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 // 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