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///
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/// @file fdwt97.cu
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/// @brief CUDA implementation of forward 9/7 2D DWT.
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/// @author Martin Jirman (207962@mail.muni.cz)
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/// @date 2011-01-20 13:18
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///
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///
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/// Copyright (c) 2011 Martin Jirman
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/// All rights reserved.
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///
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/// Redistribution and use in source and binary forms, with or without
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/// modification, are permitted provided that the following conditions are met:
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///
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/// * Redistributions of source code must retain the above copyright
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/// notice, this list of conditions and the following disclaimer.
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/// * Redistributions in binary form must reproduce the above copyright
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/// notice, this list of conditions and the following disclaimer in the
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/// documentation and/or other materials provided with the distribution.
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///
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/// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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/// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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/// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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/// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
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/// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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/// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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/// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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/// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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/// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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/// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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/// POSSIBILITY OF SUCH DAMAGE.
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///
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#include "common.h"
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#include "transform_buffer.h"
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#include "io.h"
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namespace dwt_cuda {
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/// Wraps a buffer and methods for computing 9/7 FDWT with sliding window
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/// of specified size. Template arguments specify this size.
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/// @tparam WIN_SIZE_X width of sliding window
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/// @tparam WIN_SIZE_Y height of sliding window
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template <int WIN_SIZE_X, int WIN_SIZE_Y>
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class FDWT97 {
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private:
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/// Type of shared memory buffer used for 9/7 DWT.
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typedef TransformBuffer<float, WIN_SIZE_X, WIN_SIZE_Y + 7, 4> FDWT97Buffer;
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/// Actual shared buffer used for forward 9/7 DWT.
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FDWT97Buffer buffer;
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/// Difference of indices of two vertically neighboring items in buffer.
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enum { STRIDE = FDWT97Buffer::VERTICAL_STRIDE };
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/// One thread's info about loading input image
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/// @tparam CHECKED true if loader should check for image boundaries
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template <bool CHECKED>
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struct FDWT97ColumnLoadingInfo {
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/// Loader of pixels from some input image.
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VerticalDWTPixelLoader<float, CHECKED> loader;
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/// Offset of column loaded by loader. (Offset in shared buffer.)
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int offset;
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};
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/// Horizontal 9/7 FDWT on specified lines of transform buffer.
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/// @param lines number of lines to be transformed
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/// @param firstLine index of the first line to be transformed
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__device__ void horizontalFDWT97(const int lines, const int firstLine) {
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__syncthreads();
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buffer.forEachHorizontalOdd(firstLine, lines, AddScaledSum(f97Predict1));
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__syncthreads();
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buffer.forEachHorizontalEven(firstLine, lines, AddScaledSum(f97Update1));
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__syncthreads();
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buffer.forEachHorizontalOdd(firstLine, lines, AddScaledSum(f97Predict2));
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__syncthreads();
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buffer.forEachHorizontalEven(firstLine, lines, AddScaledSum(f97Update2));
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__syncthreads();
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buffer.scaleHorizontal(scale97Div, scale97Mul, firstLine, lines);
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__syncthreads();
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}
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/// Initializes one column of shared transform buffer with 7 input pixels.
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/// Those 7 pixels will not be transformed. Also initializes given loader.
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/// @tparam CHECKED true if loader should check for image boundaries
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/// @param column (uninitialized) object for loading input pixels
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/// @param columnIndex index (not offset!) of the column to be loaded
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/// (relative to threadblock's first column)
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/// @param input pointer to input image in GPU memory
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/// @param sizeX width of the input image
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/// @param sizeY height of the input image
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/// @param firstY index of first row to be loaded from image
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template <bool CHECKED>
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__device__ void initColumn(FDWT97ColumnLoadingInfo<CHECKED> & column,
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const int columnIndex, const float * const input,
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const int sizeX, const int sizeY,
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const int firstY) {
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// get offset of the column with index 'columnIndex'
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column.offset = buffer.getColumnOffset(columnIndex);
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// printf(" offset: %d , threadIdx: %d, blockIdx.y %d\n ", column.offset, threadIdx.x, blockIdx.y);
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// x-coordinate of the first pixel to be loaded by given loader
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const int firstX = blockIdx.x * WIN_SIZE_X + columnIndex;
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if(blockIdx.y == 0) {
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// topmost block - apply mirroring rules when loading first 7 rows
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column.loader.init(sizeX, sizeY, firstX, firstY);
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// load pixels in mirrored way
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buffer[column.offset + 4 * STRIDE] = column.loader.loadFrom(input);
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buffer[column.offset + 3 * STRIDE] =
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buffer[column.offset + 5 * STRIDE] = column.loader.loadFrom(input);
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buffer[column.offset + 2 * STRIDE] =
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buffer[column.offset + 6 * STRIDE] = column.loader.loadFrom(input);
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buffer[column.offset + 1 * STRIDE] = column.loader.loadFrom(input);
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buffer[column.offset + 0 * STRIDE] = column.loader.loadFrom(input);
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// reinitialize loader to start with pixel #3 again
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column.loader.init(sizeX, sizeY, firstX, firstY + 3);
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} else {
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// non-topmost row - regular loading:
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column.loader.init(sizeX, sizeY, firstX, firstY - 4);
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// load 7 rows into the transform buffer
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for(int i = 0; i < 7; i++) {
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buffer[column.offset + i * STRIDE] = column.loader.loadFrom(input);
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}
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}
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// Now, the next pixel, which will be loaded by loader, is pixel #3.
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}
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/// Loads another WIN_SIZE_Y pixels into given column using given loader.
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/// @tparam CHECKED true if loader should check for image boundaries
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/// @param input input image to load from
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/// @param column loader and offset of loaded column in shared buffer
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template <bool CHECKED>
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inline __device__ void loadWindowIntoColumn(const float * const input,
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FDWT97ColumnLoadingInfo<CHECKED> & column) {
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for(int i = 7; i < (7 + WIN_SIZE_Y); i++) {
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buffer[column.offset + i * STRIDE] = column.loader.loadFrom(input);
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}
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}
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/// Main GPU 9/7 FDWT entry point.
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/// @tparam CHECK_LOADS true if boundaries should be checked when loading
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/// @tparam CHECK_WRITES true if boundaries should be checked when writing
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/// @param in input image
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/// @param out output buffer
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/// @param sizeX width of the input image
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/// @param sizeY height of the input image
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/// @param winSteps number of steps of sliding window
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template <bool CHECK_LOADS, bool CHECK_WRITES>
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__device__ void transform(const float * const in, float * const out,
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const int sizeX, const int sizeY,
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const int winSteps) {
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// info about columns loaded by this thread: one main column and possibly
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// one boundary column. (Only some threads load some boundary column.)
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FDWT97ColumnLoadingInfo<CHECK_LOADS> loadedColumn;
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FDWT97ColumnLoadingInfo<CHECK_LOADS> boundaryColumn;
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// Initialize first 7 lines of transform buffer.
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const int firstY = blockIdx.y * WIN_SIZE_Y * winSteps;
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initColumn(loadedColumn, threadIdx.x, in, sizeX, sizeY, firstY);
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// Some threads initialize boundary columns.
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boundaryColumn.offset = 0;
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boundaryColumn.loader.clear();
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if(threadIdx.x < 7) {
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// each thread among first 7 ones gets index of one of boundary columns
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const int colId = threadIdx.x + ((threadIdx.x < 3) ? WIN_SIZE_X : -7);
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// Thread initializes offset of the boundary column (in shared buffer),
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// first 7 pixels of the column and a loader for this column.
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initColumn(boundaryColumn, colId, in, sizeX, sizeY, firstY);
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}
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// horizontally transform first 7 rows in all columns
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horizontalFDWT97(7, 0);
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// Index of column handled by this thread. (First half of threads handle
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// even columns and others handle odd columns.)
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const int outColumnIndex = parityIdx<WIN_SIZE_X>();
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// writer of output linear bands - initialize it
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const int firstX = blockIdx.x * WIN_SIZE_X + outColumnIndex;
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VerticalDWTBandWriter<float, CHECK_WRITES> writer;
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writer.init(sizeX, sizeY, firstX, firstY);
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// transform buffer offset of column transformed and saved by this thread
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const int outColumnOffset = buffer.getColumnOffset(outColumnIndex);
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// (Each iteration of this loop assumes that first 7 rows of transform
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// buffer are already loaded with horizontally transformed coefficients.)
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for(int w = 0; w < winSteps; w++) {
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// Load another WIN_SIZE_Y lines of thread's column into the buffer.
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loadWindowIntoColumn(in, loadedColumn);
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// some threads also load boundary columns
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if(threadIdx.x < 7) {
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loadWindowIntoColumn(in, boundaryColumn);
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}
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// horizontally transform all newly loaded lines
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horizontalFDWT97(WIN_SIZE_Y, 7);
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// Using 7 registers, remember current values of last 7 rows of
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// transform buffer. These rows are transformed horizontally only
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// and will be used in next iteration.
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float last7Lines[7];
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for(int i = 0; i < 7; i++) {
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last7Lines[i] = buffer[outColumnOffset + (WIN_SIZE_Y + i) * STRIDE];
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}
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// vertically transform all central columns (do not scale yet)
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buffer.forEachVerticalOdd(outColumnOffset, AddScaledSum(f97Predict1));
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buffer.forEachVerticalEven(outColumnOffset, AddScaledSum(f97Update1));
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buffer.forEachVerticalOdd(outColumnOffset, AddScaledSum(f97Predict2));
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buffer.forEachVerticalEven(outColumnOffset, AddScaledSum(f97Update2));
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// Save all results of current window. Results are in transform buffer
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// at rows from #4 to #(4 + WIN_SIZE_Y). Other rows are invalid now.
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// (They only served as a boundary for vertical FDWT.)
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for(int i = 4; i < (4 + WIN_SIZE_Y); i += 2) {
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const int index = outColumnOffset + i * STRIDE;
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// Write low coefficients from column into low band ...
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writer.writeLowInto(out, buffer[index] * scale97Div);
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// ... and high coeficients into the high band.
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writer.writeHighInto(out, buffer[index + STRIDE] * scale97Mul);
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}
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// Use last 7 remembered lines as first 7 lines for next iteration.
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// As expected, these lines are already horizontally transformed.
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for(int i = 0; i < 7; i++) {
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buffer[outColumnOffset + i * STRIDE] = last7Lines[i];
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}
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// Wait for all writing threads before proceeding to loading new
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// pixels in next iteration. (Not to overwrite those which
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// are not written yet.)
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__syncthreads();
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}
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}
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public:
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/// Runs one of specialized variants of 9/7 FDWT according to distance of
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/// processed pixels to image boudnary. Some variants do not check for
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/// boudnary and thus are slightly faster.
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/// @param in input image
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/// @param out output buffer
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/// @param sx width of the input image
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/// @param sy height of the input image
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/// @param steps number of steps of sliding window
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__device__ static void run(const float * const input, float * const output,
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const int sx, const int sy, const int steps) {
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// object with transform buffer in shared memory
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__shared__ FDWT97<WIN_SIZE_X, WIN_SIZE_Y> fdwt97;
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// Compute limits of this threadblock's block of pixels and use them to
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// determine, whether this threadblock will have to deal with boundary.
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// (3 in next expressions is for radius of impulse response of 9/7 FDWT.)
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const int maxX = (blockIdx.x + 1) * WIN_SIZE_X + 3;
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const int maxY = (blockIdx.y + 1) * WIN_SIZE_Y * steps + 3;
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const bool atRightBoudary = maxX >= sx;
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const bool atBottomBoudary = maxY >= sy;
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// Select specialized version of code according to distance of this
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// threadblock's pixels from image boundary.
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if(atBottomBoudary) {
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// near bottom boundary => check both writing and reading
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// printf("\n atBottomBoudary \n ");
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fdwt97.transform<true, true>(input, output, sx, sy, steps);
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} else if(atRightBoudary) {
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// near right boundary only => check writing only
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fdwt97.transform<false, true>(input, output, sx, sy, steps);
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} else {
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// no nearby boundary => check nothing
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fdwt97.transform<false, false>(input, output, sx, sy, steps);
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}
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}
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}; // end of class FDWT97
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/// Main GPU 9/7 FDWT entry point.
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/// @param input input image
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/// @parma output output buffer
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/// @param sx width of the input image
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/// @param sy height of the input image
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/// @param steps number of steps of sliding window
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template <int WIN_SX, int WIN_SY>
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__launch_bounds__(WIN_SX, CTMIN(SHM_SIZE/sizeof(FDWT97<WIN_SX, WIN_SY>), 8))
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__global__ void fdwt97Kernel(const float * const input, float * const output,
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const int sx, const int sy, const int steps) {
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// Excuse me, dear reader of this code - this call have to be here. If you
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// try to simply put contents of following method right here, CUDA compiler
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// (version 3.2) will spit tons of nonsense messy errors ...
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// Hope they will not break it even more in future releases.
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FDWT97<WIN_SX, WIN_SY>::run(input, output, sx, sy, steps);
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}
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/// Only computes optimal number of sliding window steps,
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/// number of threadblocks and then lanches the 9/7 FDWT kernel.
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/// @tparam WIN_SX width of sliding window
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/// @tparam WIN_SY height of sliding window
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/// @param in input image
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/// @param out output buffer
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/// @param sx width of the input image
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/// @param sy height of the input image
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template <int WIN_SX, int WIN_SY>
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void launchFDWT97Kernel (float * in, float * out, int sx, int sy) {
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// compute optimal number of steps of each sliding window
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const int steps = divRndUp(sy, 15 * WIN_SY);
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// prepare grid size
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dim3 gSize(divRndUp(sx, WIN_SX), divRndUp(sy, WIN_SY * steps));
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printf("\n globalx=%d, globaly=%d, blocksize=%d\n", gSize.x, gSize.y, WIN_SX);
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// run kernel, possibly measure time and finally check the call
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PERF_BEGIN
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fdwt97Kernel<WIN_SX, WIN_SY><<<gSize, WIN_SX>>>(in, out, sx, sy, steps);
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PERF_END(" FDWT97", sx, sy)
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CudaDWTTester::checkLastKernelCall("FDWT 9/7 kernel");
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}
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2022-05-25 08:43:47 +08:00
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2022-05-22 03:55:49 +08:00
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/// Forward 9/7 2D DWT. See common rules (dwt.h) for more details.
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/// @param in Input DWT coefficients. Should be normalized (in range
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/// [-0.5, 0.5]). Will not be preserved (will be overwritten).
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/// @param out output buffer on GPU - format specified in common rules
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/// @param sizeX width of input image (in pixels)
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/// @param sizeY height of input image (in pixels)
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/// @param levels number of recursive DWT levels
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void fdwt97(float * in, float * out, int sizeX, int sizeY, int levels) {
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// select right width of kernel for the size of the image
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if(sizeX >= 960) {
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launchFDWT97Kernel<192, 8>(in, out, sizeX, sizeY);
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} else if (sizeX >= 480) {
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launchFDWT97Kernel<128, 6>(in, out, sizeX, sizeY);
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} else {
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launchFDWT97Kernel<64, 6>(in, out, sizeX, sizeY);
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}
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2022-05-22 03:55:49 +08:00
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// if this was not the last level, continue recursively with other levels
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if(levels > 1) {
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// copy output's LL band back into input buffer
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const int llSizeX = divRndUp(sizeX, 2);
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const int llSizeY = divRndUp(sizeY, 2);
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memCopy(in, out, llSizeX, llSizeY);
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2022-05-25 08:43:47 +08:00
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2022-05-22 03:55:49 +08:00
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// run remaining levels of FDWT
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fdwt97(in, out, llSizeX, llSizeY, levels - 1);
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}
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}
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2022-05-25 08:43:47 +08:00
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2022-05-22 03:55:49 +08:00
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} // end of namespace dwt_cuda
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