| // 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(SIMD_SSE2) |
| #include <emmintrin.h> // 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<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> |
| 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<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 + 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 = 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; |
| } |
| } |
| } |
| |
| |
| // 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 |
