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Issue 13293004: enable SSE2 in skia/convolver for linux32 (Closed) Base URL: svn://svn.chromium.org/chrome/trunk/src
Patch Set: forgot to include convolver_SSE2.h in convolver_SSE2.cc Created 7 years, 8 months ago
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1 // Copyright (c) 2011 The Chromium Authors. All rights reserved. 1 // Copyright (c) 2011 The Chromium Authors. All rights reserved.
2 // Use of this source code is governed by a BSD-style license that can be 2 // Use of this source code is governed by a BSD-style license that can be
3 // found in the LICENSE file. 3 // found in the LICENSE file.
4 4
5 #include <algorithm> 5 #include <algorithm>
6 6
7 #include "skia/ext/convolver.h" 7 #include "skia/ext/convolver.h"
8 #include "skia/ext/convolver_SSE2.h"
8 #include "third_party/skia/include/core/SkTypes.h" 9 #include "third_party/skia/include/core/SkTypes.h"
9 10
10 #if defined(SIMD_SSE2)
11 #include <emmintrin.h> // ARCH_CPU_X86_FAMILY was defined in build/config.h 11 #include <emmintrin.h> // ARCH_CPU_X86_FAMILY was defined in build/config.h
12 #endif
13 12
14 namespace skia { 13 namespace skia {
15 14
16 namespace {
17
18 // Converts the argument to an 8-bit unsigned value by clamping to the range
19 // 0-255.
20 inline unsigned char ClampTo8(int a) {
21 if (static_cast<unsigned>(a) < 256)
22 return a; // Avoid the extra check in the common case.
23 if (a < 0)
24 return 0;
25 return 255;
26 }
27
28 // Stores a list of rows in a circular buffer. The usage is you write into it
29 // by calling AdvanceRow. It will keep track of which row in the buffer it
30 // should use next, and the total number of rows added.
31 class CircularRowBuffer {
32 public:
33 // The number of pixels in each row is given in |source_row_pixel_width|.
34 // The maximum number of rows needed in the buffer is |max_y_filter_size|
35 // (we only need to store enough rows for the biggest filter).
36 //
37 // We use the |first_input_row| to compute the coordinates of all of the
38 // following rows returned by Advance().
39 CircularRowBuffer(int dest_row_pixel_width, int max_y_filter_size,
40 int first_input_row)
41 : row_byte_width_(dest_row_pixel_width * 4),
42 num_rows_(max_y_filter_size),
43 next_row_(0),
44 next_row_coordinate_(first_input_row) {
45 buffer_.resize(row_byte_width_ * max_y_filter_size);
46 row_addresses_.resize(num_rows_);
47 }
48
49 // Moves to the next row in the buffer, returning a pointer to the beginning
50 // of it.
51 unsigned char* AdvanceRow() {
52 unsigned char* row = &buffer_[next_row_ * row_byte_width_];
53 next_row_coordinate_++;
54
55 // Set the pointer to the next row to use, wrapping around if necessary.
56 next_row_++;
57 if (next_row_ == num_rows_)
58 next_row_ = 0;
59 return row;
60 }
61
62 // Returns a pointer to an "unrolled" array of rows. These rows will start
63 // at the y coordinate placed into |*first_row_index| and will continue in
64 // order for the maximum number of rows in this circular buffer.
65 //
66 // The |first_row_index_| may be negative. This means the circular buffer
67 // starts before the top of the image (it hasn't been filled yet).
68 unsigned char* const* GetRowAddresses(int* first_row_index) {
69 // Example for a 4-element circular buffer holding coords 6-9.
70 // Row 0 Coord 8
71 // Row 1 Coord 9
72 // Row 2 Coord 6 <- next_row_ = 2, next_row_coordinate_ = 10.
73 // Row 3 Coord 7
74 //
75 // The "next" row is also the first (lowest) coordinate. This computation
76 // may yield a negative value, but that's OK, the math will work out
77 // since the user of this buffer will compute the offset relative
78 // to the first_row_index and the negative rows will never be used.
79 *first_row_index = next_row_coordinate_ - num_rows_;
80
81 int cur_row = next_row_;
82 for (int i = 0; i < num_rows_; i++) {
83 row_addresses_[i] = &buffer_[cur_row * row_byte_width_];
84
85 // Advance to the next row, wrapping if necessary.
86 cur_row++;
87 if (cur_row == num_rows_)
88 cur_row = 0;
89 }
90 return &row_addresses_[0];
91 }
92
93 private:
94 // The buffer storing the rows. They are packed, each one row_byte_width_.
95 std::vector<unsigned char> buffer_;
96
97 // Number of bytes per row in the |buffer_|.
98 int row_byte_width_;
99
100 // The number of rows available in the buffer.
101 int num_rows_;
102
103 // The next row index we should write into. This wraps around as the
104 // circular buffer is used.
105 int next_row_;
106
107 // The y coordinate of the |next_row_|. This is incremented each time a
108 // new row is appended and does not wrap.
109 int next_row_coordinate_;
110
111 // Buffer used by GetRowAddresses().
112 std::vector<unsigned char*> row_addresses_;
113 };
114
115 // Convolves horizontally along a single row. The row data is given in
116 // |src_data| and continues for the num_values() of the filter.
117 template<bool has_alpha>
118 void ConvolveHorizontally(const unsigned char* src_data,
119 const ConvolutionFilter1D& filter,
120 unsigned char* out_row) {
121 // Loop over each pixel on this row in the output image.
122 int num_values = filter.num_values();
123 for (int out_x = 0; out_x < num_values; out_x++) {
124 // Get the filter that determines the current output pixel.
125 int filter_offset, filter_length;
126 const ConvolutionFilter1D::Fixed* filter_values =
127 filter.FilterForValue(out_x, &filter_offset, &filter_length);
128
129 // Compute the first pixel in this row that the filter affects. It will
130 // touch |filter_length| pixels (4 bytes each) after this.
131 const unsigned char* row_to_filter = &src_data[filter_offset * 4];
132
133 // Apply the filter to the row to get the destination pixel in |accum|.
134 int accum[4] = {0};
135 for (int filter_x = 0; filter_x < filter_length; filter_x++) {
136 ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_x];
137 accum[0] += cur_filter * row_to_filter[filter_x * 4 + 0];
138 accum[1] += cur_filter * row_to_filter[filter_x * 4 + 1];
139 accum[2] += cur_filter * row_to_filter[filter_x * 4 + 2];
140 if (has_alpha)
141 accum[3] += cur_filter * row_to_filter[filter_x * 4 + 3];
142 }
143
144 // Bring this value back in range. All of the filter scaling factors
145 // are in fixed point with kShiftBits bits of fractional part.
146 accum[0] >>= ConvolutionFilter1D::kShiftBits;
147 accum[1] >>= ConvolutionFilter1D::kShiftBits;
148 accum[2] >>= ConvolutionFilter1D::kShiftBits;
149 if (has_alpha)
150 accum[3] >>= ConvolutionFilter1D::kShiftBits;
151
152 // Store the new pixel.
153 out_row[out_x * 4 + 0] = ClampTo8(accum[0]);
154 out_row[out_x * 4 + 1] = ClampTo8(accum[1]);
155 out_row[out_x * 4 + 2] = ClampTo8(accum[2]);
156 if (has_alpha)
157 out_row[out_x * 4 + 3] = ClampTo8(accum[3]);
158 }
159 }
160
161 // Does vertical convolution to produce one output row. The filter values and
162 // length are given in the first two parameters. These are applied to each
163 // of the rows pointed to in the |source_data_rows| array, with each row
164 // being |pixel_width| wide.
165 //
166 // The output must have room for |pixel_width * 4| bytes.
167 template<bool has_alpha>
168 void ConvolveVertically(const ConvolutionFilter1D::Fixed* filter_values,
169 int filter_length,
170 unsigned char* const* source_data_rows,
171 int pixel_width,
172 unsigned char* out_row) {
173 // We go through each column in the output and do a vertical convolution,
174 // generating one output pixel each time.
175 for (int out_x = 0; out_x < pixel_width; out_x++) {
176 // Compute the number of bytes over in each row that the current column
177 // we're convolving starts at. The pixel will cover the next 4 bytes.
178 int byte_offset = out_x * 4;
179
180 // Apply the filter to one column of pixels.
181 int accum[4] = {0};
182 for (int filter_y = 0; filter_y < filter_length; filter_y++) {
183 ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_y];
184 accum[0] += cur_filter * source_data_rows[filter_y][byte_offset + 0];
185 accum[1] += cur_filter * source_data_rows[filter_y][byte_offset + 1];
186 accum[2] += cur_filter * source_data_rows[filter_y][byte_offset + 2];
187 if (has_alpha)
188 accum[3] += cur_filter * source_data_rows[filter_y][byte_offset + 3];
189 }
190
191 // Bring this value back in range. All of the filter scaling factors
192 // are in fixed point with kShiftBits bits of precision.
193 accum[0] >>= ConvolutionFilter1D::kShiftBits;
194 accum[1] >>= ConvolutionFilter1D::kShiftBits;
195 accum[2] >>= ConvolutionFilter1D::kShiftBits;
196 if (has_alpha)
197 accum[3] >>= ConvolutionFilter1D::kShiftBits;
198
199 // Store the new pixel.
200 out_row[byte_offset + 0] = ClampTo8(accum[0]);
201 out_row[byte_offset + 1] = ClampTo8(accum[1]);
202 out_row[byte_offset + 2] = ClampTo8(accum[2]);
203 if (has_alpha) {
204 unsigned char alpha = ClampTo8(accum[3]);
205
206 // Make sure the alpha channel doesn't come out smaller than any of the
207 // color channels. We use premultipled alpha channels, so this should
208 // never happen, but rounding errors will cause this from time to time.
209 // These "impossible" colors will cause overflows (and hence random pixel
210 // values) when the resulting bitmap is drawn to the screen.
211 //
212 // We only need to do this when generating the final output row (here).
213 int max_color_channel = std::max(out_row[byte_offset + 0],
214 std::max(out_row[byte_offset + 1], out_row[byte_offset + 2]));
215 if (alpha < max_color_channel)
216 out_row[byte_offset + 3] = max_color_channel;
217 else
218 out_row[byte_offset + 3] = alpha;
219 } else {
220 // No alpha channel, the image is opaque.
221 out_row[byte_offset + 3] = 0xff;
222 }
223 }
224 }
225
226
227 // Convolves horizontally along a single row. The row data is given in 15 // Convolves horizontally along a single row. The row data is given in
228 // |src_data| and continues for the num_values() of the filter. 16 // |src_data| and continues for the num_values() of the filter.
229 void ConvolveHorizontally_SSE2(const unsigned char* src_data, 17 void ConvolveHorizontally_SSE2(const unsigned char* src_data,
230 const ConvolutionFilter1D& filter, 18 const ConvolutionFilter1D& filter,
231 unsigned char* out_row) { 19 unsigned char* out_row) {
232 #if defined(SIMD_SSE2)
233 int num_values = filter.num_values(); 20 int num_values = filter.num_values();
234 21
235 int filter_offset, filter_length; 22 int filter_offset, filter_length;
236 __m128i zero = _mm_setzero_si128(); 23 __m128i zero = _mm_setzero_si128();
237 __m128i mask[4]; 24 __m128i mask[4];
238 // |mask| will be used to decimate all extra filter coefficients that are 25 // |mask| will be used to decimate all extra filter coefficients that are
239 // loaded by SIMD when |filter_length| is not divisible by 4. 26 // loaded by SIMD when |filter_length| is not divisible by 4.
240 // mask[0] is not used in following algorithm. 27 // mask[0] is not used in following algorithm.
241 mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1); 28 mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1);
242 mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1); 29 mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1);
(...skipping 100 matching lines...) Expand 10 before | Expand all | Expand 10 after
343 130
344 // Packing 32 bits |accum| to 16 bits per channel (signed saturation). 131 // Packing 32 bits |accum| to 16 bits per channel (signed saturation).
345 accum = _mm_packs_epi32(accum, zero); 132 accum = _mm_packs_epi32(accum, zero);
346 // Packing 16 bits |accum| to 8 bits per channel (unsigned saturation). 133 // Packing 16 bits |accum| to 8 bits per channel (unsigned saturation).
347 accum = _mm_packus_epi16(accum, zero); 134 accum = _mm_packus_epi16(accum, zero);
348 135
349 // Store the pixel value of 32 bits. 136 // Store the pixel value of 32 bits.
350 *(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum); 137 *(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum);
351 out_row += 4; 138 out_row += 4;
352 } 139 }
353 #endif
354 } 140 }
355 141
356 // Convolves horizontally along four rows. The row data is given in 142 // Convolves horizontally along four rows. The row data is given in
357 // |src_data| and continues for the num_values() of the filter. 143 // |src_data| and continues for the num_values() of the filter.
358 // The algorithm is almost same as |ConvolveHorizontally_SSE2|. Please 144 // The algorithm is almost same as |ConvolveHorizontally_SSE2|. Please
359 // refer to that function for detailed comments. 145 // refer to that function for detailed comments.
360 void ConvolveHorizontally4_SSE2(const unsigned char* src_data[4], 146 void Convolve4RowsHorizontally_SSE2(const unsigned char* src_data[4],
361 const ConvolutionFilter1D& filter, 147 const ConvolutionFilter1D& filter,
362 unsigned char* out_row[4]) { 148 unsigned char* out_row[4]) {
363 #if defined(SIMD_SSE2)
364 int num_values = filter.num_values(); 149 int num_values = filter.num_values();
365 150
366 int filter_offset, filter_length; 151 int filter_offset, filter_length;
367 __m128i zero = _mm_setzero_si128(); 152 __m128i zero = _mm_setzero_si128();
368 __m128i mask[4]; 153 __m128i mask[4];
369 // |mask| will be used to decimate all extra filter coefficients that are 154 // |mask| will be used to decimate all extra filter coefficients that are
370 // loaded by SIMD when |filter_length| is not divisible by 4. 155 // loaded by SIMD when |filter_length| is not divisible by 4.
371 // mask[0] is not used in following algorithm. 156 // mask[0] is not used in following algorithm.
372 mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1); 157 mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1);
373 mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1); 158 mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1);
(...skipping 90 matching lines...) Expand 10 before | Expand all | Expand 10 after
464 *(reinterpret_cast<int*>(out_row[0])) = _mm_cvtsi128_si32(accum0); 249 *(reinterpret_cast<int*>(out_row[0])) = _mm_cvtsi128_si32(accum0);
465 *(reinterpret_cast<int*>(out_row[1])) = _mm_cvtsi128_si32(accum1); 250 *(reinterpret_cast<int*>(out_row[1])) = _mm_cvtsi128_si32(accum1);
466 *(reinterpret_cast<int*>(out_row[2])) = _mm_cvtsi128_si32(accum2); 251 *(reinterpret_cast<int*>(out_row[2])) = _mm_cvtsi128_si32(accum2);
467 *(reinterpret_cast<int*>(out_row[3])) = _mm_cvtsi128_si32(accum3); 252 *(reinterpret_cast<int*>(out_row[3])) = _mm_cvtsi128_si32(accum3);
468 253
469 out_row[0] += 4; 254 out_row[0] += 4;
470 out_row[1] += 4; 255 out_row[1] += 4;
471 out_row[2] += 4; 256 out_row[2] += 4;
472 out_row[3] += 4; 257 out_row[3] += 4;
473 } 258 }
474 #endif
475 } 259 }
476 260
477 // Does vertical convolution to produce one output row. The filter values and 261 // Does vertical convolution to produce one output row. The filter values and
478 // length are given in the first two parameters. These are applied to each 262 // length are given in the first two parameters. These are applied to each
479 // of the rows pointed to in the |source_data_rows| array, with each row 263 // of the rows pointed to in the |source_data_rows| array, with each row
480 // being |pixel_width| wide. 264 // being |pixel_width| wide.
481 // 265 //
482 // The output must have room for |pixel_width * 4| bytes. 266 // The output must have room for |pixel_width * 4| bytes.
483 template<bool has_alpha> 267 template<bool has_alpha>
484 void ConvolveVertically_SSE2(const ConvolutionFilter1D::Fixed* filter_values, 268 void ConvolveVertically_SSE2(const ConvolutionFilter1D::Fixed* filter_values,
485 int filter_length, 269 int filter_length,
486 unsigned char* const* source_data_rows, 270 unsigned char* const* source_data_rows,
487 int pixel_width, 271 int pixel_width,
488 unsigned char* out_row) { 272 unsigned char* out_row) {
489 #if defined(SIMD_SSE2)
490 int width = pixel_width & ~3; 273 int width = pixel_width & ~3;
491 274
492 __m128i zero = _mm_setzero_si128(); 275 __m128i zero = _mm_setzero_si128();
493 __m128i accum0, accum1, accum2, accum3, coeff16; 276 __m128i accum0, accum1, accum2, accum3, coeff16;
494 const __m128i* src; 277 const __m128i* src;
495 // Output four pixels per iteration (16 bytes). 278 // Output four pixels per iteration (16 bytes).
496 for (int out_x = 0; out_x < width; out_x += 4) { 279 for (int out_x = 0; out_x < width; out_x += 4) {
497 280
498 // Accumulated result for each pixel. 32 bits per RGBA channel. 281 // Accumulated result for each pixel. 32 bits per RGBA channel.
499 accum0 = _mm_setzero_si128(); 282 accum0 = _mm_setzero_si128();
(...skipping 140 matching lines...) Expand 10 before | Expand all | Expand 10 after
640 __m128i mask = _mm_set1_epi32(0xff000000); 423 __m128i mask = _mm_set1_epi32(0xff000000);
641 accum0 = _mm_or_si128(accum0, mask); 424 accum0 = _mm_or_si128(accum0, mask);
642 } 425 }
643 426
644 for (int out_x = width; out_x < pixel_width; out_x++) { 427 for (int out_x = width; out_x < pixel_width; out_x++) {
645 *(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum0); 428 *(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum0);
646 accum0 = _mm_srli_si128(accum0, 4); 429 accum0 = _mm_srli_si128(accum0, 4);
647 out_row += 4; 430 out_row += 4;
648 } 431 }
649 } 432 }
650 #endif
651 }
652
653 } // namespace
654
655 // ConvolutionFilter1D ---------------------------------------------------------
656
657 ConvolutionFilter1D::ConvolutionFilter1D()
658 : max_filter_(0) {
659 }
660
661 ConvolutionFilter1D::~ConvolutionFilter1D() {
662 }
663
664 void ConvolutionFilter1D::AddFilter(int filter_offset,
665 const float* filter_values,
666 int filter_length) {
667 SkASSERT(filter_length > 0);
668
669 std::vector<Fixed> fixed_values;
670 fixed_values.reserve(filter_length);
671
672 for (int i = 0; i < filter_length; ++i)
673 fixed_values.push_back(FloatToFixed(filter_values[i]));
674
675 AddFilter(filter_offset, &fixed_values[0], filter_length);
676 }
677
678 void ConvolutionFilter1D::AddFilter(int filter_offset,
679 const Fixed* filter_values,
680 int filter_length) {
681 // It is common for leading/trailing filter values to be zeros. In such
682 // cases it is beneficial to only store the central factors.
683 // For a scaling to 1/4th in each dimension using a Lanczos-2 filter on
684 // a 1080p image this optimization gives a ~10% speed improvement.
685 int first_non_zero = 0;
686 while (first_non_zero < filter_length && filter_values[first_non_zero] == 0)
687 first_non_zero++;
688
689 if (first_non_zero < filter_length) {
690 // Here we have at least one non-zero factor.
691 int last_non_zero = filter_length - 1;
692 while (last_non_zero >= 0 && filter_values[last_non_zero] == 0)
693 last_non_zero--;
694
695 filter_offset += first_non_zero;
696 filter_length = last_non_zero + 1 - first_non_zero;
697 SkASSERT(filter_length > 0);
698
699 for (int i = first_non_zero; i <= last_non_zero; i++)
700 filter_values_.push_back(filter_values[i]);
701 } else {
702 // Here all the factors were zeroes.
703 filter_length = 0;
704 }
705
706 FilterInstance instance;
707
708 // We pushed filter_length elements onto filter_values_
709 instance.data_location = (static_cast<int>(filter_values_.size()) -
710 filter_length);
711 instance.offset = filter_offset;
712 instance.length = filter_length;
713 filters_.push_back(instance);
714
715 max_filter_ = std::max(max_filter_, filter_length);
716 }
717
718 void BGRAConvolve2D(const unsigned char* source_data,
719 int source_byte_row_stride,
720 bool source_has_alpha,
721 const ConvolutionFilter1D& filter_x,
722 const ConvolutionFilter1D& filter_y,
723 int output_byte_row_stride,
724 unsigned char* output,
725 bool use_sse2) {
726 #if !defined(SIMD_SSE2)
727 // Even we have runtime support for SSE2 instructions, since the binary
728 // was not built with SSE2 support, we had to fallback to C version.
729 use_sse2 = false;
730 #endif
731
732 int max_y_filter_size = filter_y.max_filter();
733
734 // The next row in the input that we will generate a horizontally
735 // convolved row for. If the filter doesn't start at the beginning of the
736 // image (this is the case when we are only resizing a subset), then we
737 // don't want to generate any output rows before that. Compute the starting
738 // row for convolution as the first pixel for the first vertical filter.
739 int filter_offset, filter_length;
740 const ConvolutionFilter1D::Fixed* filter_values =
741 filter_y.FilterForValue(0, &filter_offset, &filter_length);
742 int next_x_row = filter_offset;
743
744 // We loop over each row in the input doing a horizontal convolution. This
745 // will result in a horizontally convolved image. We write the results into
746 // a circular buffer of convolved rows and do vertical convolution as rows
747 // are available. This prevents us from having to store the entire
748 // intermediate image and helps cache coherency.
749 // We will need four extra rows to allow horizontal convolution could be done
750 // simultaneously. We also padding each row in row buffer to be aligned-up to
751 // 16 bytes.
752 // TODO(jiesun): We do not use aligned load from row buffer in vertical
753 // convolution pass yet. Somehow Windows does not like it.
754 int row_buffer_width = (filter_x.num_values() + 15) & ~0xF;
755 int row_buffer_height = max_y_filter_size + (use_sse2 ? 4 : 0);
756 CircularRowBuffer row_buffer(row_buffer_width,
757 row_buffer_height,
758 filter_offset);
759
760 // Loop over every possible output row, processing just enough horizontal
761 // convolutions to run each subsequent vertical convolution.
762 SkASSERT(output_byte_row_stride >= filter_x.num_values() * 4);
763 int num_output_rows = filter_y.num_values();
764
765 // We need to check which is the last line to convolve before we advance 4
766 // lines in one iteration.
767 int last_filter_offset, last_filter_length;
768
769 // SSE2 can access up to 3 extra pixels past the end of the
770 // buffer. At the bottom of the image, we have to be careful
771 // not to access data past the end of the buffer. Normally
772 // we fall back to the C++ implementation for the last row.
773 // If the last row is less than 3 pixels wide, we may have to fall
774 // back to the C++ version for more rows. Compute how many
775 // rows we need to avoid the SSE implementation for here.
776 filter_x.FilterForValue(filter_x.num_values() - 1, &last_filter_offset,
777 &last_filter_length);
778 int avoid_sse_rows = 1 + 3/(last_filter_offset + last_filter_length);
779
780 filter_y.FilterForValue(num_output_rows - 1, &last_filter_offset,
781 &last_filter_length);
782
783 for (int out_y = 0; out_y < num_output_rows; out_y++) {
784 filter_values = filter_y.FilterForValue(out_y,
785 &filter_offset, &filter_length);
786
787 // Generate output rows until we have enough to run the current filter.
788 if (use_sse2) {
789 while (next_x_row < filter_offset + filter_length) {
790 if (next_x_row + 3 < last_filter_offset + last_filter_length -
791 avoid_sse_rows) {
792 const unsigned char* src[4];
793 unsigned char* out_row[4];
794 for (int i = 0; i < 4; ++i) {
795 src[i] = &source_data[(next_x_row + i) * source_byte_row_stride];
796 out_row[i] = row_buffer.AdvanceRow();
797 }
798 ConvolveHorizontally4_SSE2(src, filter_x, out_row);
799 next_x_row += 4;
800 } else {
801 // Check if we need to avoid SSE2 for this row.
802 if (next_x_row >= last_filter_offset + last_filter_length -
803 avoid_sse_rows) {
804 if (source_has_alpha) {
805 ConvolveHorizontally<true>(
806 &source_data[next_x_row * source_byte_row_stride],
807 filter_x, row_buffer.AdvanceRow());
808 } else {
809 ConvolveHorizontally<false>(
810 &source_data[next_x_row * source_byte_row_stride],
811 filter_x, row_buffer.AdvanceRow());
812 }
813 } else {
814 ConvolveHorizontally_SSE2(
815 &source_data[next_x_row * source_byte_row_stride],
816 filter_x, row_buffer.AdvanceRow());
817 }
818 next_x_row++;
819 }
820 }
821 } else {
822 while (next_x_row < filter_offset + filter_length) {
823 if (source_has_alpha) {
824 ConvolveHorizontally<true>(
825 &source_data[next_x_row * source_byte_row_stride],
826 filter_x, row_buffer.AdvanceRow());
827 } else {
828 ConvolveHorizontally<false>(
829 &source_data[next_x_row * source_byte_row_stride],
830 filter_x, row_buffer.AdvanceRow());
831 }
832 next_x_row++;
833 }
834 }
835
836 // Compute where in the output image this row of final data will go.
837 unsigned char* cur_output_row = &output[out_y * output_byte_row_stride];
838
839 // Get the list of rows that the circular buffer has, in order.
840 int first_row_in_circular_buffer;
841 unsigned char* const* rows_to_convolve =
842 row_buffer.GetRowAddresses(&first_row_in_circular_buffer);
843
844 // Now compute the start of the subset of those rows that the filter
845 // needs.
846 unsigned char* const* first_row_for_filter =
847 &rows_to_convolve[filter_offset - first_row_in_circular_buffer];
848
849 if (source_has_alpha) {
850 if (use_sse2) {
851 ConvolveVertically_SSE2<true>(filter_values, filter_length,
852 first_row_for_filter,
853 filter_x.num_values(), cur_output_row);
854 } else {
855 ConvolveVertically<true>(filter_values, filter_length,
856 first_row_for_filter,
857 filter_x.num_values(), cur_output_row);
858 }
859 } else {
860 if (use_sse2) {
861 ConvolveVertically_SSE2<false>(filter_values, filter_length,
862 first_row_for_filter,
863 filter_x.num_values(), cur_output_row);
864 } else {
865 ConvolveVertically<false>(filter_values, filter_length,
866 first_row_for_filter,
867 filter_x.num_values(), cur_output_row);
868 }
869 }
870 }
871 } 433 }
872 434
435 void ConvolveVertically_SSE2(const ConvolutionFilter1D::Fixed* filter_values,
Stephen White 2013/04/05 08:40:47 It might be a good idea to add a similar wrapper f
hubbe 2013/04/06 20:45:46 Done.
436 int filter_length,
437 unsigned char* const* source_data_rows,
438 int pixel_width,
439 unsigned char* out_row,
440 bool has_alpha) {
441 if (has_alpha) {
442 ConvolveVertically_SSE2<true>(filter_values,
443 filter_length,
444 source_data_rows,
445 pixel_width,
446 out_row);
447 } else {
448 ConvolveVertically_SSE2<false>(filter_values,
449 filter_length,
450 source_data_rows,
451 pixel_width,
452 out_row);
453 }
454 }
455
873 } // namespace skia 456 } // namespace skia
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