SIMD implementation of Convolver for Lanczos filter etc.

skia/ext/convolver.cc

 // Copyright (c) 2011 The Chromium Authors. All rights reserved.
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
 #include <algorithm>
 
 #include "skia/ext/convolver.h"
 #include "third_party/skia/include/core/SkTypes.h"
 
+#if defined(ARCH_CPU_X86_FAMILY)
+#if defined(OS_WIN) || defined(__SSE2__)

[fbarchard, 2011/03/01 17:14:30]

I guess this is ok.  This is the expression I've tried lately:

#if defined(__x86_64__) || defined(_M_X64) || defined(__SSE2__) || _M_IX86_FP==2

which also works for /arch:AVX.
Another way to build your code is add attribute to your functions:
void ConvolveHorizontally_SSE2(
    const unsigned char* src_data,
    const ConvolutionFilter1D& filter,
    unsigned char* out_row)
    __attribute__ ((__target__ ("sse2")));

+#include <emmintrin.h>  // ARCH_CPU_X86_FAMILY was defined in build/config.h
+#endif
+#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)
@@ skipping 172 matching lines @@
     if (has_alpha)
       accum[3] >>= ConvolutionFilter1D::kShiftBits;
 
     // Store the new pixel.
     out_row[byte_offset + 0] = ClampTo8(accum[0]);
     out_row[byte_offset + 1] = ClampTo8(accum[1]);
     out_row[byte_offset + 2] = ClampTo8(accum[2]);
     if (has_alpha) {
       unsigned char alpha = ClampTo8(accum[3]);
 
-      // Make sure the alpha channel doesn't come out larger than any of the
+      // 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 + 0],
           std::max(out_row[byte_offset + 1], out_row[byte_offset + 2]));
       if (alpha < max_color_channel)
         out_row[byte_offset + 3] = max_color_channel;
       else
         out_row[byte_offset + 3] = alpha;
     } else {
       // No alpha channel, the image is opaque.
       out_row[byte_offset + 3] = 0xff;
     }
   }
 }
 
+

[fbarchard, 2011/03/01 17:14:30]

This strikes me as a lot of hard to maintain code, for a small win.  Its a small
win, mostly due to implementing it with intrinsics on 32 bit compilers.
I'd prefer see smaller amount of assembly, or move it to inline or yasm - if you
can achieve 5x or more, its interesting.

[jiesun, 2011/03/07 18:57:15]

the only speed up for this algorithm is parallelism, which we do 32 bits ( 4
elements in the same time) , therefore the maximum speedup of 4. certainly due
to Amdahl's law, you will achieve only partial speedup because some of them are
not able to make them parallel.

+// 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(ARCH_CPU_X86_FAMILY)
+#if defined(OS_WIN) || defined(__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
+#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(ARCH_CPU_X86_FAMILY)
+#if defined(OS_WIN) || defined(__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
+#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(ARCH_CPU_X86_FAMILY)
+#if defined(OS_WIN) || defined(__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
+#endif
+}
+
 }  // namespace
 
 // ConvolutionFilter1D ---------------------------------------------------------
 
 ConvolutionFilter1D::ConvolutionFilter1D()
     : max_filter_(0) {
 }
 
 ConvolutionFilter1D::~ConvolutionFilter1D() {
 }
@@ skipping 45 matching lines @@
   // 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);
 }
 
-// BGRAConvolve2D -------------------------------------------------------------
-
 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) {
+                    unsigned char* output,
+                    bool use_sse2) {
+#if defined(ARCH_CPU_X86_FAMILY)
+#if !defined(OS_WIN) && !defined(__SSE2__)
+  // even runtime support SSE2 instructions, we had not built with SSE2 support.

[brettw, 2011/03/03 17:56:19]

This comment doesn't really parse, can you reword (with capital letter at the
beginning, too).

[jiesun, 2011/03/07 18:57:15]

Done.

+  use_sse2 = false;
+#endif
+#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.
-  CircularRowBuffer row_buffer(filter_x.num_values(), max_y_filter_size,
+  // 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,

[brettw, 2011/03/03 17:56:19]

Spaces around -

[jiesun, 2011/03/07 18:57:15]

Done.

+                          &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.
-    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());
+    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];

[brettw, 2011/03/03 17:56:19]

Spaces around +

[jiesun, 2011/03/07 18:57:15]

Done.

+            out_row[i] = row_buffer.AdvanceRow();
+          }
+          ConvolveHorizontally4_SSE2(src, filter_x, out_row);
+          next_x_row+=4;

[brettw, 2011/03/03 17:56:19]

Spaces around +=

[jiesun, 2011/03/07 18:57:15]

Done.

+        } else {
+          // For the last row, SSE2 load possibly to access data beyond the
+          // image area. therefore we use C version here. Hacking into skia

[brettw, 2011/03/03 17:56:19]

I'd probably remove the sentence "Hacking into skia to add line paddings..."
since it doesn't really help here. 

[jiesun, 2011/03/07 18:57:15]

Done.

+          // to add line paddings is not something in my mind.
+          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++;
+        }
       }
-      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) {
-      ConvolveVertically<true>(filter_values, filter_length,
-                               first_row_for_filter,
-                               filter_x.num_values(), cur_output_row);
+      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 {
-      ConvolveVertically<false>(filter_values, filter_length,
-                                first_row_for_filter,
-                                filter_x.num_values(), cur_output_row);
+      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