1 /*
2 * Copyright (c) 2011 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
11 /*
12 * The core AEC algorithm, SSE2 version of speed-critical functions.
13 */
14
15 #include <emmintrin.h>
16 #include <math.h>
17 #include <string.h> // memset
18
19 #include "webrtc/common_audio/signal_processing/include/signal_processing_library.h"
20 #include "webrtc/modules/audio_processing/aec/aec_common.h"
21 #include "webrtc/modules/audio_processing/aec/aec_core_internal.h"
22 #include "webrtc/modules/audio_processing/aec/aec_rdft.h"
23
MulRe(float aRe,float aIm,float bRe,float bIm)24 __inline static float MulRe(float aRe, float aIm, float bRe, float bIm) {
25 return aRe * bRe - aIm * bIm;
26 }
27
MulIm(float aRe,float aIm,float bRe,float bIm)28 __inline static float MulIm(float aRe, float aIm, float bRe, float bIm) {
29 return aRe * bIm + aIm * bRe;
30 }
31
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])32 static void FilterFarSSE2(
33 int num_partitions,
34 int x_fft_buf_block_pos,
35 float x_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
36 float h_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
37 float y_fft[2][PART_LEN1]) {
38
39 int i;
40 for (i = 0; i < num_partitions; i++) {
41 int j;
42 int xPos = (i + x_fft_buf_block_pos) * PART_LEN1;
43 int pos = i * PART_LEN1;
44 // Check for wrap
45 if (i + x_fft_buf_block_pos >= num_partitions) {
46 xPos -= num_partitions * (PART_LEN1);
47 }
48
49 // vectorized code (four at once)
50 for (j = 0; j + 3 < PART_LEN1; j += 4) {
51 const __m128 x_fft_buf_re = _mm_loadu_ps(&x_fft_buf[0][xPos + j]);
52 const __m128 x_fft_buf_im = _mm_loadu_ps(&x_fft_buf[1][xPos + j]);
53 const __m128 h_fft_buf_re = _mm_loadu_ps(&h_fft_buf[0][pos + j]);
54 const __m128 h_fft_buf_im = _mm_loadu_ps(&h_fft_buf[1][pos + j]);
55 const __m128 y_fft_re = _mm_loadu_ps(&y_fft[0][j]);
56 const __m128 y_fft_im = _mm_loadu_ps(&y_fft[1][j]);
57 const __m128 a = _mm_mul_ps(x_fft_buf_re, h_fft_buf_re);
58 const __m128 b = _mm_mul_ps(x_fft_buf_im, h_fft_buf_im);
59 const __m128 c = _mm_mul_ps(x_fft_buf_re, h_fft_buf_im);
60 const __m128 d = _mm_mul_ps(x_fft_buf_im, h_fft_buf_re);
61 const __m128 e = _mm_sub_ps(a, b);
62 const __m128 f = _mm_add_ps(c, d);
63 const __m128 g = _mm_add_ps(y_fft_re, e);
64 const __m128 h = _mm_add_ps(y_fft_im, f);
65 _mm_storeu_ps(&y_fft[0][j], g);
66 _mm_storeu_ps(&y_fft[1][j], h);
67 }
68 // scalar code for the remaining items.
69 for (; j < PART_LEN1; j++) {
70 y_fft[0][j] += MulRe(x_fft_buf[0][xPos + j],
71 x_fft_buf[1][xPos + j],
72 h_fft_buf[0][pos + j],
73 h_fft_buf[1][pos + j]);
74 y_fft[1][j] += MulIm(x_fft_buf[0][xPos + j],
75 x_fft_buf[1][xPos + j],
76 h_fft_buf[0][pos + j],
77 h_fft_buf[1][pos + j]);
78 }
79 }
80 }
81
ScaleErrorSignalSSE2(int extended_filter_enabled,float normal_mu,float normal_error_threshold,float x_pow[PART_LEN1],float ef[2][PART_LEN1])82 static void ScaleErrorSignalSSE2(int extended_filter_enabled,
83 float normal_mu,
84 float normal_error_threshold,
85 float x_pow[PART_LEN1],
86 float ef[2][PART_LEN1]) {
87 const __m128 k1e_10f = _mm_set1_ps(1e-10f);
88 const __m128 kMu = extended_filter_enabled ? _mm_set1_ps(kExtendedMu)
89 : _mm_set1_ps(normal_mu);
90 const __m128 kThresh = extended_filter_enabled
91 ? _mm_set1_ps(kExtendedErrorThreshold)
92 : _mm_set1_ps(normal_error_threshold);
93
94 int i;
95 // vectorized code (four at once)
96 for (i = 0; i + 3 < PART_LEN1; i += 4) {
97 const __m128 x_pow_local = _mm_loadu_ps(&x_pow[i]);
98 const __m128 ef_re_base = _mm_loadu_ps(&ef[0][i]);
99 const __m128 ef_im_base = _mm_loadu_ps(&ef[1][i]);
100
101 const __m128 xPowPlus = _mm_add_ps(x_pow_local, k1e_10f);
102 __m128 ef_re = _mm_div_ps(ef_re_base, xPowPlus);
103 __m128 ef_im = _mm_div_ps(ef_im_base, xPowPlus);
104 const __m128 ef_re2 = _mm_mul_ps(ef_re, ef_re);
105 const __m128 ef_im2 = _mm_mul_ps(ef_im, ef_im);
106 const __m128 ef_sum2 = _mm_add_ps(ef_re2, ef_im2);
107 const __m128 absEf = _mm_sqrt_ps(ef_sum2);
108 const __m128 bigger = _mm_cmpgt_ps(absEf, kThresh);
109 __m128 absEfPlus = _mm_add_ps(absEf, k1e_10f);
110 const __m128 absEfInv = _mm_div_ps(kThresh, absEfPlus);
111 __m128 ef_re_if = _mm_mul_ps(ef_re, absEfInv);
112 __m128 ef_im_if = _mm_mul_ps(ef_im, absEfInv);
113 ef_re_if = _mm_and_ps(bigger, ef_re_if);
114 ef_im_if = _mm_and_ps(bigger, ef_im_if);
115 ef_re = _mm_andnot_ps(bigger, ef_re);
116 ef_im = _mm_andnot_ps(bigger, ef_im);
117 ef_re = _mm_or_ps(ef_re, ef_re_if);
118 ef_im = _mm_or_ps(ef_im, ef_im_if);
119 ef_re = _mm_mul_ps(ef_re, kMu);
120 ef_im = _mm_mul_ps(ef_im, kMu);
121
122 _mm_storeu_ps(&ef[0][i], ef_re);
123 _mm_storeu_ps(&ef[1][i], ef_im);
124 }
125 // scalar code for the remaining items.
126 {
127 const float mu =
128 extended_filter_enabled ? kExtendedMu : normal_mu;
129 const float error_threshold = extended_filter_enabled
130 ? kExtendedErrorThreshold
131 : normal_error_threshold;
132 for (; i < (PART_LEN1); i++) {
133 float abs_ef;
134 ef[0][i] /= (x_pow[i] + 1e-10f);
135 ef[1][i] /= (x_pow[i] + 1e-10f);
136 abs_ef = sqrtf(ef[0][i] * ef[0][i] + ef[1][i] * ef[1][i]);
137
138 if (abs_ef > error_threshold) {
139 abs_ef = error_threshold / (abs_ef + 1e-10f);
140 ef[0][i] *= abs_ef;
141 ef[1][i] *= abs_ef;
142 }
143
144 // Stepsize factor
145 ef[0][i] *= mu;
146 ef[1][i] *= mu;
147 }
148 }
149 }
150
FilterAdaptationSSE2(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])151 static void FilterAdaptationSSE2(
152 int num_partitions,
153 int x_fft_buf_block_pos,
154 float x_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
155 float e_fft[2][PART_LEN1],
156 float h_fft_buf[2][kExtendedNumPartitions * PART_LEN1]) {
157 float fft[PART_LEN2];
158 int i, j;
159 for (i = 0; i < num_partitions; i++) {
160 int xPos = (i + x_fft_buf_block_pos) * (PART_LEN1);
161 int pos = i * PART_LEN1;
162 // Check for wrap
163 if (i + x_fft_buf_block_pos >= num_partitions) {
164 xPos -= num_partitions * PART_LEN1;
165 }
166
167 // Process the whole array...
168 for (j = 0; j < PART_LEN; j += 4) {
169 // Load x_fft_buf and e_fft.
170 const __m128 x_fft_buf_re = _mm_loadu_ps(&x_fft_buf[0][xPos + j]);
171 const __m128 x_fft_buf_im = _mm_loadu_ps(&x_fft_buf[1][xPos + j]);
172 const __m128 e_fft_re = _mm_loadu_ps(&e_fft[0][j]);
173 const __m128 e_fft_im = _mm_loadu_ps(&e_fft[1][j]);
174 // Calculate the product of conjugate(x_fft_buf) by e_fft.
175 // re(conjugate(a) * b) = aRe * bRe + aIm * bIm
176 // im(conjugate(a) * b)= aRe * bIm - aIm * bRe
177 const __m128 a = _mm_mul_ps(x_fft_buf_re, e_fft_re);
178 const __m128 b = _mm_mul_ps(x_fft_buf_im, e_fft_im);
179 const __m128 c = _mm_mul_ps(x_fft_buf_re, e_fft_im);
180 const __m128 d = _mm_mul_ps(x_fft_buf_im, e_fft_re);
181 const __m128 e = _mm_add_ps(a, b);
182 const __m128 f = _mm_sub_ps(c, d);
183 // Interleave real and imaginary parts.
184 const __m128 g = _mm_unpacklo_ps(e, f);
185 const __m128 h = _mm_unpackhi_ps(e, f);
186 // Store
187 _mm_storeu_ps(&fft[2 * j + 0], g);
188 _mm_storeu_ps(&fft[2 * j + 4], h);
189 }
190 // ... and fixup the first imaginary entry.
191 fft[1] = MulRe(x_fft_buf[0][xPos + PART_LEN],
192 -x_fft_buf[1][xPos + PART_LEN],
193 e_fft[0][PART_LEN],
194 e_fft[1][PART_LEN]);
195
196 aec_rdft_inverse_128(fft);
197 memset(fft + PART_LEN, 0, sizeof(float) * PART_LEN);
198
199 // fft scaling
200 {
201 float scale = 2.0f / PART_LEN2;
202 const __m128 scale_ps = _mm_load_ps1(&scale);
203 for (j = 0; j < PART_LEN; j += 4) {
204 const __m128 fft_ps = _mm_loadu_ps(&fft[j]);
205 const __m128 fft_scale = _mm_mul_ps(fft_ps, scale_ps);
206 _mm_storeu_ps(&fft[j], fft_scale);
207 }
208 }
209 aec_rdft_forward_128(fft);
210
211 {
212 float wt1 = h_fft_buf[1][pos];
213 h_fft_buf[0][pos + PART_LEN] += fft[1];
214 for (j = 0; j < PART_LEN; j += 4) {
215 __m128 wtBuf_re = _mm_loadu_ps(&h_fft_buf[0][pos + j]);
216 __m128 wtBuf_im = _mm_loadu_ps(&h_fft_buf[1][pos + j]);
217 const __m128 fft0 = _mm_loadu_ps(&fft[2 * j + 0]);
218 const __m128 fft4 = _mm_loadu_ps(&fft[2 * j + 4]);
219 const __m128 fft_re =
220 _mm_shuffle_ps(fft0, fft4, _MM_SHUFFLE(2, 0, 2, 0));
221 const __m128 fft_im =
222 _mm_shuffle_ps(fft0, fft4, _MM_SHUFFLE(3, 1, 3, 1));
223 wtBuf_re = _mm_add_ps(wtBuf_re, fft_re);
224 wtBuf_im = _mm_add_ps(wtBuf_im, fft_im);
225 _mm_storeu_ps(&h_fft_buf[0][pos + j], wtBuf_re);
226 _mm_storeu_ps(&h_fft_buf[1][pos + j], wtBuf_im);
227 }
228 h_fft_buf[1][pos] = wt1;
229 }
230 }
231 }
232
mm_pow_ps(__m128 a,__m128 b)233 static __m128 mm_pow_ps(__m128 a, __m128 b) {
234 // a^b = exp2(b * log2(a))
235 // exp2(x) and log2(x) are calculated using polynomial approximations.
236 __m128 log2_a, b_log2_a, a_exp_b;
237
238 // Calculate log2(x), x = a.
239 {
240 // To calculate log2(x), we decompose x like this:
241 // x = y * 2^n
242 // n is an integer
243 // y is in the [1.0, 2.0) range
244 //
245 // log2(x) = log2(y) + n
246 // n can be evaluated by playing with float representation.
247 // log2(y) in a small range can be approximated, this code uses an order
248 // five polynomial approximation. The coefficients have been
249 // estimated with the Remez algorithm and the resulting
250 // polynomial has a maximum relative error of 0.00086%.
251
252 // Compute n.
253 // This is done by masking the exponent, shifting it into the top bit of
254 // the mantissa, putting eight into the biased exponent (to shift/
255 // compensate the fact that the exponent has been shifted in the top/
256 // fractional part and finally getting rid of the implicit leading one
257 // from the mantissa by substracting it out.
258 static const ALIGN16_BEG int float_exponent_mask[4] ALIGN16_END = {
259 0x7F800000, 0x7F800000, 0x7F800000, 0x7F800000};
260 static const ALIGN16_BEG int eight_biased_exponent[4] ALIGN16_END = {
261 0x43800000, 0x43800000, 0x43800000, 0x43800000};
262 static const ALIGN16_BEG int implicit_leading_one[4] ALIGN16_END = {
263 0x43BF8000, 0x43BF8000, 0x43BF8000, 0x43BF8000};
264 static const int shift_exponent_into_top_mantissa = 8;
265 const __m128 two_n = _mm_and_ps(a, *((__m128*)float_exponent_mask));
266 const __m128 n_1 = _mm_castsi128_ps(_mm_srli_epi32(
267 _mm_castps_si128(two_n), shift_exponent_into_top_mantissa));
268 const __m128 n_0 = _mm_or_ps(n_1, *((__m128*)eight_biased_exponent));
269 const __m128 n = _mm_sub_ps(n_0, *((__m128*)implicit_leading_one));
270
271 // Compute y.
272 static const ALIGN16_BEG int mantissa_mask[4] ALIGN16_END = {
273 0x007FFFFF, 0x007FFFFF, 0x007FFFFF, 0x007FFFFF};
274 static const ALIGN16_BEG int zero_biased_exponent_is_one[4] ALIGN16_END = {
275 0x3F800000, 0x3F800000, 0x3F800000, 0x3F800000};
276 const __m128 mantissa = _mm_and_ps(a, *((__m128*)mantissa_mask));
277 const __m128 y =
278 _mm_or_ps(mantissa, *((__m128*)zero_biased_exponent_is_one));
279
280 // Approximate log2(y) ~= (y - 1) * pol5(y).
281 // pol5(y) = C5 * y^5 + C4 * y^4 + C3 * y^3 + C2 * y^2 + C1 * y + C0
282 static const ALIGN16_BEG float ALIGN16_END C5[4] = {
283 -3.4436006e-2f, -3.4436006e-2f, -3.4436006e-2f, -3.4436006e-2f};
284 static const ALIGN16_BEG float ALIGN16_END
285 C4[4] = {3.1821337e-1f, 3.1821337e-1f, 3.1821337e-1f, 3.1821337e-1f};
286 static const ALIGN16_BEG float ALIGN16_END
287 C3[4] = {-1.2315303f, -1.2315303f, -1.2315303f, -1.2315303f};
288 static const ALIGN16_BEG float ALIGN16_END
289 C2[4] = {2.5988452f, 2.5988452f, 2.5988452f, 2.5988452f};
290 static const ALIGN16_BEG float ALIGN16_END
291 C1[4] = {-3.3241990f, -3.3241990f, -3.3241990f, -3.3241990f};
292 static const ALIGN16_BEG float ALIGN16_END
293 C0[4] = {3.1157899f, 3.1157899f, 3.1157899f, 3.1157899f};
294 const __m128 pol5_y_0 = _mm_mul_ps(y, *((__m128*)C5));
295 const __m128 pol5_y_1 = _mm_add_ps(pol5_y_0, *((__m128*)C4));
296 const __m128 pol5_y_2 = _mm_mul_ps(pol5_y_1, y);
297 const __m128 pol5_y_3 = _mm_add_ps(pol5_y_2, *((__m128*)C3));
298 const __m128 pol5_y_4 = _mm_mul_ps(pol5_y_3, y);
299 const __m128 pol5_y_5 = _mm_add_ps(pol5_y_4, *((__m128*)C2));
300 const __m128 pol5_y_6 = _mm_mul_ps(pol5_y_5, y);
301 const __m128 pol5_y_7 = _mm_add_ps(pol5_y_6, *((__m128*)C1));
302 const __m128 pol5_y_8 = _mm_mul_ps(pol5_y_7, y);
303 const __m128 pol5_y = _mm_add_ps(pol5_y_8, *((__m128*)C0));
304 const __m128 y_minus_one =
305 _mm_sub_ps(y, *((__m128*)zero_biased_exponent_is_one));
306 const __m128 log2_y = _mm_mul_ps(y_minus_one, pol5_y);
307
308 // Combine parts.
309 log2_a = _mm_add_ps(n, log2_y);
310 }
311
312 // b * log2(a)
313 b_log2_a = _mm_mul_ps(b, log2_a);
314
315 // Calculate exp2(x), x = b * log2(a).
316 {
317 // To calculate 2^x, we decompose x like this:
318 // x = n + y
319 // n is an integer, the value of x - 0.5 rounded down, therefore
320 // y is in the [0.5, 1.5) range
321 //
322 // 2^x = 2^n * 2^y
323 // 2^n can be evaluated by playing with float representation.
324 // 2^y in a small range can be approximated, this code uses an order two
325 // polynomial approximation. The coefficients have been estimated
326 // with the Remez algorithm and the resulting polynomial has a
327 // maximum relative error of 0.17%.
328
329 // To avoid over/underflow, we reduce the range of input to ]-127, 129].
330 static const ALIGN16_BEG float max_input[4] ALIGN16_END = {129.f, 129.f,
331 129.f, 129.f};
332 static const ALIGN16_BEG float min_input[4] ALIGN16_END = {
333 -126.99999f, -126.99999f, -126.99999f, -126.99999f};
334 const __m128 x_min = _mm_min_ps(b_log2_a, *((__m128*)max_input));
335 const __m128 x_max = _mm_max_ps(x_min, *((__m128*)min_input));
336 // Compute n.
337 static const ALIGN16_BEG float half[4] ALIGN16_END = {0.5f, 0.5f,
338 0.5f, 0.5f};
339 const __m128 x_minus_half = _mm_sub_ps(x_max, *((__m128*)half));
340 const __m128i x_minus_half_floor = _mm_cvtps_epi32(x_minus_half);
341 // Compute 2^n.
342 static const ALIGN16_BEG int float_exponent_bias[4] ALIGN16_END = {
343 127, 127, 127, 127};
344 static const int float_exponent_shift = 23;
345 const __m128i two_n_exponent =
346 _mm_add_epi32(x_minus_half_floor, *((__m128i*)float_exponent_bias));
347 const __m128 two_n =
348 _mm_castsi128_ps(_mm_slli_epi32(two_n_exponent, float_exponent_shift));
349 // Compute y.
350 const __m128 y = _mm_sub_ps(x_max, _mm_cvtepi32_ps(x_minus_half_floor));
351 // Approximate 2^y ~= C2 * y^2 + C1 * y + C0.
352 static const ALIGN16_BEG float C2[4] ALIGN16_END = {
353 3.3718944e-1f, 3.3718944e-1f, 3.3718944e-1f, 3.3718944e-1f};
354 static const ALIGN16_BEG float C1[4] ALIGN16_END = {
355 6.5763628e-1f, 6.5763628e-1f, 6.5763628e-1f, 6.5763628e-1f};
356 static const ALIGN16_BEG float C0[4] ALIGN16_END = {1.0017247f, 1.0017247f,
357 1.0017247f, 1.0017247f};
358 const __m128 exp2_y_0 = _mm_mul_ps(y, *((__m128*)C2));
359 const __m128 exp2_y_1 = _mm_add_ps(exp2_y_0, *((__m128*)C1));
360 const __m128 exp2_y_2 = _mm_mul_ps(exp2_y_1, y);
361 const __m128 exp2_y = _mm_add_ps(exp2_y_2, *((__m128*)C0));
362
363 // Combine parts.
364 a_exp_b = _mm_mul_ps(exp2_y, two_n);
365 }
366 return a_exp_b;
367 }
368
OverdriveAndSuppressSSE2(AecCore * aec,float hNl[PART_LEN1],const float hNlFb,float efw[2][PART_LEN1])369 static void OverdriveAndSuppressSSE2(AecCore* aec,
370 float hNl[PART_LEN1],
371 const float hNlFb,
372 float efw[2][PART_LEN1]) {
373 int i;
374 const __m128 vec_hNlFb = _mm_set1_ps(hNlFb);
375 const __m128 vec_one = _mm_set1_ps(1.0f);
376 const __m128 vec_minus_one = _mm_set1_ps(-1.0f);
377 const __m128 vec_overDriveSm = _mm_set1_ps(aec->overDriveSm);
378 // vectorized code (four at once)
379 for (i = 0; i + 3 < PART_LEN1; i += 4) {
380 // Weight subbands
381 __m128 vec_hNl = _mm_loadu_ps(&hNl[i]);
382 const __m128 vec_weightCurve = _mm_loadu_ps(&WebRtcAec_weightCurve[i]);
383 const __m128 bigger = _mm_cmpgt_ps(vec_hNl, vec_hNlFb);
384 const __m128 vec_weightCurve_hNlFb = _mm_mul_ps(vec_weightCurve, vec_hNlFb);
385 const __m128 vec_one_weightCurve = _mm_sub_ps(vec_one, vec_weightCurve);
386 const __m128 vec_one_weightCurve_hNl =
387 _mm_mul_ps(vec_one_weightCurve, vec_hNl);
388 const __m128 vec_if0 = _mm_andnot_ps(bigger, vec_hNl);
389 const __m128 vec_if1 = _mm_and_ps(
390 bigger, _mm_add_ps(vec_weightCurve_hNlFb, vec_one_weightCurve_hNl));
391 vec_hNl = _mm_or_ps(vec_if0, vec_if1);
392
393 {
394 const __m128 vec_overDriveCurve =
395 _mm_loadu_ps(&WebRtcAec_overDriveCurve[i]);
396 const __m128 vec_overDriveSm_overDriveCurve =
397 _mm_mul_ps(vec_overDriveSm, vec_overDriveCurve);
398 vec_hNl = mm_pow_ps(vec_hNl, vec_overDriveSm_overDriveCurve);
399 _mm_storeu_ps(&hNl[i], vec_hNl);
400 }
401
402 // Suppress error signal
403 {
404 __m128 vec_efw_re = _mm_loadu_ps(&efw[0][i]);
405 __m128 vec_efw_im = _mm_loadu_ps(&efw[1][i]);
406 vec_efw_re = _mm_mul_ps(vec_efw_re, vec_hNl);
407 vec_efw_im = _mm_mul_ps(vec_efw_im, vec_hNl);
408
409 // Ooura fft returns incorrect sign on imaginary component. It matters
410 // here because we are making an additive change with comfort noise.
411 vec_efw_im = _mm_mul_ps(vec_efw_im, vec_minus_one);
412 _mm_storeu_ps(&efw[0][i], vec_efw_re);
413 _mm_storeu_ps(&efw[1][i], vec_efw_im);
414 }
415 }
416 // scalar code for the remaining items.
417 for (; i < PART_LEN1; i++) {
418 // Weight subbands
419 if (hNl[i] > hNlFb) {
420 hNl[i] = WebRtcAec_weightCurve[i] * hNlFb +
421 (1 - WebRtcAec_weightCurve[i]) * hNl[i];
422 }
423 hNl[i] = powf(hNl[i], aec->overDriveSm * WebRtcAec_overDriveCurve[i]);
424
425 // Suppress error signal
426 efw[0][i] *= hNl[i];
427 efw[1][i] *= hNl[i];
428
429 // Ooura fft returns incorrect sign on imaginary component. It matters
430 // here because we are making an additive change with comfort noise.
431 efw[1][i] *= -1;
432 }
433 }
434
_mm_add_ps_4x1(__m128 sum,float * dst)435 __inline static void _mm_add_ps_4x1(__m128 sum, float *dst) {
436 // A+B C+D
437 sum = _mm_add_ps(sum, _mm_shuffle_ps(sum, sum, _MM_SHUFFLE(0, 0, 3, 2)));
438 // A+B+C+D A+B+C+D
439 sum = _mm_add_ps(sum, _mm_shuffle_ps(sum, sum, _MM_SHUFFLE(1, 1, 1, 1)));
440 _mm_store_ss(dst, sum);
441 }
442
PartitionDelaySSE2(const AecCore * aec)443 static int PartitionDelaySSE2(const AecCore* aec) {
444 // Measures the energy in each filter partition and returns the partition with
445 // highest energy.
446 // TODO(bjornv): Spread computational cost by computing one partition per
447 // block?
448 float wfEnMax = 0;
449 int i;
450 int delay = 0;
451
452 for (i = 0; i < aec->num_partitions; i++) {
453 int j;
454 int pos = i * PART_LEN1;
455 float wfEn = 0;
456 __m128 vec_wfEn = _mm_set1_ps(0.0f);
457 // vectorized code (four at once)
458 for (j = 0; j + 3 < PART_LEN1; j += 4) {
459 const __m128 vec_wfBuf0 = _mm_loadu_ps(&aec->wfBuf[0][pos + j]);
460 const __m128 vec_wfBuf1 = _mm_loadu_ps(&aec->wfBuf[1][pos + j]);
461 vec_wfEn = _mm_add_ps(vec_wfEn, _mm_mul_ps(vec_wfBuf0, vec_wfBuf0));
462 vec_wfEn = _mm_add_ps(vec_wfEn, _mm_mul_ps(vec_wfBuf1, vec_wfBuf1));
463 }
464 _mm_add_ps_4x1(vec_wfEn, &wfEn);
465
466 // scalar code for the remaining items.
467 for (; j < PART_LEN1; j++) {
468 wfEn += aec->wfBuf[0][pos + j] * aec->wfBuf[0][pos + j] +
469 aec->wfBuf[1][pos + j] * aec->wfBuf[1][pos + j];
470 }
471
472 if (wfEn > wfEnMax) {
473 wfEnMax = wfEn;
474 delay = i;
475 }
476 }
477 return delay;
478 }
479
480 // Updates the following smoothed Power Spectral Densities (PSD):
481 // - sd : near-end
482 // - se : residual echo
483 // - sx : far-end
484 // - sde : cross-PSD of near-end and residual echo
485 // - sxd : cross-PSD of near-end and far-end
486 //
487 // In addition to updating the PSDs, also the filter diverge state is determined
488 // upon actions are taken.
SmoothedPSD(AecCore * aec,float efw[2][PART_LEN1],float dfw[2][PART_LEN1],float xfw[2][PART_LEN1],int * extreme_filter_divergence)489 static void SmoothedPSD(AecCore* aec,
490 float efw[2][PART_LEN1],
491 float dfw[2][PART_LEN1],
492 float xfw[2][PART_LEN1],
493 int* extreme_filter_divergence) {
494 // Power estimate smoothing coefficients.
495 const float* ptrGCoh = aec->extended_filter_enabled
496 ? WebRtcAec_kExtendedSmoothingCoefficients[aec->mult - 1]
497 : WebRtcAec_kNormalSmoothingCoefficients[aec->mult - 1];
498 int i;
499 float sdSum = 0, seSum = 0;
500 const __m128 vec_15 = _mm_set1_ps(WebRtcAec_kMinFarendPSD);
501 const __m128 vec_GCoh0 = _mm_set1_ps(ptrGCoh[0]);
502 const __m128 vec_GCoh1 = _mm_set1_ps(ptrGCoh[1]);
503 __m128 vec_sdSum = _mm_set1_ps(0.0f);
504 __m128 vec_seSum = _mm_set1_ps(0.0f);
505
506 for (i = 0; i + 3 < PART_LEN1; i += 4) {
507 const __m128 vec_dfw0 = _mm_loadu_ps(&dfw[0][i]);
508 const __m128 vec_dfw1 = _mm_loadu_ps(&dfw[1][i]);
509 const __m128 vec_efw0 = _mm_loadu_ps(&efw[0][i]);
510 const __m128 vec_efw1 = _mm_loadu_ps(&efw[1][i]);
511 const __m128 vec_xfw0 = _mm_loadu_ps(&xfw[0][i]);
512 const __m128 vec_xfw1 = _mm_loadu_ps(&xfw[1][i]);
513 __m128 vec_sd = _mm_mul_ps(_mm_loadu_ps(&aec->sd[i]), vec_GCoh0);
514 __m128 vec_se = _mm_mul_ps(_mm_loadu_ps(&aec->se[i]), vec_GCoh0);
515 __m128 vec_sx = _mm_mul_ps(_mm_loadu_ps(&aec->sx[i]), vec_GCoh0);
516 __m128 vec_dfw_sumsq = _mm_mul_ps(vec_dfw0, vec_dfw0);
517 __m128 vec_efw_sumsq = _mm_mul_ps(vec_efw0, vec_efw0);
518 __m128 vec_xfw_sumsq = _mm_mul_ps(vec_xfw0, vec_xfw0);
519 vec_dfw_sumsq = _mm_add_ps(vec_dfw_sumsq, _mm_mul_ps(vec_dfw1, vec_dfw1));
520 vec_efw_sumsq = _mm_add_ps(vec_efw_sumsq, _mm_mul_ps(vec_efw1, vec_efw1));
521 vec_xfw_sumsq = _mm_add_ps(vec_xfw_sumsq, _mm_mul_ps(vec_xfw1, vec_xfw1));
522 vec_xfw_sumsq = _mm_max_ps(vec_xfw_sumsq, vec_15);
523 vec_sd = _mm_add_ps(vec_sd, _mm_mul_ps(vec_dfw_sumsq, vec_GCoh1));
524 vec_se = _mm_add_ps(vec_se, _mm_mul_ps(vec_efw_sumsq, vec_GCoh1));
525 vec_sx = _mm_add_ps(vec_sx, _mm_mul_ps(vec_xfw_sumsq, vec_GCoh1));
526 _mm_storeu_ps(&aec->sd[i], vec_sd);
527 _mm_storeu_ps(&aec->se[i], vec_se);
528 _mm_storeu_ps(&aec->sx[i], vec_sx);
529
530 {
531 const __m128 vec_3210 = _mm_loadu_ps(&aec->sde[i][0]);
532 const __m128 vec_7654 = _mm_loadu_ps(&aec->sde[i + 2][0]);
533 __m128 vec_a = _mm_shuffle_ps(vec_3210, vec_7654,
534 _MM_SHUFFLE(2, 0, 2, 0));
535 __m128 vec_b = _mm_shuffle_ps(vec_3210, vec_7654,
536 _MM_SHUFFLE(3, 1, 3, 1));
537 __m128 vec_dfwefw0011 = _mm_mul_ps(vec_dfw0, vec_efw0);
538 __m128 vec_dfwefw0110 = _mm_mul_ps(vec_dfw0, vec_efw1);
539 vec_a = _mm_mul_ps(vec_a, vec_GCoh0);
540 vec_b = _mm_mul_ps(vec_b, vec_GCoh0);
541 vec_dfwefw0011 = _mm_add_ps(vec_dfwefw0011,
542 _mm_mul_ps(vec_dfw1, vec_efw1));
543 vec_dfwefw0110 = _mm_sub_ps(vec_dfwefw0110,
544 _mm_mul_ps(vec_dfw1, vec_efw0));
545 vec_a = _mm_add_ps(vec_a, _mm_mul_ps(vec_dfwefw0011, vec_GCoh1));
546 vec_b = _mm_add_ps(vec_b, _mm_mul_ps(vec_dfwefw0110, vec_GCoh1));
547 _mm_storeu_ps(&aec->sde[i][0], _mm_unpacklo_ps(vec_a, vec_b));
548 _mm_storeu_ps(&aec->sde[i + 2][0], _mm_unpackhi_ps(vec_a, vec_b));
549 }
550
551 {
552 const __m128 vec_3210 = _mm_loadu_ps(&aec->sxd[i][0]);
553 const __m128 vec_7654 = _mm_loadu_ps(&aec->sxd[i + 2][0]);
554 __m128 vec_a = _mm_shuffle_ps(vec_3210, vec_7654,
555 _MM_SHUFFLE(2, 0, 2, 0));
556 __m128 vec_b = _mm_shuffle_ps(vec_3210, vec_7654,
557 _MM_SHUFFLE(3, 1, 3, 1));
558 __m128 vec_dfwxfw0011 = _mm_mul_ps(vec_dfw0, vec_xfw0);
559 __m128 vec_dfwxfw0110 = _mm_mul_ps(vec_dfw0, vec_xfw1);
560 vec_a = _mm_mul_ps(vec_a, vec_GCoh0);
561 vec_b = _mm_mul_ps(vec_b, vec_GCoh0);
562 vec_dfwxfw0011 = _mm_add_ps(vec_dfwxfw0011,
563 _mm_mul_ps(vec_dfw1, vec_xfw1));
564 vec_dfwxfw0110 = _mm_sub_ps(vec_dfwxfw0110,
565 _mm_mul_ps(vec_dfw1, vec_xfw0));
566 vec_a = _mm_add_ps(vec_a, _mm_mul_ps(vec_dfwxfw0011, vec_GCoh1));
567 vec_b = _mm_add_ps(vec_b, _mm_mul_ps(vec_dfwxfw0110, vec_GCoh1));
568 _mm_storeu_ps(&aec->sxd[i][0], _mm_unpacklo_ps(vec_a, vec_b));
569 _mm_storeu_ps(&aec->sxd[i + 2][0], _mm_unpackhi_ps(vec_a, vec_b));
570 }
571
572 vec_sdSum = _mm_add_ps(vec_sdSum, vec_sd);
573 vec_seSum = _mm_add_ps(vec_seSum, vec_se);
574 }
575
576 _mm_add_ps_4x1(vec_sdSum, &sdSum);
577 _mm_add_ps_4x1(vec_seSum, &seSum);
578
579 for (; i < PART_LEN1; i++) {
580 aec->sd[i] = ptrGCoh[0] * aec->sd[i] +
581 ptrGCoh[1] * (dfw[0][i] * dfw[0][i] + dfw[1][i] * dfw[1][i]);
582 aec->se[i] = ptrGCoh[0] * aec->se[i] +
583 ptrGCoh[1] * (efw[0][i] * efw[0][i] + efw[1][i] * efw[1][i]);
584 // We threshold here to protect against the ill-effects of a zero farend.
585 // The threshold is not arbitrarily chosen, but balances protection and
586 // adverse interaction with the algorithm's tuning.
587 // TODO(bjornv): investigate further why this is so sensitive.
588 aec->sx[i] =
589 ptrGCoh[0] * aec->sx[i] +
590 ptrGCoh[1] * WEBRTC_SPL_MAX(
591 xfw[0][i] * xfw[0][i] + xfw[1][i] * xfw[1][i],
592 WebRtcAec_kMinFarendPSD);
593
594 aec->sde[i][0] =
595 ptrGCoh[0] * aec->sde[i][0] +
596 ptrGCoh[1] * (dfw[0][i] * efw[0][i] + dfw[1][i] * efw[1][i]);
597 aec->sde[i][1] =
598 ptrGCoh[0] * aec->sde[i][1] +
599 ptrGCoh[1] * (dfw[0][i] * efw[1][i] - dfw[1][i] * efw[0][i]);
600
601 aec->sxd[i][0] =
602 ptrGCoh[0] * aec->sxd[i][0] +
603 ptrGCoh[1] * (dfw[0][i] * xfw[0][i] + dfw[1][i] * xfw[1][i]);
604 aec->sxd[i][1] =
605 ptrGCoh[0] * aec->sxd[i][1] +
606 ptrGCoh[1] * (dfw[0][i] * xfw[1][i] - dfw[1][i] * xfw[0][i]);
607
608 sdSum += aec->sd[i];
609 seSum += aec->se[i];
610 }
611
612 // Divergent filter safeguard update.
613 aec->divergeState = (aec->divergeState ? 1.05f : 1.0f) * seSum > sdSum;
614
615 // Signal extreme filter divergence if the error is significantly larger
616 // than the nearend (13 dB).
617 *extreme_filter_divergence = (seSum > (19.95f * sdSum));
618 }
619
620 // Window time domain data to be used by the fft.
WindowDataSSE2(float * x_windowed,const float * x)621 static void WindowDataSSE2(float* x_windowed, const float* x) {
622 int i;
623 for (i = 0; i < PART_LEN; i += 4) {
624 const __m128 vec_Buf1 = _mm_loadu_ps(&x[i]);
625 const __m128 vec_Buf2 = _mm_loadu_ps(&x[PART_LEN + i]);
626 const __m128 vec_sqrtHanning = _mm_load_ps(&WebRtcAec_sqrtHanning[i]);
627 // A B C D
628 __m128 vec_sqrtHanning_rev =
629 _mm_loadu_ps(&WebRtcAec_sqrtHanning[PART_LEN - i - 3]);
630 // D C B A
631 vec_sqrtHanning_rev =
632 _mm_shuffle_ps(vec_sqrtHanning_rev, vec_sqrtHanning_rev,
633 _MM_SHUFFLE(0, 1, 2, 3));
634 _mm_storeu_ps(&x_windowed[i], _mm_mul_ps(vec_Buf1, vec_sqrtHanning));
635 _mm_storeu_ps(&x_windowed[PART_LEN + i],
636 _mm_mul_ps(vec_Buf2, vec_sqrtHanning_rev));
637 }
638 }
639
640 // Puts fft output data into a complex valued array.
StoreAsComplexSSE2(const float * data,float data_complex[2][PART_LEN1])641 static void StoreAsComplexSSE2(const float* data,
642 float data_complex[2][PART_LEN1]) {
643 int i;
644 for (i = 0; i < PART_LEN; i += 4) {
645 const __m128 vec_fft0 = _mm_loadu_ps(&data[2 * i]);
646 const __m128 vec_fft4 = _mm_loadu_ps(&data[2 * i + 4]);
647 const __m128 vec_a = _mm_shuffle_ps(vec_fft0, vec_fft4,
648 _MM_SHUFFLE(2, 0, 2, 0));
649 const __m128 vec_b = _mm_shuffle_ps(vec_fft0, vec_fft4,
650 _MM_SHUFFLE(3, 1, 3, 1));
651 _mm_storeu_ps(&data_complex[0][i], vec_a);
652 _mm_storeu_ps(&data_complex[1][i], vec_b);
653 }
654 // fix beginning/end values
655 data_complex[1][0] = 0;
656 data_complex[1][PART_LEN] = 0;
657 data_complex[0][0] = data[0];
658 data_complex[0][PART_LEN] = data[1];
659 }
660
SubbandCoherenceSSE2(AecCore * aec,float efw[2][PART_LEN1],float dfw[2][PART_LEN1],float xfw[2][PART_LEN1],float * fft,float * cohde,float * cohxd,int * extreme_filter_divergence)661 static void SubbandCoherenceSSE2(AecCore* aec,
662 float efw[2][PART_LEN1],
663 float dfw[2][PART_LEN1],
664 float xfw[2][PART_LEN1],
665 float* fft,
666 float* cohde,
667 float* cohxd,
668 int* extreme_filter_divergence) {
669 int i;
670
671 SmoothedPSD(aec, efw, dfw, xfw, extreme_filter_divergence);
672
673 {
674 const __m128 vec_1eminus10 = _mm_set1_ps(1e-10f);
675
676 // Subband coherence
677 for (i = 0; i + 3 < PART_LEN1; i += 4) {
678 const __m128 vec_sd = _mm_loadu_ps(&aec->sd[i]);
679 const __m128 vec_se = _mm_loadu_ps(&aec->se[i]);
680 const __m128 vec_sx = _mm_loadu_ps(&aec->sx[i]);
681 const __m128 vec_sdse = _mm_add_ps(vec_1eminus10,
682 _mm_mul_ps(vec_sd, vec_se));
683 const __m128 vec_sdsx = _mm_add_ps(vec_1eminus10,
684 _mm_mul_ps(vec_sd, vec_sx));
685 const __m128 vec_sde_3210 = _mm_loadu_ps(&aec->sde[i][0]);
686 const __m128 vec_sde_7654 = _mm_loadu_ps(&aec->sde[i + 2][0]);
687 const __m128 vec_sxd_3210 = _mm_loadu_ps(&aec->sxd[i][0]);
688 const __m128 vec_sxd_7654 = _mm_loadu_ps(&aec->sxd[i + 2][0]);
689 const __m128 vec_sde_0 = _mm_shuffle_ps(vec_sde_3210, vec_sde_7654,
690 _MM_SHUFFLE(2, 0, 2, 0));
691 const __m128 vec_sde_1 = _mm_shuffle_ps(vec_sde_3210, vec_sde_7654,
692 _MM_SHUFFLE(3, 1, 3, 1));
693 const __m128 vec_sxd_0 = _mm_shuffle_ps(vec_sxd_3210, vec_sxd_7654,
694 _MM_SHUFFLE(2, 0, 2, 0));
695 const __m128 vec_sxd_1 = _mm_shuffle_ps(vec_sxd_3210, vec_sxd_7654,
696 _MM_SHUFFLE(3, 1, 3, 1));
697 __m128 vec_cohde = _mm_mul_ps(vec_sde_0, vec_sde_0);
698 __m128 vec_cohxd = _mm_mul_ps(vec_sxd_0, vec_sxd_0);
699 vec_cohde = _mm_add_ps(vec_cohde, _mm_mul_ps(vec_sde_1, vec_sde_1));
700 vec_cohde = _mm_div_ps(vec_cohde, vec_sdse);
701 vec_cohxd = _mm_add_ps(vec_cohxd, _mm_mul_ps(vec_sxd_1, vec_sxd_1));
702 vec_cohxd = _mm_div_ps(vec_cohxd, vec_sdsx);
703 _mm_storeu_ps(&cohde[i], vec_cohde);
704 _mm_storeu_ps(&cohxd[i], vec_cohxd);
705 }
706
707 // scalar code for the remaining items.
708 for (; i < PART_LEN1; i++) {
709 cohde[i] =
710 (aec->sde[i][0] * aec->sde[i][0] + aec->sde[i][1] * aec->sde[i][1]) /
711 (aec->sd[i] * aec->se[i] + 1e-10f);
712 cohxd[i] =
713 (aec->sxd[i][0] * aec->sxd[i][0] + aec->sxd[i][1] * aec->sxd[i][1]) /
714 (aec->sx[i] * aec->sd[i] + 1e-10f);
715 }
716 }
717 }
718
WebRtcAec_InitAec_SSE2(void)719 void WebRtcAec_InitAec_SSE2(void) {
720 WebRtcAec_FilterFar = FilterFarSSE2;
721 WebRtcAec_ScaleErrorSignal = ScaleErrorSignalSSE2;
722 WebRtcAec_FilterAdaptation = FilterAdaptationSSE2;
723 WebRtcAec_OverdriveAndSuppress = OverdriveAndSuppressSSE2;
724 WebRtcAec_SubbandCoherence = SubbandCoherenceSSE2;
725 WebRtcAec_StoreAsComplex = StoreAsComplexSSE2;
726 WebRtcAec_PartitionDelay = PartitionDelaySSE2;
727 WebRtcAec_WindowData = WindowDataSSE2;
728 }
729