1_ps(0.0f);
for (i = 0; i + 3 < PART_LEN1; i += 4) {
const __m128 vec_dfw0 = _mm_loadu_ps(&dfw[0][i]);
const __m128 vec_dfw1 = _mm_loadu_ps(&dfw[1][i]);
const __m128 vec_efw0 = _mm_loadu_ps(&efw[0][i]);
const __m128 vec_efw1 = _mm_loadu_ps(&efw[1][i]);
const __m128 vec_xfw0 = _mm_loadu_ps(&xfw[0][i]);
const __m128 vec_xfw1 = _mm_loadu_ps(&xfw[1][i]);
__m128 vec_sd =
_mm_mul_ps(_mm_loadu_ps(&coherence_state->sd[i]), vec_GCoh0);
__m128 vec_se =
_mm_mul_ps(_mm_loadu_ps(&coherence_state->se[i]), vec_GCoh0);
__m128 vec_sx =
_mm_mul_ps(_mm_loadu_ps(&coherence_state->sx[i]), vec_GCoh0);
__m128 vec_dfw_sumsq = _mm_mul_ps(vec_dfw0, vec_dfw0);
__m128 vec_efw_sumsq = _mm_mul_ps(vec_efw0, vec_efw0);
__m128 vec_xfw_sumsq = _mm_mul_ps(vec_xfw0, vec_xfw0);
vec_dfw_sumsq = _mm_add_ps(vec_dfw_sumsq, _mm_mul_ps(vec_dfw1, vec_dfw1));
vec_efw_sumsq = _mm_add_ps(vec_efw_sumsq, _mm_mul_ps(vec_efw1, vec_efw1));
vec_xfw_sumsq = _mm_add_ps(vec_xfw_sumsq, _mm_mul_ps(vec_xfw1, vec_xfw1));
vec_xfw_sumsq = _mm_max_ps(vec_xfw_sumsq, vec_15);
vec_sd = _mm_add_ps(vec_sd, _mm_mul_ps(vec_dfw_sumsq, vec_GCoh1));
vec_se = _mm_add_ps(vec_se, _mm_mul_ps(vec_efw_sumsq, vec_GCoh1));
vec_sx = _mm_add_ps(vec_sx, _mm_mul_ps(vec_xfw_sumsq, vec_GCoh1));
_mm_storeu_ps(&coherence_state->sd[i], vec_sd);
_mm_storeu_ps(&coherence_state->se[i], vec_se);
_mm_storeu_ps(&coherence_state->sx[i], vec_sx);
{
const __m128 vec_3210 = _mm_loadu_ps(&coherence_state->sde[i][0]);
const __m128 vec_7654 = _mm_loadu_ps(&coherence_state->sde[i + 2][0]);
__m128 vec_a =
_mm_shuffle_ps(vec_3210, vec_7654, _MM_SHUFFLE(2, 0, 2, 0));
__m128 vec_b =
_mm_shuffle_ps(vec_3210, vec_7654, _MM_SHUFFLE(3, 1, 3, 1));
__m128 vec_dfwefw0011 = _mm_mul_ps(vec_dfw0, vec_efw0);
__m128 vec_dfwefw0110 = _mm_mul_ps(vec_dfw0, vec_efw1);
vec_a = _mm_mul_ps(vec_a, vec_GCoh0);
vec_b = _mm_mul_ps(vec_b, vec_GCoh0);
vec_dfwefw0011 =
_mm_add_ps(vec_dfwefw0011, _mm_mul_ps(vec_dfw1, vec_efw1));
vec_dfwefw0110 =
_mm_sub_ps(vec_dfwefw0110, _mm_mul_ps(vec_dfw1, vec_efw0));
vec_a = _mm_add_ps(vec_a, _mm_mul_ps(vec_dfwefw0011, vec_GCoh1));
vec_b = _mm_add_ps(vec_b, _mm_mul_ps(vec_dfwefw0110, vec_GCoh1));
_mm_storeu_ps(&coherence_state->sde[i][0], _mm_unpacklo_ps(vec_a, vec_b));
_mm_storeu_ps(&coherence_state->sde[i + 2][0],
_mm_unpackhi_ps(vec_a, vec_b));
}
{
const __m128 vec_3210 = _mm_loadu_ps(&coherence_state->sxd[i][0]);
const __m128 vec_7654 = _mm_loadu_ps(&coherence_state->sxd[i + 2][0]);
__m128 vec_a =
_mm_shuffle_ps(vec_3210, vec_7654, _MM_SHUFFLE(2, 0, 2, 0));
__m128 vec_b =
_mm_shuffle_ps(vec_3210, vec_7654, _MM_SHUFFLE(3, 1, 3, 1));
__m128 vec_dfwxfw0011 = _mm_mul_ps(vec_dfw0, vec_xfw0);
__m128 vec_dfwxfw0110 = _mm_mul_ps(vec_dfw0, vec_xfw1);
vec_a = _mm_mul_ps(vec_a, vec_GCoh0);
vec_b = _mm_mul_ps(vec_b, vec_GCoh0);
vec_dfwxfw0011 =
_mm_add_ps(vec_dfwxfw0011, _mm_mul_ps(vec_dfw1, vec_xfw1));
vec_dfwxfw0110 =
_mm_sub_ps(vec_dfwxfw0110, _mm_mul_ps(vec_dfw1, vec_xfw0));
vec_a = _mm_add_ps(vec_a, _mm_mul_ps(vec_dfwxfw0011, vec_GCoh1));
vec_b = _mm_add_ps(vec_b, _mm_mul_ps(vec_dfwxfw0110, vec_GCoh1));
_mm_storeu_ps(&coherence_state->sxd[i][0], _mm_unpacklo_ps(vec_a, vec_b));
_mm_storeu_ps(&coherence_state->sxd[i + 2][0],
_mm_unpackhi_ps(vec_a, vec_b));
}
vec_sdSum = _mm_add_ps(vec_sdSum, vec_sd);
vec_seSum = _mm_add_ps(vec_seSum, vec_se);
}
_mm_add_ps_4x1(vec_sdSum, &sdSum);
_mm_add_ps_4x1(vec_seSum, &seSum);
for (; i < PART_LEN1; i++) {
coherence_state->sd[i] =
ptrGCoh[0] * coherence_state->sd[i] +
ptrGCoh[1] * (dfw[0][i] * dfw[0][i] + dfw[1][i] * dfw[1][i]);
coherence_state->se[i] =
ptrGCoh[0] * coherence_state->se[i] +
ptrGCoh[1] * (efw[0][i] * efw[0][i] + efw[1][i] * efw[1][i]);
// We threshold here to protect against the ill-effects of a zero farend.
// The threshold is not arbitrarily chosen, but balances protection and
// adverse interaction with the algorithm's tuning.
// TODO(bjornv): investigate further why this is so sensitive.
coherence_state->sx[i] =
ptrGCoh[0] * coherence_state->sx[i] +
ptrGCoh[1] *
WEBRTC_SPL_MAX(xfw[0][i] * xfw[0][i] + xfw[1][i] * xfw[1][i],
WebRtcAec_kMinFarendPSD);
coherence_state->sde[i][0] =
ptrGCoh[0] * coherence_state->sde[i][0] +
ptrGCoh[1] * (dfw[0][i] * efw[0][i] + dfw[1][i] * efw[1][i]);
coherence_state->sde[i][1] =
ptrGCoh[0] * coherence_state->sde[i][1] +
ptrGCoh[1] * (dfw[0][i] * efw[1][i] - dfw[1][i] * efw[0][i]);
coherence_state->sxd[i][0] =
ptrGCoh[0] * coherence_state->sxd[i][0] +
ptrGCoh[1] * (dfw[0][i] * xfw[0][i] + dfw[1][i] * xfw[1][i]);
coherence_state->sxd[i][1] =
ptrGCoh[0] * coherence_state->sxd[i][1] +
ptrGCoh[1] * (dfw[0][i] * xfw[1][i] - dfw[1][i] * xfw[0][i]);
sdSum += coherence_state->sd[i];
seSum += coherence_state->se[i];
}
// Divergent filter safeguard update.
*filter_divergence_state =
(*filter_divergence_state ? 1.05f : 1.0f) * seSum > sdSum;
// Signal extreme filter divergence if the error is significantly larger
// than the nearend (13 dB).
*extreme_filter_divergence = (seSum > (19.95f * sdSum));
}
// Window time domain data to be used by the fft.
static void WindowDataSSE2(float* x_windowed, const float* x) {
int i;
for (i = 0; i < PART_LEN; i += 4) {
const __m128 vec_Buf1 = _mm_loadu_ps(&x[i]);
const __m128 vec_Buf2 = _mm_loadu_ps(&x[PART_LEN + i]);
const __m128 vec_sqrtHanning = _mm_load_ps(&WebRtcAec_sqrtHanning[i]);
// A B C D
__m128 vec_sqrtHanning_rev =
_mm_loadu_ps(&WebRtcAec_sqrtHanning[PART_LEN - i - 3]);
// D C B A
vec_sqrtHanning_rev = _mm_shuffle_ps(
vec_sqrtHanning_rev, vec_sqrtHanning_rev, _MM_SHUFFLE(0, 1, 2, 3));
_mm_storeu_ps(&x_windowed[i], _mm_mul_ps(vec_Buf1, vec_sqrtHanning));
_mm_storeu_ps(&x_windowed[PART_LEN + i],
_mm_mul_ps(vec_Buf2, vec_sqrtHanning_rev));
}
}
// Puts fft output data into a complex valued array.
static void StoreAsComplexSSE2(const float* data,
float data_complex[2][PART_LEN1]) {
int i;
for (i = 0; i < PART_LEN; i += 4) {
const __m128 vec_fft0 = _mm_loadu_ps(&data[2 * i]);
const __m128 vec_fft4 = _mm_loadu_ps(&data[2 * i + 4]);
const __m128 vec_a =
_mm_shuffle_ps(vec_fft0, vec_fft4, _MM_SHUFFLE(2, 0, 2, 0));
const __m128 vec_b =
_mm_shuffle_ps(vec_fft0, vec_fft4, _MM_SHUFFLE(3, 1, 3, 1));
_mm_storeu_ps(&data_complex[0][i], vec_a);
_mm_storeu_ps(&data_complex[1][i], vec_b);
}
// fix beginning/end values
data_complex[1][0] = 0;
data_complex[1][PART_LEN] = 0;
data_complex[0][0] = data[0];
data_complex[0][PART_LEN] = data[1];
}
static void ComputeCoherenceSSE2(const CoherenceState* coherence_state,
float* cohde,
float* cohxd) {
int i;
{
const __m128 vec_1eminus10 = _mm_set1_ps(1e-10f);
// Subband coherence
for (i = 0; i + 3 < PART_LEN1; i += 4) {
const __m128 vec_sd = _mm_loadu_ps(&coherence_state->sd[i]);
const __m128 vec_se = _mm_loadu_ps(&coherence_state->se[i]);
const __m128 vec_sx = _mm_loadu_ps(&coherence_state->sx[i]);
const __m128 vec_sdse =
_mm_add_ps(vec_1eminus10, _mm_mul_ps(vec_sd, vec_se));
const __m128 vec_sdsx =
_mm_add_ps(vec_1eminus10, _mm_mul_ps(vec_sd, vec_sx));
const __m128 vec_sde_3210 = _mm_loadu_ps(&coherence_state->sde[i][0]);
const __m128 vec_sde_7654 = _mm_loadu_ps(&coherence_state->sde[i + 2][0]);
const __m128 vec_sxd_3210 = _mm_loadu_ps(&coherence_state->sxd[i][0]);
const __m128 vec_sxd_7654 = _mm_loadu_ps(&coherence_state->sxd[i + 2][0]);
const __m128 vec_sde_0 =
_mm_shuffle_ps(vec_sde_3210, vec_sde_7654, _MM_SHUFFLE(2, 0, 2, 0));
const __m128 vec_sde_1 =
_mm_shuffle_ps(vec_sde_3210, vec_sde_7654, _MM_SHUFFLE(3, 1, 3, 1));
const __m128 vec_sxd_0 =
_mm_shuffle_ps(vec_sxd_3210, vec_sxd_7654, _MM_SHUFFLE(2, 0, 2, 0));
const __m128 vec_sxd_1 =
_mm_shuffle_ps(vec_sxd_3210, vec_sxd_7654, _MM_SHUFFLE(3, 1, 3, 1));
__m128 vec_cohde = _mm_mul_ps(vec_sde_0, vec_sde_0);
__m128 vec_cohxd = _mm_mul_ps(vec_sxd_0, vec_sxd_0);
vec_cohde = _mm_add_ps(vec_cohde, _mm_mul_ps(vec_sde_1, vec_sde_1));
vec_cohde = _mm_div_ps(vec_cohde, vec_sdse);
vec_cohxd = _mm_add_ps(vec_cohxd, _mm_mul_ps(vec_sxd_1, vec_sxd_1));
vec_cohxd = _mm_div_ps(vec_cohxd, vec_sdsx);
_mm_storeu_ps(&cohde[i], vec_cohde);
_mm_storeu_ps(&cohxd[i], vec_cohxd);
}
// scalar code for the remaining items.
for (; i < PART_LEN1; i++) {
cohde[i] = (coherence_state->sde[i][0] * coherence_state->sde[i][0] +
coherence_state->sde[i][1] * coherence_state->sde[i][1]) /
(coherence_state->sd[i] * coherence_state->se[i] + 1e-10f);
cohxd[i] = (coherence_state->sxd[i][0] * coherence_state->sxd[i][0] +
coherence_state->sxd[i][1] * coherence_state->sxd[i][1]) /
(coherence_state->sx[i] * coherence_state->sd[i] + 1e-10f);
}
}
}
void WebRtcAec_InitAec_SSE2(void) {
WebRtcAec_FilterFar = FilterFarSSE2;
WebRtcAec_ScaleErrorSignal = ScaleErrorSignalSSE2;
WebRtcAec_FilterAdaptation = FilterAdaptationSSE2;
WebRtcAec_Overdrive = OverdriveSSE2;
WebRtcAec_Suppress = SuppressSSE2;
WebRtcAec_ComputeCoherence = ComputeCoherenceSSE2;
WebRtcAec_UpdateCoherenceSpectra = UpdateCoherenceSpectraSSE2;
WebRtcAec_StoreAsComplex = StoreAsComplexSSE2;
WebRtcAec_PartitionDelay = PartitionDelaySSE2;
WebRtcAec_WindowData = WindowDataSSE2;
}
} // namespace webrtc