summaryrefslogtreecommitdiffstats
path: root/third_party/aom/av1/encoder/x86/rdopt_sse4.c
blob: 12ac1461959680b8ab7f852b6844fe744a5f89d6 (plain)
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
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
/*
 * Copyright (c) 2018, Alliance for Open Media. All rights reserved
 *
 * This source code is subject to the terms of the BSD 2 Clause License and
 * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
 * was not distributed with this source code in the LICENSE file, you can
 * obtain it at www.aomedia.org/license/software. If the Alliance for Open
 * Media Patent License 1.0 was not distributed with this source code in the
 * PATENTS file, you can obtain it at www.aomedia.org/license/patent.
 */

#include <assert.h>
#include <emmintrin.h>
#include "aom_dsp/x86/synonyms.h"

#include "config/av1_rtcd.h"
#include "av1/encoder/rdopt.h"

// Process horizontal and vertical correlations in a 4x4 block of pixels.
// We actually use the 4x4 pixels to calculate correlations corresponding to
// the top-left 3x3 pixels, so this function must be called with 1x1 overlap,
// moving the window along/down by 3 pixels at a time.
INLINE static void horver_correlation_4x4(const int16_t *diff, int stride,
                                          __m128i *xy_sum_32,
                                          __m128i *xz_sum_32, __m128i *x_sum_32,
                                          __m128i *x2_sum_32) {
  // Pixels in this 4x4   [ a b c d ]
  // are referred to as:  [ e f g h ]
  //                      [ i j k l ]
  //                      [ m n o p ]

  const __m128i pixelsa = _mm_set_epi64x(*(int64_t *)&diff[0 * stride],
                                         *(int64_t *)&diff[2 * stride]);
  const __m128i pixelsb = _mm_set_epi64x(*(int64_t *)&diff[1 * stride],
                                         *(int64_t *)&diff[3 * stride]);
  // pixelsa = [d c b a l k j i] as i16
  // pixelsb = [h g f e p o n m] as i16

  const __m128i slli_a = _mm_slli_epi64(pixelsa, 16);
  const __m128i slli_b = _mm_slli_epi64(pixelsb, 16);
  // slli_a = [c b a 0 k j i 0] as i16
  // slli_b = [g f e 0 o n m 0] as i16

  const __m128i xy_madd_a = _mm_madd_epi16(pixelsa, slli_a);
  const __m128i xy_madd_b = _mm_madd_epi16(pixelsb, slli_b);
  // xy_madd_a = [bc+cd ab jk+kl ij] as i32
  // xy_madd_b = [fg+gh ef no+op mn] as i32

  const __m128i xy32 = _mm_hadd_epi32(xy_madd_b, xy_madd_a);
  // xy32 = [ab+bc+cd ij+jk+kl ef+fg+gh mn+no+op] as i32
  *xy_sum_32 = _mm_add_epi32(*xy_sum_32, xy32);

  const __m128i xz_madd_a = _mm_madd_epi16(slli_a, slli_b);
  // xz_madd_a = [bf+cg ae jn+ko im] i32

  const __m128i swap_b = _mm_srli_si128(slli_b, 8);
  // swap_b = [0 0 0 0 g f e 0] as i16
  const __m128i xz_madd_b = _mm_madd_epi16(slli_a, swap_b);
  // xz_madd_b = [0 0 gk+fj ei] i32

  const __m128i xz32 = _mm_hadd_epi32(xz_madd_b, xz_madd_a);
  // xz32 = [ae+bf+cg im+jn+ko 0 ei+fj+gk] i32
  *xz_sum_32 = _mm_add_epi32(*xz_sum_32, xz32);

  // Now calculate the straight sums, x_sum += a+b+c+e+f+g+i+j+k
  // (sum up every element in slli_a and swap_b)
  const __m128i sum_slli_a = _mm_hadd_epi16(slli_a, slli_a);
  const __m128i sum_slli_a32 = _mm_cvtepi16_epi32(sum_slli_a);
  // sum_slli_a32 = [c+b a k+j i] as i32
  const __m128i swap_b32 = _mm_cvtepi16_epi32(swap_b);
  // swap_b32 = [g f e 0] as i32
  *x_sum_32 = _mm_add_epi32(*x_sum_32, sum_slli_a32);
  *x_sum_32 = _mm_add_epi32(*x_sum_32, swap_b32);
  // sum = [c+b+g a+f k+j+e i] as i32

  // Also sum their squares
  const __m128i slli_a_2 = _mm_madd_epi16(slli_a, slli_a);
  const __m128i swap_b_2 = _mm_madd_epi16(swap_b, swap_b);
  // slli_a_2 = [c2+b2 a2 k2+j2 i2]
  // swap_b_2 = [0 0 g2+f2 e2]
  const __m128i sum2 = _mm_hadd_epi32(slli_a_2, swap_b_2);
  // sum2 = [0 g2+f2+e2 c2+b2+a2 k2+j2+i2]
  *x2_sum_32 = _mm_add_epi32(*x2_sum_32, sum2);
}

void av1_get_horver_correlation_full_sse4_1(const int16_t *diff, int stride,
                                            int width, int height, float *hcorr,
                                            float *vcorr) {
  // The following notation is used:
  // x - current pixel
  // y - right neighbour pixel
  // z - below neighbour pixel
  // w - down-right neighbour pixel
  int64_t xy_sum = 0, xz_sum = 0;
  int64_t x_sum = 0, x2_sum = 0;

  // Process horizontal and vertical correlations through the body in 4x4
  // blocks.  This excludes the final row and column and possibly one extra
  // column depending how 3 divides into width and height
  int32_t xy_tmp[4] = { 0 }, xz_tmp[4] = { 0 };
  int32_t x_tmp[4] = { 0 }, x2_tmp[4] = { 0 };
  __m128i xy_sum_32 = _mm_setzero_si128();
  __m128i xz_sum_32 = _mm_setzero_si128();
  __m128i x_sum_32 = _mm_setzero_si128();
  __m128i x2_sum_32 = _mm_setzero_si128();
  for (int i = 0; i <= height - 4; i += 3) {
    for (int j = 0; j <= width - 4; j += 3) {
      horver_correlation_4x4(&diff[i * stride + j], stride, &xy_sum_32,
                             &xz_sum_32, &x_sum_32, &x2_sum_32);
    }
    xx_storeu_128(xy_tmp, xy_sum_32);
    xx_storeu_128(xz_tmp, xz_sum_32);
    xx_storeu_128(x_tmp, x_sum_32);
    xx_storeu_128(x2_tmp, x2_sum_32);
    xy_sum += (int64_t)xy_tmp[3] + xy_tmp[2] + xy_tmp[1];
    xz_sum += (int64_t)xz_tmp[3] + xz_tmp[2] + xz_tmp[0];
    x_sum += (int64_t)x_tmp[3] + x_tmp[2] + x_tmp[1] + x_tmp[0];
    x2_sum += (int64_t)x2_tmp[2] + x2_tmp[1] + x2_tmp[0];
    xy_sum_32 = _mm_setzero_si128();
    xz_sum_32 = _mm_setzero_si128();
    x_sum_32 = _mm_setzero_si128();
    x2_sum_32 = _mm_setzero_si128();
  }

  // x_sum now covers every pixel except the final 1-2 rows and 1-2 cols
  int64_t x_finalrow = 0, x_finalcol = 0, x2_finalrow = 0, x2_finalcol = 0;

  // Do we have 2 rows remaining or just the one?  Note that width and height
  // are powers of 2, so each modulo 3 must be 1 or 2.
  if (height % 3 == 1) {  // Just horiz corrs on the final row
    const int16_t x0 = diff[(height - 1) * stride];
    x_sum += x0;
    x_finalrow += x0;
    x2_sum += x0 * x0;
    x2_finalrow += x0 * x0;
    for (int j = 0; j < width - 1; ++j) {
      const int16_t x = diff[(height - 1) * stride + j];
      const int16_t y = diff[(height - 1) * stride + j + 1];
      xy_sum += x * y;
      x_sum += y;
      x2_sum += y * y;
      x_finalrow += y;
      x2_finalrow += y * y;
    }
  } else {  // Two rows remaining to do
    const int16_t x0 = diff[(height - 2) * stride];
    const int16_t z0 = diff[(height - 1) * stride];
    x_sum += x0 + z0;
    x2_sum += x0 * x0 + z0 * z0;
    x_finalrow += z0;
    x2_finalrow += z0 * z0;
    for (int j = 0; j < width - 1; ++j) {
      const int16_t x = diff[(height - 2) * stride + j];
      const int16_t y = diff[(height - 2) * stride + j + 1];
      const int16_t z = diff[(height - 1) * stride + j];
      const int16_t w = diff[(height - 1) * stride + j + 1];

      // Horizontal and vertical correlations for the penultimate row:
      xy_sum += x * y;
      xz_sum += x * z;

      // Now just horizontal correlations for the final row:
      xy_sum += z * w;

      x_sum += y + w;
      x2_sum += y * y + w * w;
      x_finalrow += w;
      x2_finalrow += w * w;
    }
  }

  // Do we have 2 columns remaining or just the one?
  if (width % 3 == 1) {  // Just vert corrs on the final col
    const int16_t x0 = diff[width - 1];
    x_sum += x0;
    x_finalcol += x0;
    x2_sum += x0 * x0;
    x2_finalcol += x0 * x0;
    for (int i = 0; i < height - 1; ++i) {
      const int16_t x = diff[i * stride + width - 1];
      const int16_t z = diff[(i + 1) * stride + width - 1];
      xz_sum += x * z;
      x_finalcol += z;
      x2_finalcol += z * z;
      // So the bottom-right elements don't get counted twice:
      if (i < height - (height % 3 == 1 ? 2 : 3)) {
        x_sum += z;
        x2_sum += z * z;
      }
    }
  } else {  // Two cols remaining
    const int16_t x0 = diff[width - 2];
    const int16_t y0 = diff[width - 1];
    x_sum += x0 + y0;
    x2_sum += x0 * x0 + y0 * y0;
    x_finalcol += y0;
    x2_finalcol += y0 * y0;
    for (int i = 0; i < height - 1; ++i) {
      const int16_t x = diff[i * stride + width - 2];
      const int16_t y = diff[i * stride + width - 1];
      const int16_t z = diff[(i + 1) * stride + width - 2];
      const int16_t w = diff[(i + 1) * stride + width - 1];

      // Horizontal and vertical correlations for the penultimate col:
      // Skip these on the last iteration of this loop if we also had two
      // rows remaining, otherwise the final horizontal and vertical correlation
      // get erroneously processed twice
      if (i < height - 2 || height % 3 == 1) {
        xy_sum += x * y;
        xz_sum += x * z;
      }

      x_finalcol += w;
      x2_finalcol += w * w;
      // So the bottom-right elements don't get counted twice:
      if (i < height - (height % 3 == 1 ? 2 : 3)) {
        x_sum += z + w;
        x2_sum += z * z + w * w;
      }

      // Now just vertical correlations for the final column:
      xz_sum += y * w;
    }
  }

  // Calculate the simple sums and squared-sums
  int64_t x_firstrow = 0, x_firstcol = 0;
  int64_t x2_firstrow = 0, x2_firstcol = 0;

  for (int j = 0; j < width; ++j) {
    x_firstrow += diff[j];
    x2_firstrow += diff[j] * diff[j];
  }
  for (int i = 0; i < height; ++i) {
    x_firstcol += diff[i * stride];
    x2_firstcol += diff[i * stride] * diff[i * stride];
  }

  int64_t xhor_sum = x_sum - x_finalcol;
  int64_t xver_sum = x_sum - x_finalrow;
  int64_t y_sum = x_sum - x_firstcol;
  int64_t z_sum = x_sum - x_firstrow;
  int64_t x2hor_sum = x2_sum - x2_finalcol;
  int64_t x2ver_sum = x2_sum - x2_finalrow;
  int64_t y2_sum = x2_sum - x2_firstcol;
  int64_t z2_sum = x2_sum - x2_firstrow;

  const float num_hor = (float)(height * (width - 1));
  const float num_ver = (float)((height - 1) * width);

  const float xhor_var_n = x2hor_sum - (xhor_sum * xhor_sum) / num_hor;
  const float xver_var_n = x2ver_sum - (xver_sum * xver_sum) / num_ver;

  const float y_var_n = y2_sum - (y_sum * y_sum) / num_hor;
  const float z_var_n = z2_sum - (z_sum * z_sum) / num_ver;

  const float xy_var_n = xy_sum - (xhor_sum * y_sum) / num_hor;
  const float xz_var_n = xz_sum - (xver_sum * z_sum) / num_ver;

  if (xhor_var_n > 0 && y_var_n > 0) {
    *hcorr = xy_var_n / sqrtf(xhor_var_n * y_var_n);
    *hcorr = *hcorr < 0 ? 0 : *hcorr;
  } else {
    *hcorr = 1.0;
  }
  if (xver_var_n > 0 && z_var_n > 0) {
    *vcorr = xz_var_n / sqrtf(xver_var_n * z_var_n);
    *vcorr = *vcorr < 0 ? 0 : *vcorr;
  } else {
    *vcorr = 1.0;
  }
}