// 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 "convolver.h" #include #include "nsAlgorithm.h" #include "skia/SkTypes.h" // note: SIMD_SSE2 is not enabled because of bugs, apparently #if defined(SIMD_SSE2) #include // ARCH_CPU_X86_FAMILY was defined in build/config.h #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(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 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 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 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 + 0]; accum[1] += cur_filter * row_to_filter[filter_x * 4 + 1]; accum[2] += cur_filter * row_to_filter[filter_x * 4 + 2]; if (has_alpha) accum[3] += cur_filter * row_to_filter[filter_x * 4 + 3]; } // 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 + 0] = ClampTo8(accum[0]); out_row[out_x * 4 + 1] = ClampTo8(accum[1]); out_row[out_x * 4 + 2] = ClampTo8(accum[2]); if (has_alpha) out_row[out_x * 4 + 3] = 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 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 + 0]; accum[1] += cur_filter * source_data_rows[filter_y][byte_offset + 1]; accum[2] += cur_filter * source_data_rows[filter_y][byte_offset + 2]; if (has_alpha) accum[3] += cur_filter * source_data_rows[filter_y][byte_offset + 3]; } // 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 + 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 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 = NS_MAX(out_row[byte_offset + 0], NS_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; } } } // 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(&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(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(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(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(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(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(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(out_row[0])) = _mm_cvtsi128_si32(accum0); *(reinterpret_cast(out_row[1])) = _mm_cvtsi128_si32(accum1); *(reinterpret_cast(out_row[2])) = _mm_cvtsi128_si32(accum2); *(reinterpret_cast(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 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( &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( &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(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_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(filter_values_.size()) - filter_length); instance.offset = filter_offset; instance.length = filter_length; filters_.push_back(instance); max_filter_ = NS_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( &source_data[next_x_row * source_byte_row_stride], filter_x, row_buffer.AdvanceRow()); } else { ConvolveHorizontally( &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( &source_data[next_x_row * source_byte_row_stride], filter_x, row_buffer.AdvanceRow()); } else { ConvolveHorizontally( &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(filter_values, filter_length, first_row_for_filter, filter_x.num_values(), cur_output_row); } else { ConvolveVertically(filter_values, filter_length, first_row_for_filter, filter_x.num_values(), cur_output_row); } } else { if (use_sse2) { ConvolveVertically_SSE2(filter_values, filter_length, first_row_for_filter, filter_x.num_values(), cur_output_row); } else { ConvolveVertically(filter_values, filter_length, first_row_for_filter, filter_x.num_values(), cur_output_row); } } } } } // namespace skia