DXR is a code search and navigation tool aimed at making sense of large projects. It supports full-text and regex searches as well as structural queries.

Header

Mercurial (d1ed7de67f5a)

VCS Links

Line Code
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909
// Copyright (c) 2006-2011 The Chromium Authors. All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions
// are met:
//  * Redistributions of source code must retain the above copyright
//    notice, this list of conditions and the following disclaimer.
//  * Redistributions in binary form must reproduce the above copyright
//    notice, this list of conditions and the following disclaimer in
//    the documentation and/or other materials provided with the
//    distribution.
//  * Neither the name of Google, Inc. nor the names of its contributors
//    may be used to endorse or promote products derived from this
//    software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
// FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
// COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
// INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
// BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
// OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
// AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
// OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
// OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
// SUCH DAMAGE.

#include "convolver.h"

#include <algorithm>

#include "skia/SkTypes.h"

// note: SIMD_SSE2 is not enabled because of bugs, apparently

#if defined(SIMD_SSE2)
#include <emmintrin.h>  // ARCH_CPU_X86_FAMILY was defined in build/config.h
#endif

#if defined(SK_CPU_LENDIAN)
#define R_OFFSET_IDX 0
#define G_OFFSET_IDX 1
#define B_OFFSET_IDX 2
#define A_OFFSET_IDX 3
#else
#define R_OFFSET_IDX 3
#define G_OFFSET_IDX 2
#define B_OFFSET_IDX 1
#define A_OFFSET_IDX 0
#endif

namespace skia {

namespace {

// Converts the argument to an 8-bit unsigned value by clamping to the range
// 0-255.
inline unsigned char ClampTo8(int a) {
  if (static_cast<unsigned>(a) < 256)
    return a;  // Avoid the extra check in the common case.
  if (a < 0)
    return 0;
  return 255;
}

// Stores a list of rows in a circular buffer. The usage is you write into it
// by calling AdvanceRow. It will keep track of which row in the buffer it
// should use next, and the total number of rows added.
class CircularRowBuffer {
 public:
  // The number of pixels in each row is given in |source_row_pixel_width|.
  // The maximum number of rows needed in the buffer is |max_y_filter_size|
  // (we only need to store enough rows for the biggest filter).
  //
  // We use the |first_input_row| to compute the coordinates of all of the
  // following rows returned by Advance().
  CircularRowBuffer(int dest_row_pixel_width, int max_y_filter_size,
                    int first_input_row)
      : row_byte_width_(dest_row_pixel_width * 4),
        num_rows_(max_y_filter_size),
        next_row_(0),
        next_row_coordinate_(first_input_row) {
    buffer_.resize(row_byte_width_ * max_y_filter_size);
    row_addresses_.resize(num_rows_);
  }

  // Moves to the next row in the buffer, returning a pointer to the beginning
  // of it.
  unsigned char* AdvanceRow() {
    unsigned char* row = &buffer_[next_row_ * row_byte_width_];
    next_row_coordinate_++;

    // Set the pointer to the next row to use, wrapping around if necessary.
    next_row_++;
    if (next_row_ == num_rows_)
      next_row_ = 0;
    return row;
  }

  // Returns a pointer to an "unrolled" array of rows. These rows will start
  // at the y coordinate placed into |*first_row_index| and will continue in
  // order for the maximum number of rows in this circular buffer.
  //
  // The |first_row_index_| may be negative. This means the circular buffer
  // starts before the top of the image (it hasn't been filled yet).
  unsigned char* const* GetRowAddresses(int* first_row_index) {
    // Example for a 4-element circular buffer holding coords 6-9.
    //   Row 0   Coord 8
    //   Row 1   Coord 9
    //   Row 2   Coord 6  <- next_row_ = 2, next_row_coordinate_ = 10.
    //   Row 3   Coord 7
    //
    // The "next" row is also the first (lowest) coordinate. This computation
    // may yield a negative value, but that's OK, the math will work out
    // since the user of this buffer will compute the offset relative
    // to the first_row_index and the negative rows will never be used.
    *first_row_index = next_row_coordinate_ - num_rows_;

    int cur_row = next_row_;
    for (int i = 0; i < num_rows_; i++) {
      row_addresses_[i] = &buffer_[cur_row * row_byte_width_];

      // Advance to the next row, wrapping if necessary.
      cur_row++;
      if (cur_row == num_rows_)
        cur_row = 0;
    }
    return &row_addresses_[0];
  }

 private:
  // The buffer storing the rows. They are packed, each one row_byte_width_.
  std::vector<unsigned char> buffer_;

  // Number of bytes per row in the |buffer_|.
  int row_byte_width_;

  // The number of rows available in the buffer.
  int num_rows_;

  // The next row index we should write into. This wraps around as the
  // circular buffer is used.
  int next_row_;

  // The y coordinate of the |next_row_|. This is incremented each time a
  // new row is appended and does not wrap.
  int next_row_coordinate_;

  // Buffer used by GetRowAddresses().
  std::vector<unsigned char*> row_addresses_;
};

// Convolves horizontally along a single row. The row data is given in
// |src_data| and continues for the num_values() of the filter.
template<bool has_alpha>
// This function is miscompiled with gcc 4.5 with pgo. See bug 827946.
#if defined(__GNUC__) && defined(MOZ_GCC_VERSION_AT_LEAST)
#if MOZ_GCC_VERSION_AT_LEAST(4, 5, 0) && !MOZ_GCC_VERSION_AT_LEAST(4, 6, 0)
__attribute__((optimize("-O1")))
#endif
#endif
void ConvolveHorizontally(const unsigned char* src_data,
                          const ConvolutionFilter1D& filter,
                          unsigned char* out_row) {
  // Loop over each pixel on this row in the output image.
  int num_values = filter.num_values();
  for (int out_x = 0; out_x < num_values; out_x++) {
    // Get the filter that determines the current output pixel.
    int filter_offset, filter_length;
    const ConvolutionFilter1D::Fixed* filter_values =
        filter.FilterForValue(out_x, &filter_offset, &filter_length);

    // Compute the first pixel in this row that the filter affects. It will
    // touch |filter_length| pixels (4 bytes each) after this.
    const unsigned char* row_to_filter = &src_data[filter_offset * 4];

    // Apply the filter to the row to get the destination pixel in |accum|.
    int accum[4] = {0};
    for (int filter_x = 0; filter_x < filter_length; filter_x++) {
      ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_x];
      accum[0] += cur_filter * row_to_filter[filter_x * 4 + R_OFFSET_IDX];
      accum[1] += cur_filter * row_to_filter[filter_x * 4 + G_OFFSET_IDX];
      accum[2] += cur_filter * row_to_filter[filter_x * 4 + B_OFFSET_IDX];
      if (has_alpha)
        accum[3] += cur_filter * row_to_filter[filter_x * 4 + A_OFFSET_IDX];
    }

    // Bring this value back in range. All of the filter scaling factors
    // are in fixed point with kShiftBits bits of fractional part.
    accum[0] >>= ConvolutionFilter1D::kShiftBits;
    accum[1] >>= ConvolutionFilter1D::kShiftBits;
    accum[2] >>= ConvolutionFilter1D::kShiftBits;
    if (has_alpha)
      accum[3] >>= ConvolutionFilter1D::kShiftBits;

    // Store the new pixel.
    out_row[out_x * 4 + R_OFFSET_IDX] = ClampTo8(accum[0]);
    out_row[out_x * 4 + G_OFFSET_IDX] = ClampTo8(accum[1]);
    out_row[out_x * 4 + B_OFFSET_IDX] = ClampTo8(accum[2]);
    if (has_alpha)
      out_row[out_x * 4 + A_OFFSET_IDX] = ClampTo8(accum[3]);
  }
}

// Does vertical convolution to produce one output row. The filter values and
// length are given in the first two parameters. These are applied to each
// of the rows pointed to in the |source_data_rows| array, with each row
// being |pixel_width| wide.
//
// The output must have room for |pixel_width * 4| bytes.
template<bool has_alpha>
void ConvolveVertically(const ConvolutionFilter1D::Fixed* filter_values,
                        int filter_length,
                        unsigned char* const* source_data_rows,
                        int pixel_width,
                        unsigned char* out_row) {
  // We go through each column in the output and do a vertical convolution,
  // generating one output pixel each time.
  for (int out_x = 0; out_x < pixel_width; out_x++) {
    // Compute the number of bytes over in each row that the current column
    // we're convolving starts at. The pixel will cover the next 4 bytes.
    int byte_offset = out_x * 4;

    // Apply the filter to one column of pixels.
    int accum[4] = {0};
    for (int filter_y = 0; filter_y < filter_length; filter_y++) {
      ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_y];
      accum[0] += cur_filter 
	* source_data_rows[filter_y][byte_offset + R_OFFSET_IDX];
      accum[1] += cur_filter 
	* source_data_rows[filter_y][byte_offset + G_OFFSET_IDX];
      accum[2] += cur_filter 
	* source_data_rows[filter_y][byte_offset + B_OFFSET_IDX];
      if (has_alpha)
        accum[3] += cur_filter 
	  * source_data_rows[filter_y][byte_offset + A_OFFSET_IDX];
    }

    // Bring this value back in range. All of the filter scaling factors
    // are in fixed point with kShiftBits bits of precision.
    accum[0] >>= ConvolutionFilter1D::kShiftBits;
    accum[1] >>= ConvolutionFilter1D::kShiftBits;
    accum[2] >>= ConvolutionFilter1D::kShiftBits;
    if (has_alpha)
      accum[3] >>= ConvolutionFilter1D::kShiftBits;

    // Store the new pixel.
    out_row[byte_offset + R_OFFSET_IDX] = ClampTo8(accum[0]);
    out_row[byte_offset + G_OFFSET_IDX] = ClampTo8(accum[1]);
    out_row[byte_offset + B_OFFSET_IDX] = ClampTo8(accum[2]);
    if (has_alpha) {
      unsigned char alpha = ClampTo8(accum[3]);

      // Make sure the alpha channel doesn't come out smaller than any of the
      // color channels. We use premultipled alpha channels, so this should
      // never happen, but rounding errors will cause this from time to time.
      // These "impossible" colors will cause overflows (and hence random pixel
      // values) when the resulting bitmap is drawn to the screen.
      //
      // We only need to do this when generating the final output row (here).
      int max_color_channel = std::max(out_row[byte_offset + R_OFFSET_IDX],
          std::max(out_row[byte_offset + G_OFFSET_IDX], out_row[byte_offset + B_OFFSET_IDX]));
      if (alpha < max_color_channel)
        out_row[byte_offset + A_OFFSET_IDX] = max_color_channel;
      else
        out_row[byte_offset + A_OFFSET_IDX] = alpha;
    } else {
      // No alpha channel, the image is opaque.
      out_row[byte_offset + A_OFFSET_IDX] = 0xff;
    }
  }
}


// Convolves horizontally along a single row. The row data is given in
// |src_data| and continues for the num_values() of the filter.
void ConvolveHorizontally_SSE2(const unsigned char* src_data,
                               const ConvolutionFilter1D& filter,
                               unsigned char* out_row) {
#if defined(SIMD_SSE2)
  int num_values = filter.num_values();

  int filter_offset, filter_length;
  __m128i zero = _mm_setzero_si128();
  __m128i mask[4];
  // |mask| will be used to decimate all extra filter coefficients that are
  // loaded by SIMD when |filter_length| is not divisible by 4.
  // mask[0] is not used in following algorithm.
  mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1);
  mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1);
  mask[3] = _mm_set_epi16(0, 0, 0, 0, 0, -1, -1, -1);

  // Output one pixel each iteration, calculating all channels (RGBA) together.
  for (int out_x = 0; out_x < num_values; out_x++) {
    const ConvolutionFilter1D::Fixed* filter_values =
        filter.FilterForValue(out_x, &filter_offset, &filter_length);

    __m128i accum = _mm_setzero_si128();

    // Compute the first pixel in this row that the filter affects. It will
    // touch |filter_length| pixels (4 bytes each) after this.
    const __m128i* row_to_filter =
        reinterpret_cast<const __m128i*>(&src_data[filter_offset << 2]);

    // We will load and accumulate with four coefficients per iteration.
    for (int filter_x = 0; filter_x < filter_length >> 2; filter_x++) {

      // Load 4 coefficients => duplicate 1st and 2nd of them for all channels.
      __m128i coeff, coeff16;
      // [16] xx xx xx xx c3 c2 c1 c0
      coeff = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(filter_values));
      // [16] xx xx xx xx c1 c1 c0 c0
      coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(1, 1, 0, 0));
      // [16] c1 c1 c1 c1 c0 c0 c0 c0
      coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);

      // Load four pixels => unpack the first two pixels to 16 bits =>
      // multiply with coefficients => accumulate the convolution result.
      // [8] a3 b3 g3 r3 a2 b2 g2 r2 a1 b1 g1 r1 a0 b0 g0 r0
      __m128i src8 = _mm_loadu_si128(row_to_filter);
      // [16] a1 b1 g1 r1 a0 b0 g0 r0
      __m128i src16 = _mm_unpacklo_epi8(src8, zero);
      __m128i mul_hi = _mm_mulhi_epi16(src16, coeff16);
      __m128i mul_lo = _mm_mullo_epi16(src16, coeff16);
      // [32]  a0*c0 b0*c0 g0*c0 r0*c0
      __m128i t = _mm_unpacklo_epi16(mul_lo, mul_hi);
      accum = _mm_add_epi32(accum, t);
      // [32]  a1*c1 b1*c1 g1*c1 r1*c1
      t = _mm_unpackhi_epi16(mul_lo, mul_hi);
      accum = _mm_add_epi32(accum, t);

      // Duplicate 3rd and 4th coefficients for all channels =>
      // unpack the 3rd and 4th pixels to 16 bits => multiply with coefficients
      // => accumulate the convolution results.
      // [16] xx xx xx xx c3 c3 c2 c2
      coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(3, 3, 2, 2));
      // [16] c3 c3 c3 c3 c2 c2 c2 c2
      coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);
      // [16] a3 g3 b3 r3 a2 g2 b2 r2
      src16 = _mm_unpackhi_epi8(src8, zero);
      mul_hi = _mm_mulhi_epi16(src16, coeff16);
      mul_lo = _mm_mullo_epi16(src16, coeff16);
      // [32]  a2*c2 b2*c2 g2*c2 r2*c2
      t = _mm_unpacklo_epi16(mul_lo, mul_hi);
      accum = _mm_add_epi32(accum, t);
      // [32]  a3*c3 b3*c3 g3*c3 r3*c3
      t = _mm_unpackhi_epi16(mul_lo, mul_hi);
      accum = _mm_add_epi32(accum, t);

      // Advance the pixel and coefficients pointers.
      row_to_filter += 1;
      filter_values += 4;
    }

    // When |filter_length| is not divisible by 4, we need to decimate some of
    // the filter coefficient that was loaded incorrectly to zero; Other than
    // that the algorithm is same with above, exceot that the 4th pixel will be
    // always absent.
    int r = filter_length&3;
    if (r) {
      // Note: filter_values must be padded to align_up(filter_offset, 8).
      __m128i coeff, coeff16;
      coeff = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(filter_values));
      // Mask out extra filter taps.
      coeff = _mm_and_si128(coeff, mask[r]);
      coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(1, 1, 0, 0));
      coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);

      // Note: line buffer must be padded to align_up(filter_offset, 16).
      // We resolve this by use C-version for the last horizontal line.
      __m128i src8 = _mm_loadu_si128(row_to_filter);
      __m128i src16 = _mm_unpacklo_epi8(src8, zero);
      __m128i mul_hi = _mm_mulhi_epi16(src16, coeff16);
      __m128i mul_lo = _mm_mullo_epi16(src16, coeff16);
      __m128i t = _mm_unpacklo_epi16(mul_lo, mul_hi);
      accum = _mm_add_epi32(accum, t);
      t = _mm_unpackhi_epi16(mul_lo, mul_hi);
      accum = _mm_add_epi32(accum, t);

      src16 = _mm_unpackhi_epi8(src8, zero);
      coeff16 = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(3, 3, 2, 2));
      coeff16 = _mm_unpacklo_epi16(coeff16, coeff16);
      mul_hi = _mm_mulhi_epi16(src16, coeff16);
      mul_lo = _mm_mullo_epi16(src16, coeff16);
      t = _mm_unpacklo_epi16(mul_lo, mul_hi);
      accum = _mm_add_epi32(accum, t);
    }

    // Shift right for fixed point implementation.
    accum = _mm_srai_epi32(accum, ConvolutionFilter1D::kShiftBits);

    // Packing 32 bits |accum| to 16 bits per channel (signed saturation).
    accum = _mm_packs_epi32(accum, zero);
    // Packing 16 bits |accum| to 8 bits per channel (unsigned saturation).
    accum = _mm_packus_epi16(accum, zero);

    // Store the pixel value of 32 bits.
    *(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum);
    out_row += 4;
  }
#endif
}

// Convolves horizontally along four rows. The row data is given in
// |src_data| and continues for the num_values() of the filter.
// The algorithm is almost same as |ConvolveHorizontally_SSE2|. Please
// refer to that function for detailed comments.
void ConvolveHorizontally4_SSE2(const unsigned char* src_data[4],
                                const ConvolutionFilter1D& filter,
                                unsigned char* out_row[4]) {
#if defined(SIMD_SSE2)
  int num_values = filter.num_values();

  int filter_offset, filter_length;
  __m128i zero = _mm_setzero_si128();
  __m128i mask[4];
  // |mask| will be used to decimate all extra filter coefficients that are
  // loaded by SIMD when |filter_length| is not divisible by 4.
  // mask[0] is not used in following algorithm.
  mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1);
  mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1);
  mask[3] = _mm_set_epi16(0, 0, 0, 0, 0, -1, -1, -1);

  // Output one pixel each iteration, calculating all channels (RGBA) together.
  for (int out_x = 0; out_x < num_values; out_x++) {
    const ConvolutionFilter1D::Fixed* filter_values =
        filter.FilterForValue(out_x, &filter_offset, &filter_length);

    // four pixels in a column per iteration.
    __m128i accum0 = _mm_setzero_si128();
    __m128i accum1 = _mm_setzero_si128();
    __m128i accum2 = _mm_setzero_si128();
    __m128i accum3 = _mm_setzero_si128();
    int start = (filter_offset<<2);
    // We will load and accumulate with four coefficients per iteration.
    for (int filter_x = 0; filter_x < (filter_length >> 2); filter_x++) {
      __m128i coeff, coeff16lo, coeff16hi;
      // [16] xx xx xx xx c3 c2 c1 c0
      coeff = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(filter_values));
      // [16] xx xx xx xx c1 c1 c0 c0
      coeff16lo = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(1, 1, 0, 0));
      // [16] c1 c1 c1 c1 c0 c0 c0 c0
      coeff16lo = _mm_unpacklo_epi16(coeff16lo, coeff16lo);
      // [16] xx xx xx xx c3 c3 c2 c2
      coeff16hi = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(3, 3, 2, 2));
      // [16] c3 c3 c3 c3 c2 c2 c2 c2
      coeff16hi = _mm_unpacklo_epi16(coeff16hi, coeff16hi);

      __m128i src8, src16, mul_hi, mul_lo, t;

#define ITERATION(src, accum)                                          \
      src8 = _mm_loadu_si128(reinterpret_cast<const __m128i*>(src));   \
      src16 = _mm_unpacklo_epi8(src8, zero);                           \
      mul_hi = _mm_mulhi_epi16(src16, coeff16lo);                      \
      mul_lo = _mm_mullo_epi16(src16, coeff16lo);                      \
      t = _mm_unpacklo_epi16(mul_lo, mul_hi);                          \
      accum = _mm_add_epi32(accum, t);                                 \
      t = _mm_unpackhi_epi16(mul_lo, mul_hi);                          \
      accum = _mm_add_epi32(accum, t);                                 \
      src16 = _mm_unpackhi_epi8(src8, zero);                           \
      mul_hi = _mm_mulhi_epi16(src16, coeff16hi);                      \
      mul_lo = _mm_mullo_epi16(src16, coeff16hi);                      \
      t = _mm_unpacklo_epi16(mul_lo, mul_hi);                          \
      accum = _mm_add_epi32(accum, t);                                 \
      t = _mm_unpackhi_epi16(mul_lo, mul_hi);                          \
      accum = _mm_add_epi32(accum, t)

      ITERATION(src_data[0] + start, accum0);
      ITERATION(src_data[1] + start, accum1);
      ITERATION(src_data[2] + start, accum2);
      ITERATION(src_data[3] + start, accum3);

      start += 16;
      filter_values += 4;
    }

    int r = filter_length & 3;
    if (r) {
      // Note: filter_values must be padded to align_up(filter_offset, 8);
      __m128i coeff;
      coeff = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(filter_values));
      // Mask out extra filter taps.
      coeff = _mm_and_si128(coeff, mask[r]);

      __m128i coeff16lo = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(1, 1, 0, 0));
      /* c1 c1 c1 c1 c0 c0 c0 c0 */
      coeff16lo = _mm_unpacklo_epi16(coeff16lo, coeff16lo);
      __m128i coeff16hi = _mm_shufflelo_epi16(coeff, _MM_SHUFFLE(3, 3, 2, 2));
      coeff16hi = _mm_unpacklo_epi16(coeff16hi, coeff16hi);

      __m128i src8, src16, mul_hi, mul_lo, t;

      ITERATION(src_data[0] + start, accum0);
      ITERATION(src_data[1] + start, accum1);
      ITERATION(src_data[2] + start, accum2);
      ITERATION(src_data[3] + start, accum3);
    }

    accum0 = _mm_srai_epi32(accum0, ConvolutionFilter1D::kShiftBits);
    accum0 = _mm_packs_epi32(accum0, zero);
    accum0 = _mm_packus_epi16(accum0, zero);
    accum1 = _mm_srai_epi32(accum1, ConvolutionFilter1D::kShiftBits);
    accum1 = _mm_packs_epi32(accum1, zero);
    accum1 = _mm_packus_epi16(accum1, zero);
    accum2 = _mm_srai_epi32(accum2, ConvolutionFilter1D::kShiftBits);
    accum2 = _mm_packs_epi32(accum2, zero);
    accum2 = _mm_packus_epi16(accum2, zero);
    accum3 = _mm_srai_epi32(accum3, ConvolutionFilter1D::kShiftBits);
    accum3 = _mm_packs_epi32(accum3, zero);
    accum3 = _mm_packus_epi16(accum3, zero);

    *(reinterpret_cast<int*>(out_row[0])) = _mm_cvtsi128_si32(accum0);
    *(reinterpret_cast<int*>(out_row[1])) = _mm_cvtsi128_si32(accum1);
    *(reinterpret_cast<int*>(out_row[2])) = _mm_cvtsi128_si32(accum2);
    *(reinterpret_cast<int*>(out_row[3])) = _mm_cvtsi128_si32(accum3);

    out_row[0] += 4;
    out_row[1] += 4;
    out_row[2] += 4;
    out_row[3] += 4;
  }
#endif
}

// Does vertical convolution to produce one output row. The filter values and
// length are given in the first two parameters. These are applied to each
// of the rows pointed to in the |source_data_rows| array, with each row
// being |pixel_width| wide.
//
// The output must have room for |pixel_width * 4| bytes.
template<bool has_alpha>
void ConvolveVertically_SSE2(const ConvolutionFilter1D::Fixed* filter_values,
                             int filter_length,
                             unsigned char* const* source_data_rows,
                             int pixel_width,
                             unsigned char* out_row) {
#if defined(SIMD_SSE2)
  int width = pixel_width & ~3;

  __m128i zero = _mm_setzero_si128();
  __m128i accum0, accum1, accum2, accum3, coeff16;
  const __m128i* src;
  // Output four pixels per iteration (16 bytes).
  for (int out_x = 0; out_x < width; out_x += 4) {

    // Accumulated result for each pixel. 32 bits per RGBA channel.
    accum0 = _mm_setzero_si128();
    accum1 = _mm_setzero_si128();
    accum2 = _mm_setzero_si128();
    accum3 = _mm_setzero_si128();

    // Convolve with one filter coefficient per iteration.
    for (int filter_y = 0; filter_y < filter_length; filter_y++) {

      // Duplicate the filter coefficient 8 times.
      // [16] cj cj cj cj cj cj cj cj
      coeff16 = _mm_set1_epi16(filter_values[filter_y]);

      // Load four pixels (16 bytes) together.
      // [8] a3 b3 g3 r3 a2 b2 g2 r2 a1 b1 g1 r1 a0 b0 g0 r0
      src = reinterpret_cast<const __m128i*>(
          &source_data_rows[filter_y][out_x << 2]);
      __m128i src8 = _mm_loadu_si128(src);

      // Unpack 1st and 2nd pixels from 8 bits to 16 bits for each channels =>
      // multiply with current coefficient => accumulate the result.
      // [16] a1 b1 g1 r1 a0 b0 g0 r0
      __m128i src16 = _mm_unpacklo_epi8(src8, zero);
      __m128i mul_hi = _mm_mulhi_epi16(src16, coeff16);
      __m128i mul_lo = _mm_mullo_epi16(src16, coeff16);
      // [32] a0 b0 g0 r0
      __m128i t = _mm_unpacklo_epi16(mul_lo, mul_hi);
      accum0 = _mm_add_epi32(accum0, t);
      // [32] a1 b1 g1 r1
      t = _mm_unpackhi_epi16(mul_lo, mul_hi);
      accum1 = _mm_add_epi32(accum1, t);

      // Unpack 3rd and 4th pixels from 8 bits to 16 bits for each channels =>
      // multiply with current coefficient => accumulate the result.
      // [16] a3 b3 g3 r3 a2 b2 g2 r2
      src16 = _mm_unpackhi_epi8(src8, zero);
      mul_hi = _mm_mulhi_epi16(src16, coeff16);
      mul_lo = _mm_mullo_epi16(src16, coeff16);
      // [32] a2 b2 g2 r2
      t = _mm_unpacklo_epi16(mul_lo, mul_hi);
      accum2 = _mm_add_epi32(accum2, t);
      // [32] a3 b3 g3 r3
      t = _mm_unpackhi_epi16(mul_lo, mul_hi);
      accum3 = _mm_add_epi32(accum3, t);
    }

    // Shift right for fixed point implementation.
    accum0 = _mm_srai_epi32(accum0, ConvolutionFilter1D::kShiftBits);
    accum1 = _mm_srai_epi32(accum1, ConvolutionFilter1D::kShiftBits);
    accum2 = _mm_srai_epi32(accum2, ConvolutionFilter1D::kShiftBits);
    accum3 = _mm_srai_epi32(accum3, ConvolutionFilter1D::kShiftBits);

    // Packing 32 bits |accum| to 16 bits per channel (signed saturation).
    // [16] a1 b1 g1 r1 a0 b0 g0 r0
    accum0 = _mm_packs_epi32(accum0, accum1);
    // [16] a3 b3 g3 r3 a2 b2 g2 r2
    accum2 = _mm_packs_epi32(accum2, accum3);

    // Packing 16 bits |accum| to 8 bits per channel (unsigned saturation).
    // [8] a3 b3 g3 r3 a2 b2 g2 r2 a1 b1 g1 r1 a0 b0 g0 r0
    accum0 = _mm_packus_epi16(accum0, accum2);

    if (has_alpha) {
      // Compute the max(ri, gi, bi) for each pixel.
      // [8] xx a3 b3 g3 xx a2 b2 g2 xx a1 b1 g1 xx a0 b0 g0
      __m128i a = _mm_srli_epi32(accum0, 8);
      // [8] xx xx xx max3 xx xx xx max2 xx xx xx max1 xx xx xx max0
      __m128i b = _mm_max_epu8(a, accum0);  // Max of r and g.
      // [8] xx xx a3 b3 xx xx a2 b2 xx xx a1 b1 xx xx a0 b0
      a = _mm_srli_epi32(accum0, 16);
      // [8] xx xx xx max3 xx xx xx max2 xx xx xx max1 xx xx xx max0
      b = _mm_max_epu8(a, b);  // Max of r and g and b.
      // [8] max3 00 00 00 max2 00 00 00 max1 00 00 00 max0 00 00 00
      b = _mm_slli_epi32(b, 24);

      // Make sure the value of alpha channel is always larger than maximum
      // value of color channels.
      accum0 = _mm_max_epu8(b, accum0);
    } else {
      // Set value of alpha channels to 0xFF.
      __m128i mask = _mm_set1_epi32(0xff000000);
      accum0 = _mm_or_si128(accum0, mask);
    }

    // Store the convolution result (16 bytes) and advance the pixel pointers.
    _mm_storeu_si128(reinterpret_cast<__m128i*>(out_row), accum0);
    out_row += 16;
  }

  // When the width of the output is not divisible by 4, We need to save one
  // pixel (4 bytes) each time. And also the fourth pixel is always absent.
  if (pixel_width & 3) {
    accum0 = _mm_setzero_si128();
    accum1 = _mm_setzero_si128();
    accum2 = _mm_setzero_si128();
    for (int filter_y = 0; filter_y < filter_length; ++filter_y) {
      coeff16 = _mm_set1_epi16(filter_values[filter_y]);
      // [8] a3 b3 g3 r3 a2 b2 g2 r2 a1 b1 g1 r1 a0 b0 g0 r0
      src = reinterpret_cast<const __m128i*>(
          &source_data_rows[filter_y][width<<2]);
      __m128i src8 = _mm_loadu_si128(src);
      // [16] a1 b1 g1 r1 a0 b0 g0 r0
      __m128i src16 = _mm_unpacklo_epi8(src8, zero);
      __m128i mul_hi = _mm_mulhi_epi16(src16, coeff16);
      __m128i mul_lo = _mm_mullo_epi16(src16, coeff16);
      // [32] a0 b0 g0 r0
      __m128i t = _mm_unpacklo_epi16(mul_lo, mul_hi);
      accum0 = _mm_add_epi32(accum0, t);
      // [32] a1 b1 g1 r1
      t = _mm_unpackhi_epi16(mul_lo, mul_hi);
      accum1 = _mm_add_epi32(accum1, t);
      // [16] a3 b3 g3 r3 a2 b2 g2 r2
      src16 = _mm_unpackhi_epi8(src8, zero);
      mul_hi = _mm_mulhi_epi16(src16, coeff16);
      mul_lo = _mm_mullo_epi16(src16, coeff16);
      // [32] a2 b2 g2 r2
      t = _mm_unpacklo_epi16(mul_lo, mul_hi);
      accum2 = _mm_add_epi32(accum2, t);
    }

    accum0 = _mm_srai_epi32(accum0, ConvolutionFilter1D::kShiftBits);
    accum1 = _mm_srai_epi32(accum1, ConvolutionFilter1D::kShiftBits);
    accum2 = _mm_srai_epi32(accum2, ConvolutionFilter1D::kShiftBits);
    // [16] a1 b1 g1 r1 a0 b0 g0 r0
    accum0 = _mm_packs_epi32(accum0, accum1);
    // [16] a3 b3 g3 r3 a2 b2 g2 r2
    accum2 = _mm_packs_epi32(accum2, zero);
    // [8] a3 b3 g3 r3 a2 b2 g2 r2 a1 b1 g1 r1 a0 b0 g0 r0
    accum0 = _mm_packus_epi16(accum0, accum2);
    if (has_alpha) {
      // [8] xx a3 b3 g3 xx a2 b2 g2 xx a1 b1 g1 xx a0 b0 g0
      __m128i a = _mm_srli_epi32(accum0, 8);
      // [8] xx xx xx max3 xx xx xx max2 xx xx xx max1 xx xx xx max0
      __m128i b = _mm_max_epu8(a, accum0);  // Max of r and g.
      // [8] xx xx a3 b3 xx xx a2 b2 xx xx a1 b1 xx xx a0 b0
      a = _mm_srli_epi32(accum0, 16);
      // [8] xx xx xx max3 xx xx xx max2 xx xx xx max1 xx xx xx max0
      b = _mm_max_epu8(a, b);  // Max of r and g and b.
      // [8] max3 00 00 00 max2 00 00 00 max1 00 00 00 max0 00 00 00
      b = _mm_slli_epi32(b, 24);
      accum0 = _mm_max_epu8(b, accum0);
    } else {
      __m128i mask = _mm_set1_epi32(0xff000000);
      accum0 = _mm_or_si128(accum0, mask);
    }

    for (int out_x = width; out_x < pixel_width; out_x++) {
      *(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum0);
      accum0 = _mm_srli_si128(accum0, 4);
      out_row += 4;
    }
  }
#endif
}

}  // namespace

// ConvolutionFilter1D ---------------------------------------------------------

ConvolutionFilter1D::ConvolutionFilter1D()
    : max_filter_(0) {
}

ConvolutionFilter1D::~ConvolutionFilter1D() {
}

void ConvolutionFilter1D::AddFilter(int filter_offset,
                                    const float* filter_values,
                                    int filter_length) {
  SkASSERT(filter_length > 0);

  std::vector<Fixed> fixed_values;
  fixed_values.reserve(filter_length);

  for (int i = 0; i < filter_length; ++i)
    fixed_values.push_back(FloatToFixed(filter_values[i]));

  AddFilter(filter_offset, &fixed_values[0], filter_length);
}

void ConvolutionFilter1D::AddFilter(int filter_offset,
                                    const Fixed* filter_values,
                                    int filter_length) {
  // It is common for leading/trailing filter values to be zeros. In such
  // cases it is beneficial to only store the central factors.
  // For a scaling to 1/4th in each dimension using a Lanczos-2 filter on
  // a 1080p image this optimization gives a ~10% speed improvement.
  int first_non_zero = 0;
  while (first_non_zero < filter_length && filter_values[first_non_zero] == 0)
    first_non_zero++;

  if (first_non_zero < filter_length) {
    // Here we have at least one non-zero factor.
    int last_non_zero = filter_length - 1;
    while (last_non_zero >= 0 && filter_values[last_non_zero] == 0)
      last_non_zero--;

    filter_offset += first_non_zero;
    filter_length = last_non_zero + 1 - first_non_zero;
    SkASSERT(filter_length > 0);

    for (int i = first_non_zero; i <= last_non_zero; i++)
      filter_values_.push_back(filter_values[i]);
  } else {
    // Here all the factors were zeroes.
    filter_length = 0;
  }

  FilterInstance instance;

  // We pushed filter_length elements onto filter_values_
  instance.data_location = (static_cast<int>(filter_values_.size()) -
                            filter_length);
  instance.offset = filter_offset;
  instance.length = filter_length;
  filters_.push_back(instance);

  max_filter_ = std::max(max_filter_, filter_length);
}

void BGRAConvolve2D(const unsigned char* source_data,
                    int source_byte_row_stride,
                    bool source_has_alpha,
                    const ConvolutionFilter1D& filter_x,
                    const ConvolutionFilter1D& filter_y,
                    int output_byte_row_stride,
                    unsigned char* output,
                    bool use_sse2) {
#if !defined(SIMD_SSE2)
  // Even we have runtime support for SSE2 instructions, since the binary
  // was not built with SSE2 support, we had to fallback to C version.
  use_sse2 = false;
#endif

  int max_y_filter_size = filter_y.max_filter();

  // The next row in the input that we will generate a horizontally
  // convolved row for. If the filter doesn't start at the beginning of the
  // image (this is the case when we are only resizing a subset), then we
  // don't want to generate any output rows before that. Compute the starting
  // row for convolution as the first pixel for the first vertical filter.
  int filter_offset, filter_length;
  const ConvolutionFilter1D::Fixed* filter_values =
      filter_y.FilterForValue(0, &filter_offset, &filter_length);
  int next_x_row = filter_offset;

  // We loop over each row in the input doing a horizontal convolution. This
  // will result in a horizontally convolved image. We write the results into
  // a circular buffer of convolved rows and do vertical convolution as rows
  // are available. This prevents us from having to store the entire
  // intermediate image and helps cache coherency.
  // We will need four extra rows to allow horizontal convolution could be done
  // simultaneously. We also padding each row in row buffer to be aligned-up to
  // 16 bytes.
  // TODO(jiesun): We do not use aligned load from row buffer in vertical
  // convolution pass yet. Somehow Windows does not like it.
  int row_buffer_width = (filter_x.num_values() + 15) & ~0xF;
  int row_buffer_height = max_y_filter_size + (use_sse2 ? 4 : 0);
  CircularRowBuffer row_buffer(row_buffer_width,
                               row_buffer_height,
                               filter_offset);

  // Loop over every possible output row, processing just enough horizontal
  // convolutions to run each subsequent vertical convolution.
  SkASSERT(output_byte_row_stride >= filter_x.num_values() * 4);
  int num_output_rows = filter_y.num_values();

  // We need to check which is the last line to convolve before we advance 4
  // lines in one iteration.
  int last_filter_offset, last_filter_length;
  filter_y.FilterForValue(num_output_rows - 1, &last_filter_offset,
                          &last_filter_length);

  for (int out_y = 0; out_y < num_output_rows; out_y++) {
    filter_values = filter_y.FilterForValue(out_y,
                                            &filter_offset, &filter_length);

    // Generate output rows until we have enough to run the current filter.
    if (use_sse2) {
      while (next_x_row < filter_offset + filter_length) {
        if (next_x_row + 3 < last_filter_offset + last_filter_length - 1) {
          const unsigned char* src[4];
          unsigned char* out_row[4];
          for (int i = 0; i < 4; ++i) {
            src[i] = &source_data[(next_x_row + i) * source_byte_row_stride];
            out_row[i] = row_buffer.AdvanceRow();
          }
          ConvolveHorizontally4_SSE2(src, filter_x, out_row);
          next_x_row += 4;
        } else {
          // For the last row, SSE2 load possibly to access data beyond the
          // image area. therefore we use C version here. 
          if (next_x_row == last_filter_offset + last_filter_length - 1) {
            if (source_has_alpha) {
              ConvolveHorizontally<true>(
                  &source_data[next_x_row * source_byte_row_stride],
                  filter_x, row_buffer.AdvanceRow());
            } else {
              ConvolveHorizontally<false>(
                  &source_data[next_x_row * source_byte_row_stride],
                  filter_x, row_buffer.AdvanceRow());
            }
          } else {
            ConvolveHorizontally_SSE2(
                &source_data[next_x_row * source_byte_row_stride],
                filter_x, row_buffer.AdvanceRow());
          }
          next_x_row++;
        }
      }
    } else {
      while (next_x_row < filter_offset + filter_length) {
        if (source_has_alpha) {
          ConvolveHorizontally<true>(
              &source_data[next_x_row * source_byte_row_stride],
              filter_x, row_buffer.AdvanceRow());
        } else {
          ConvolveHorizontally<false>(
              &source_data[next_x_row * source_byte_row_stride],
              filter_x, row_buffer.AdvanceRow());
        }
        next_x_row++;
      }
    }

    // Compute where in the output image this row of final data will go.
    unsigned char* cur_output_row = &output[out_y * output_byte_row_stride];

    // Get the list of rows that the circular buffer has, in order.
    int first_row_in_circular_buffer;
    unsigned char* const* rows_to_convolve =
        row_buffer.GetRowAddresses(&first_row_in_circular_buffer);

    // Now compute the start of the subset of those rows that the filter
    // needs.
    unsigned char* const* first_row_for_filter =
        &rows_to_convolve[filter_offset - first_row_in_circular_buffer];

    if (source_has_alpha) {
      if (use_sse2) {
        ConvolveVertically_SSE2<true>(filter_values, filter_length,
                                      first_row_for_filter,
                                      filter_x.num_values(), cur_output_row);
      } else {
        ConvolveVertically<true>(filter_values, filter_length,
                                 first_row_for_filter,
                                 filter_x.num_values(), cur_output_row);
      }
    } else {
      if (use_sse2) {
        ConvolveVertically_SSE2<false>(filter_values, filter_length,
                                       first_row_for_filter,
                                       filter_x.num_values(), cur_output_row);
      } else {
        ConvolveVertically<false>(filter_values, filter_length,
                                 first_row_for_filter,
                                 filter_x.num_values(), cur_output_row);
      }
    }
  }
}

}  // namespace skia