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Merge pull request #6 from jchen706/master 

add dwt2d example and fixes and workflow
This commit is contained in:
Ruobing Han 2022-05-24 23:44:43 +00:00 committed by GitHub
parent 52431a983d 82fe95734f
commit d834f31626
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GPG Key ID: 4AEE18F83AFDEB23
25 changed files with 4062 additions and 2 deletions
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38
.github/workflows/build.yml vendored
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@ -155,3 +155,41 @@ jobs:
llc --relocation-model=pic --filetype=obj host.bc
g++ -o lavaMD -fPIC -no-pie -I${{ github.workspace }}/runtime/threadPool/include -L${{ github.workspace }}/build/runtime -L${{ github.workspace }}/build/runtime/threadPool main.c host.o kernel.o util/timer/timer.c util/num/num.c -lpthread -lc -lx86Runtime -lthreadPool -pthread
./lavaMD -boxes1d 10
- name: Execute the dwt2d example
run: |
cd ${{ github.workspace }}/SC_evaluate/rodinia-cox/dwt2d
clang++ -I. -I/include -fno-strict-aliasing dwt_cuda/fdwt53.cu dwt_cuda/fdwt97.cu dwt_cuda/common.cu dwt_cuda/rdwt97.cu dwt_cuda/rdwt53.cu components.cu dwt.cu main.cu -c --cuda-path=${{ github.workspace }}/cuda-10.1 --cuda-gpu-arch=sm_61 -L${{ github.workspace }}/cuda-10.1/lib64 -lcudart_static -ldl -lrt -pthread -save-temps -v || true
export LD_LIBRARY_PATH=${{ github.workspace }}/build/runtime:${{ github.workspace }}/build/runtime/threadPool:$LD_LIBRARY_PATH
export PATH=${{ github.workspace }}/build/compilation:$PATH
kernelTranslator common-cuda-nvptx64-nvidia-cuda-sm_50.bc common.bc
kernelTranslator components-cuda-nvptx64-nvidia-cuda-sm_50.bc components.bc
kernelTranslator fdwt53-cuda-nvptx64-nvidia-cuda-sm_50.bc fdwt53.bc
kernelTranslator dwt-cuda-nvptx64-nvidia-cuda-sm_50.bc dwt.bc
kernelTranslator fdwt97-cuda-nvptx64-nvidia-cuda-sm_50.bc fdwt97.bc
kernelTranslator rdwt97-cuda-nvptx64-nvidia-cuda-sm_50.bc rdwt97.bc
kernelTranslator rdwt53-cuda-nvptx64-nvidia-cuda-sm_50.bc rdwt53.bc
hostTranslator main-host-x86_64-unknown-linux-gnu.bc host.bc
hostTranslator common-host-x86_64-unknown-linux-gnu.bc common_host.bc
hostTranslator components-host-x86_64-unknown-linux-gnu.bc components_host.bc
hostTranslator dwt-host-x86_64-unknown-linux-gnu.bc dwt_host.bc
hostTranslator fdwt53-host-x86_64-unknown-linux-gnu.bc fdwt53_host.bc
hostTranslator fdwt97-host-x86_64-unknown-linux-gnu.bc fdwt97_host.bc
hostTranslator rdwt53-host-x86_64-unknown-linux-gnu.bc rdwt53_host.bc
hostTranslator rdwt97-host-x86_64-unknown-linux-gnu.bc rdwt97_host.bc
llc --relocation-model=pic --filetype=obj common.bc
llc --relocation-model=pic --filetype=obj components.bc
llc --relocation-model=pic --filetype=obj fdwt53.bc
llc --relocation-model=pic --filetype=obj dwt.bc
llc --relocation-model=pic --filetype=obj host.bc
llc --relocation-model=pic --filetype=obj common_host.bc
llc --relocation-model=pic --filetype=obj components_host.bc
llc --relocation-model=pic --filetype=obj fdwt53_host.bc
llc --relocation-model=pic --filetype=obj dwt_host.bc
llc --relocation-model=pic --filetype=obj fdwt97_host.bc
llc --relocation-model=pic --filetype=obj rdwt97_host.bc
llc --relocation-model=pic --filetype=obj rdwt53_host.bc
llc --relocation-model=pic --filetype=obj fdwt97.bc
llc --relocation-model=pic --filetype=obj rdwt97.bc
llc --relocation-model=pic --filetype=obj rdwt53.bc
g++ -o dwt2d -fPIC -no-pie -I${{ github.workspace }}/runtime/threadPool/include -L${{ github.workspace }}/build/runtime -L${{ github.workspace }}/build/runtime/threadPool common.o components.o dwt.o fdwt53.o fdwt97.o rdwt97.o rdwt53.o host.o common_host.o components_host.o dwt_host.o fdwt53_host.o fdwt97_host.o rdwt97_host.o rdwt53_host.o -lpthread -lc -lx86Runtime -lthreadPool -pthread
./dwt2d 192.bmp -d 192x192 -f -5 -l 3

6
compilation/KernelTranslation/lib/init.cpp
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@ -395,5 +395,9 @@ void init_block(llvm::Module *M, std::ofstream &fout) {
// replace asm Inline
replace_asm_call(M);
// replace dynamic shared memory
replace_dynamic_shared_memory(M);
auto dynamic_shared_memory_addr =
M->getGlobalVariable("dynamic_shared_memory");
if (dynamic_shared_memory_addr) {
replace_dynamic_shared_memory(M);
}
}

6
compilation/KernelTranslation/lib/insert_warp_loop.cpp
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@ -270,11 +270,17 @@ void AddContextSaveRestore(llvm::Instruction *instruction,
AddContextSave(instruction, alloca, intra_warp_loop);
std::vector<Instruction *> uses;
Function *f2 = instruction->getParent()->getParent();
for (Instruction::use_iterator ui = instruction->use_begin(),
ue = instruction->use_end();
ui != ue; ++ui) {
llvm::Instruction *user = cast<Instruction>(ui->getUser());
Function *f1 = user->getParent()->getParent();
if(f2->getName() != f1->getName()) {
continue;
}
if (user == NULL)
continue;
if (user == theStore)

18
compilation/KernelTranslation/lib/memory_hierarchy.cpp
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@ -86,6 +86,24 @@ void mem_share2global(llvm::Module *M) {
corresponding_global_memory.insert(
std::pair<GlobalVariable *, GlobalVariable *>(share_memory,
global_memory));
} else if (element_type->isStructTy()) {
auto undef = llvm::UndefValue::get(element_type);
llvm::GlobalVariable *global_memory = new llvm::GlobalVariable(
*M, element_type, false, llvm::GlobalValue::ExternalLinkage, undef,
new_name, NULL, llvm::GlobalValue::GeneralDynamicTLSModel, 0,
false);
global_memory->setDSOLocal(true);
Comdat * comdat = M->getOrInsertComdat(StringRef(share_memory->getName()));
comdat->setSelectionKind(Comdat::SelectionKind::Any);
global_memory->setComdat(comdat);
global_memory->setLinkage(llvm::GlobalValue::LinkOnceODRLinkage);
global_memory->setInitializer(undef);
global_memory->setAlignment(share_memory->getAlignment());
corresponding_global_memory.insert(
std::pair<GlobalVariable *, GlobalVariable *>(share_memory,
global_memory));
} else {
assert(0 && "The required Share Memory Type is not supported\n");
}

62
examples/dwt2d/common.h Executable file
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@ -0,0 +1,62 @@
/*
* Copyright (c) 2009, Jiri Matela
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef _COMMON_H
#define _COMMON_H
//24-bit multiplication is faster on G80,
//but we must be sure to multiply integers
//only within [-8M, 8M - 1] range
#define IMUL(a, b) __mul24(a, b)
////cuda timing macros
//#define CTIMERINIT cudaEvent_t cstart, cstop; \
// cudaEventCreate(&cstart); \
// cudaEventCreate(&cstop); \
// float elapsedTime
//#define CTIMERSTART(cstart) cudaEventRecord(cstart,0)
//#define CTIMERSTOP(cstop) cudaEventRecord(cstop,0); \
// cudaEventSynchronize(cstop); \
// cudaEventElapsedTime(&elapsedTime, cstart, cstop)
//divide and round up macro
#define DIVANDRND(a, b) ((((a) % (b)) != 0) ? ((a) / (b) + 1) : ((a) / (b)))
# define cudaCheckError( msg ) { \
cudaError_t err = cudaGetLastError(); \
if( cudaSuccess != err) { \
fprintf(stderr, "%s: %i: %s: %s.\n", \
__FILE__, __LINE__, msg, cudaGetErrorString( err) ); \
exit(-1); \
} }
# define cudaCheckAsyncError( msg ) { \
cudaThreadSynchronize(); \
cudaCheckError( msg ); \
}
#endif

193
examples/dwt2d/components.cu Executable file
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@ -0,0 +1,193 @@
/*
* Copyright (c) 2009, Jiri Matela
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*/
#include <unistd.h>
#include <error.h>
#include <stdio.h>
#include <stdlib.h>
#include <errno.h>
#include <assert.h>
#include "components.h"
#include "common.h"
#define THREADS 256
/* Store 3 RGB float components */
__device__ void storeComponents(float *d_r, float *d_g, float *d_b, float r, float g, float b, int pos)
{
d_r[pos] = (r/255.0f) - 0.5f;
d_g[pos] = (g/255.0f) - 0.5f;
d_b[pos] = (b/255.0f) - 0.5f;
}
/* Store 3 RGB intege components */
__device__ void storeComponents(int *d_r, int *d_g, int *d_b, int r, int g, int b, int pos)
{
d_r[pos] = r - 128;
d_g[pos] = g - 128;
d_b[pos] = b - 128;
}
/* Store float component */
__device__ void storeComponent(float *d_c, float c, int pos)
{
d_c[pos] = (c/255.0f) - 0.5f;
}
/* Store integer component */
__device__ void storeComponent(int *d_c, int c, int pos)
{
d_c[pos] = c - 128;
}
/* Copy img src data into three separated component buffers */
template<typename T>
__global__ void c_CopySrcToComponents(T *d_r, T *d_g, T *d_b,
unsigned char * d_src,
int pixels)
{
int x = threadIdx.x;
int gX = blockDim.x*blockIdx.x;
__shared__ unsigned char sData[THREADS*3];
/* Copy data to shared mem by 4bytes
other checks are not necessary, since
d_src buffer is aligned to sharedDataSize */
if ( (x*4) < THREADS*3 ) {
float *s = (float *)d_src;
float *d = (float *)sData;
d[x] = s[((gX*3)>>2) + x];
}
__syncthreads();
T r, g, b;
int offset = x*3;
r = (T)(sData[offset]);
g = (T)(sData[offset+1]);
b = (T)(sData[offset+2]);
int globalOutputPosition = gX + x;
if (globalOutputPosition < pixels) {
storeComponents(d_r, d_g, d_b, r, g, b, globalOutputPosition);
}
}
/* Copy img src data into three separated component buffers */
template<typename T>
__global__ void c_CopySrcToComponent(T *d_c, unsigned char * d_src, int pixels)
{
int x = threadIdx.x;
int gX = blockDim.x*blockIdx.x;
__shared__ unsigned char sData[THREADS];
/* Copy data to shared mem by 4bytes
other checks are not necessary, since
d_src buffer is aligned to sharedDataSize */
if ( (x*4) < THREADS) {
float *s = (float *)d_src;
float *d = (float *)sData;
d[x] = s[(gX>>2) + x];
}
__syncthreads();
T c;
c = (T)(sData[x]);
int globalOutputPosition = gX + x;
if (globalOutputPosition < pixels) {
storeComponent(d_c, c, globalOutputPosition);
}
}
/* Separate compoents of 8bit RGB source image */
template<typename T>
void rgbToComponents(T *d_r, T *d_g, T *d_b, unsigned char * src, int width, int height)
{
unsigned char * d_src;
int pixels = width*height;
int alignedSize = DIVANDRND(width*height, THREADS) * THREADS * 3; //aligned to thread block size -- THREADS
/* Alloc d_src buffer */
cudaMalloc((void **)&d_src, alignedSize);
cudaCheckAsyncError("Cuda malloc")
cudaMemset(d_src, 0, alignedSize);
/* Copy data to device */
cudaMemcpy(d_src, src, pixels*3, cudaMemcpyHostToDevice);
cudaCheckError("Copy data to device")
/* Kernel */
dim3 threads(THREADS);
dim3 grid(alignedSize/(THREADS*3));
assert(alignedSize%(THREADS*3) == 0);
c_CopySrcToComponents<<<grid, threads>>>(d_r, d_g, d_b, d_src, pixels);
cudaCheckAsyncError("CopySrcToComponents kernel")
/* Free Memory */
cudaFree(d_src);
cudaCheckAsyncError("Free memory")
}
template void rgbToComponents<float>(float *d_r, float *d_g, float *d_b, unsigned char * src, int width, int height);
template void rgbToComponents<int>(int *d_r, int *d_g, int *d_b, unsigned char * src, int width, int height);
/* Copy a 8bit source image data into a color compoment of type T */
template<typename T>
void bwToComponent(T *d_c, unsigned char * src, int width, int height)
{
unsigned char * d_src;
int pixels = width*height;
int alignedSize = DIVANDRND(pixels, THREADS) * THREADS; //aligned to thread block size -- THREADS
/* Alloc d_src buffer */
cudaMalloc((void **)&d_src, alignedSize);
cudaCheckAsyncError("Cuda malloc")
cudaMemset(d_src, 0, alignedSize);
/* Copy data to device */
cudaMemcpy(d_src, src, pixels, cudaMemcpyHostToDevice);
cudaCheckError("Copy data to device")
/* Kernel */
dim3 threads(THREADS);
dim3 grid(alignedSize/(THREADS));
assert(alignedSize%(THREADS) == 0);
c_CopySrcToComponent<<<grid, threads>>>(d_c, d_src, pixels);
cudaCheckAsyncError("CopySrcToComponent kernel")
/* Free Memory */
cudaFree(d_src);
cudaCheckAsyncError("Free memory")
}
template void bwToComponent<float>(float *d_c, unsigned char *src, int width, int height);
template void bwToComponent<int>(int *d_c, unsigned char *src, int width, int height);

38
examples/dwt2d/components.h Executable file
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@ -0,0 +1,38 @@
/*
* Copyright (c) 2009, Jiri Matela
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef _COMPONENTS_H
#define _COMPONENTS_H
/* Separate compoents of source 8bit RGB image */
template<typename T>
void rgbToComponents(T *d_r, T *d_g, T *d_b, unsigned char * src, int width, int height);
/* Copy a 8bit source image data into a color compoment of type T */
template<typename T>
void bwToComponent(T *d_c, unsigned char * src, int width, int height);
#endif

385
examples/dwt2d/dwt.cu Executable file
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@ -0,0 +1,385 @@
/*
* Copyright (c) 2009, Jiri Matela
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*/
#include <stdio.h>
#include <fcntl.h>
#include <assert.h>
#include <errno.h>
#include <sys/time.h>
#include <unistd.h>
#include <error.h>
#include "dwt_cuda/dwt.h"
#include "dwt_cuda/common.h"
#include "dwt.h"
#include "common.h"
#include <iostream>
#include <fstream>
inline void fdwt(float *in, float *out, int width, int height, int levels)
{
printf(" Running fdwt97 Float \n");
dwt_cuda::fdwt97(in, out, width, height, levels);
}
/*
inline void fdwt(float *in, float *out, int width, int height, int levels, float *diffOut)
{
dwt_cuda::fdwt97(in, out, width, height, levels, diffOut);
}
*/
inline void fdwt(int *in, int *out, int width, int height, int levels)
{
printf(" Running fdwt53 Int \n");
dwt_cuda::fdwt53(in, out, width, height, levels);
}
/*
inline void fdwt(int *in, int *out, int width, int height, int levels, int *diffOut)
{
dwt_cuda::fdwt53(in, out, width, height, levels, diffOut);
}
*/
inline void rdwt(float *in, float *out, int width, int height, int levels)
{
printf(" Running rdwt97 Float \n");
dwt_cuda::rdwt97(in, out, width, height, levels);
}
inline void rdwt(int *in, int *out, int width, int height, int levels)
{
printf(" Running rdwt53 Int \n");
dwt_cuda::rdwt53(in, out, width, height, levels);
}
template<typename T>
int nStage2dDWT(T * in, T * out, T * backup, int pixWidth, int pixHeight, int stages, bool forward)
{
printf("\n*** %d stages of 2D forward DWT:\n", stages);
/* create backup of input, because each test iteration overwrites it */
const int size = pixHeight * pixWidth * sizeof(T);
cudaMemcpy(backup, in, size, cudaMemcpyDeviceToDevice);
cudaCheckError("Memcopy device to device");
/* Measure time of individual levels. */
if(forward)
fdwt(in, out, pixWidth, pixHeight, stages);
else
rdwt(in, out, pixWidth, pixHeight, stages);
// Measure overall time of DWT.
/* #ifdef GPU_DWT_TESTING_1
dwt_cuda::CudaDWTTester tester;
for(int i = tester.getNumIterations(); i--; ) {
// Recover input and measure one overall DWT run.
cudaMemcpy(in, backup, size, cudaMemcpyDeviceToDevice);
cudaCheckError("Memcopy device to device");
tester.beginTestIteration();
if(forward)
fdwt(in, out, pixWidth, pixHeight, stages);
else
rdwt(in, out, pixWidth, pixHeight, stages);
tester.endTestIteration();
}
tester.showPerformance(" Overall DWT", pixWidth, pixHeight);
#endif // GPU_DWT_TESTING
cudaCheckAsyncError("DWT Kernel calls");
*/ return 0;
}
template int nStage2dDWT<float>(float*, float*, float*, int, int, int, bool);
template int nStage2dDWT<int>(int*, int*, int*, int, int, int, bool);
/*
template<typename T>
int nStage2dDWT(T * in, T * out, T * backup, int pixWidth, int pixHeight, int stages, bool forward, T * diffOut)
{
printf("*** %d stages of 2D forward DWT:\n", stages);
// create backup of input, because each test iteration overwrites it
const int size = pixHeight * pixWidth * sizeof(T);
cudaMemcpy(backup, in, size, cudaMemcpyDeviceToDevice);
cudaCheckError("Memcopy device to device");
// Measure time of individual levels.
if(forward)
fdwt(in, out, pixWidth, pixHeight, stages, diffOut);
else
rdwt(in, out, pixWidth, pixHeight, stages);
// Measure overall time of DWT.
#ifdef GPU_DWT_TESTING_1
dwt_cuda::CudaDWTTester tester;
for(int i = tester.getNumIterations(); i--; ) {
// Recover input and measure one overall DWT run.
cudaMemcpy(in, backup, size, cudaMemcpyDeviceToDevice);
cudaCheckError("Memcopy device to device");
tester.beginTestIteration();
if(forward)
fdwt(in, out, pixWidth, pixHeight, stages, diffOut);
else
rdwt(in, out, pixWidth, pixHeight, stages);
tester.endTestIteration();
}
tester.showPerformance(" Overall DWT", pixWidth, pixHeight);
#endif // GPU_DWT_TESTING
cudaCheckAsyncError("DWT Kernel calls");
return 0;
}
template int nStage2dDWT<float>(float*, float*, float*, int, int, int, bool, float*);
template int nStage2dDWT<int>(int*, int*, int*, int, int, int, bool, int*);
*/
void samplesToChar(unsigned char * dst, float * src, int samplesNum, const char * filename)
{
int i;
std::ofstream outputFile;
char outfile[strlen(filename)+strlen(".txt")];
strcpy(outfile, filename);
strcpy(outfile+strlen(filename), ".txt");
outputFile.open(outfile);
for(i = 0; i < samplesNum; i++) {
float r = (src[i]+0.5f) * 255;
if (r > 255) r = 255;
if (r < 0) r = 0;
dst[i] = (unsigned char)r;
outputFile << "index: " << i << " val: "<< r <<" \n";
}
outputFile.close();
}
void samplesToChar(unsigned char * dst, int * src, int samplesNum, const char * filename)
{
int i;
std::ofstream outputFile;
char outfile[strlen(filename)+strlen(".txt")];
strcpy(outfile, filename);
strcpy(outfile+strlen(filename), ".txt");
outputFile.open(outfile);
for(i = 0; i < samplesNum; i++) {
int r = src[i]+128;
if (r > 255) r = 255;
if (r < 0) r = 0;
dst[i] = (unsigned char)r;
// added this line to output check
outputFile << "index: " << i << " val: "<< r <<" \n";
}
outputFile.close();
}
///* Write output linear orderd*/
template<typename T>
int writeLinear(T *component_cuda, int pixWidth, int pixHeight,
const char * filename, const char * suffix)
{
unsigned char * result;
T *gpu_output;
int i;
int size;
int samplesNum = pixWidth*pixHeight;
size = samplesNum*sizeof(T);
cudaMallocHost((void **)&gpu_output, size);
cudaCheckError("Malloc host");
memset(gpu_output, 0, size);
result = (unsigned char *)malloc(samplesNum);
cudaMemcpy(gpu_output, component_cuda, size, cudaMemcpyDeviceToHost);
cudaCheckError("Memcopy device to host");
/* T to char */
samplesToChar(result, gpu_output, samplesNum, filename);
/* Write component */
char outfile[strlen(filename)+strlen(suffix)];
strcpy(outfile, filename);
strcpy(outfile+strlen(filename), suffix);
i = open(outfile, O_CREAT|O_WRONLY, 0644);
if (i == -1) {
error(0,errno,"cannot access %s", outfile);
return -1;
}
printf("\nWriting to %s (%d x %d)\n", outfile, pixWidth, pixHeight);
ssize_t x ;
x = write(i, result, samplesNum);
close(i);
/* Clean up */
cudaFreeHost(gpu_output);
cudaCheckError("Cuda free host memory");
free(result);
if(x == 0) return 1;
return 0;
}
template int writeLinear<float>(float *component_cuda, int pixWidth, int pixHeight, const char * filename, const char * suffix);
template int writeLinear<int>(int *component_cuda, int pixWidth, int pixHeight, const char * filename, const char * suffix);
/* Write output visual ordered */
template<typename T>
int writeNStage2DDWT(T *component_cuda, int pixWidth, int pixHeight,
int stages, const char * filename, const char * suffix)
{
struct band {
int dimX;
int dimY;
};
struct dimensions {
struct band LL;
struct band HL;
struct band LH;
struct band HH;
};
unsigned char * result;
T *src, *dst;
int i,s;
int size;
int offset;
int yOffset;
int samplesNum = pixWidth*pixHeight;
struct dimensions * bandDims;
bandDims = (struct dimensions *)malloc(stages * sizeof(struct dimensions));
bandDims[0].LL.dimX = DIVANDRND(pixWidth,2);
bandDims[0].LL.dimY = DIVANDRND(pixHeight,2);
bandDims[0].HL.dimX = pixWidth - bandDims[0].LL.dimX;
bandDims[0].HL.dimY = bandDims[0].LL.dimY;
bandDims[0].LH.dimX = bandDims[0].LL.dimX;
bandDims[0].LH.dimY = pixHeight - bandDims[0].LL.dimY;
bandDims[0].HH.dimX = bandDims[0].HL.dimX;
bandDims[0].HH.dimY = bandDims[0].LH.dimY;
for (i = 1; i < stages; i++) {
bandDims[i].LL.dimX = DIVANDRND(bandDims[i-1].LL.dimX,2);
bandDims[i].LL.dimY = DIVANDRND(bandDims[i-1].LL.dimY,2);
bandDims[i].HL.dimX = bandDims[i-1].LL.dimX - bandDims[i].LL.dimX;
bandDims[i].HL.dimY = bandDims[i].LL.dimY;
bandDims[i].LH.dimX = bandDims[i].LL.dimX;
bandDims[i].LH.dimY = bandDims[i-1].LL.dimY - bandDims[i].LL.dimY;
bandDims[i].HH.dimX = bandDims[i].HL.dimX;
bandDims[i].HH.dimY = bandDims[i].LH.dimY;
}
#if 0
printf("Original image pixWidth x pixHeight: %d x %d\n", pixWidth, pixHeight);
for (i = 0; i < stages; i++) {
printf("Stage %d: LL: pixWidth x pixHeight: %d x %d\n", i, bandDims[i].LL.dimX, bandDims[i].LL.dimY);
printf("Stage %d: HL: pixWidth x pixHeight: %d x %d\n", i, bandDims[i].HL.dimX, bandDims[i].HL.dimY);
printf("Stage %d: LH: pixWidth x pixHeight: %d x %d\n", i, bandDims[i].LH.dimX, bandDims[i].LH.dimY);
printf("Stage %d: HH: pixWidth x pixHeight: %d x %d\n", i, bandDims[i].HH.dimX, bandDims[i].HH.dimY);
}
#endif
size = samplesNum*sizeof(T);
cudaMallocHost((void **)&src, size);
cudaCheckError("Malloc host");
dst = (T*)malloc(size);
memset(src, 0, size);
memset(dst, 0, size);
result = (unsigned char *)malloc(samplesNum);
cudaMemcpy(src, component_cuda, size, cudaMemcpyDeviceToHost);
cudaCheckError("Memcopy device to host");
// LL Band
size = bandDims[stages-1].LL.dimX * sizeof(T);
for (i = 0; i < bandDims[stages-1].LL.dimY; i++) {
memcpy(dst+i*pixWidth, src+i*bandDims[stages-1].LL.dimX, size);
}
for (s = stages - 1; s >= 0; s--) {
// HL Band
size = bandDims[s].HL.dimX * sizeof(T);
offset = bandDims[s].LL.dimX * bandDims[s].LL.dimY;
for (i = 0; i < bandDims[s].HL.dimY; i++) {
memcpy(dst+i*pixWidth+bandDims[s].LL.dimX,
src+offset+i*bandDims[s].HL.dimX,
size);
}
// LH band
size = bandDims[s].LH.dimX * sizeof(T);
offset += bandDims[s].HL.dimX * bandDims[s].HL.dimY;
yOffset = bandDims[s].LL.dimY;
for (i = 0; i < bandDims[s].HL.dimY; i++) {
memcpy(dst+(yOffset+i)*pixWidth,
src+offset+i*bandDims[s].LH.dimX,
size);
}
//HH band
size = bandDims[s].HH.dimX * sizeof(T);
offset += bandDims[s].LH.dimX * bandDims[s].LH.dimY;
yOffset = bandDims[s].HL.dimY;
for (i = 0; i < bandDims[s].HH.dimY; i++) {
memcpy(dst+(yOffset+i)*pixWidth+bandDims[s].LH.dimX,
src+offset+i*bandDims[s].HH.dimX,
size);
}
}
/* Write component */
samplesToChar(result, dst, samplesNum, filename);
char outfile[strlen(filename)+strlen(suffix)];
strcpy(outfile, filename);
strcpy(outfile+strlen(filename), suffix);
i = open(outfile, O_CREAT|O_WRONLY, 0644);
if (i == -1) {
error(0,errno,"cannot access %s", outfile);
return -1;
}
printf("\nWriting to %s (%d x %d)\n", outfile, pixWidth, pixHeight);
ssize_t x;
x = write(i, result, samplesNum);
close(i);
cudaFreeHost(src);
cudaCheckError("Cuda free host memory");
free(dst);
free(result);
free(bandDims);
if (x == 0) return 1;
return 0;
}
template int writeNStage2DDWT<float>(float *component_cuda, int pixWidth, int pixHeight, int stages, const char * filename, const char * suffix);
template int writeNStage2DDWT<int>(int *component_cuda, int pixWidth, int pixHeight, int stages, const char * filename, const char * suffix);

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/*
* Copyright (c) 2009, Jiri Matela
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef _DWT_H
#define _DWT_H
template<typename T>
int nStage2dDWT(T *in, T *out, T * backup, int pixWidth, int pixHeight, int stages, bool forward);
template<typename T>
int writeNStage2DDWT(T *component_cuda, int width, int height,
int stages, const char * filename, const char * suffix);
template<typename T>
int writeLinear(T *component_cuda, int width, int height,
const char * filename, const char * suffix);
#endif

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///
/// @file common.cu
/// @author Martin Jirman (207962@mail.muni.cz)
/// @date 2011-01-20 14:37
///
/// Copyright (c) 2011 Martin Jirman
/// All rights reserved.
///
/// Redistribution and use in source and binary forms, with or without
/// modification, are permitted provided that the following conditions are met:
///
/// * Redistributions of source code must retain the above copyright
/// notice, this list of conditions and the following disclaimer.
/// * Redistributions in binary form must reproduce the above copyright
/// notice, this list of conditions and the following disclaimer in the
/// documentation and/or other materials provided with the distribution.
///
/// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
/// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
/// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
/// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
/// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
/// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
/// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
/// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
/// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
/// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
/// POSSIBILITY OF SUCH DAMAGE.
///
#include "common.h"
namespace dwt_cuda {
bool CudaDWTTester::testRunning = false;
}

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///
/// @file common.h
/// @author Martin Jirman (207962@mail.muni.cz)
/// @brief Common stuff for all CUDA dwt functions.
/// @date 2011-01-20 14:19
///
/// Copyright (c) 2011 Martin Jirman
/// All rights reserved.
///
/// Redistribution and use in source and binary forms, with or without
/// modification, are permitted provided that the following conditions are met:
///
/// * Redistributions of source code must retain the above copyright
/// notice, this list of conditions and the following disclaimer.
/// * Redistributions in binary form must reproduce the above copyright
/// notice, this list of conditions and the following disclaimer in the
/// documentation and/or other materials provided with the distribution.
///
/// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
/// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
/// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
/// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
/// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
/// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
/// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
/// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
/// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
/// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
/// POSSIBILITY OF SUCH DAMAGE.
///
#ifndef DWT_COMMON_H
#define DWT_COMMON_H
#include <cstdio>
#include <algorithm>
#include <vector>
// compile time minimum macro
#define CTMIN(a,b) (((a) < (b)) ? (a) : (b))
// performance testing macros
#if defined(GPU_DWT_TESTING)
#define PERF_BEGIN \
{ \
dwt_cuda::CudaDWTTester PERF_TESTER; \
for(int PERF_N = PERF_TESTER.getNumIterations(); PERF_N--; ) \
{ \
PERF_TESTER.beginTestIteration();
#define PERF_END(PERF_NAME, PERF_W, PERF_H) \
PERF_TESTER.endTestIteration(); \
} \
PERF_TESTER.showPerformance(PERF_NAME, PERF_W, PERF_H); \
}
#else // GPU_DWT_TESTING
#define PERF_BEGIN
#define PERF_END(PERF_NAME, PERF_W, PERF_H)
#endif // GPU_DWT_TESTING
namespace dwt_cuda {
/// Divide and round up.
template <typename T>
__device__ __host__ inline T divRndUp(const T & n, const T & d) {
return (n / d) + ((n % d) ? 1 : 0);
}
// 9/7 forward DWT lifting schema coefficients
const float f97Predict1 = -1.586134342; ///< forward 9/7 predict 1
const float f97Update1 = -0.05298011854; ///< forward 9/7 update 1
const float f97Predict2 = 0.8829110762; ///< forward 9/7 predict 2
const float f97Update2 = 0.4435068522; ///< forward 9/7 update 2
// 9/7 reverse DWT lifting schema coefficients
const float r97update2 = -f97Update2; ///< undo 9/7 update 2
const float r97predict2 = -f97Predict2; ///< undo 9/7 predict 2
const float r97update1 = -f97Update1; ///< undo 9/7 update 1
const float r97Predict1 = -f97Predict1; ///< undo 9/7 predict 1
// FDWT 9/7 scaling coefficients
const float scale97Mul = 1.23017410491400f;
const float scale97Div = 1.0 / scale97Mul;
// 5/3 forward DWT lifting schema coefficients
const float forward53Predict = -0.5f; /// forward 5/3 predict
const float forward53Update = 0.25f; /// forward 5/3 update
// 5/3 forward DWT lifting schema coefficients
const float reverse53Update = -forward53Update; /// undo 5/3 update
const float reverse53Predict = -forward53Predict; /// undo 5/3 predict
/// Functor which adds scaled sum of neighbors to given central pixel.
struct AddScaledSum {
const float scale; // scale of neighbors
__device__ AddScaledSum(const float scale) : scale(scale) {}
__device__ void operator()(const float p, float & c, const float n) const {
// if(threadIdx.x == 0) {
// printf("scale %f, p %f c %f n %f , result: %f\n", scale, p, c, n, scale * (p + n) );
// }
c += scale * (p + n);
}
};
/// Returns index ranging from 0 to num threads, such that first half
/// of threads get even indices and others get odd indices. Each thread
/// gets different index.
/// Example: (for 8 threads) threadIdx.x: 0 1 2 3 4 5 6 7
/// parityIdx: 0 2 4 6 1 3 5 7
/// @tparam THREADS total count of participating threads
/// @return parity-separated index of thread
template <int THREADS>
__device__ inline int parityIdx() {
return (threadIdx.x * 2) - (THREADS - 1) * (threadIdx.x / (THREADS / 2));
}
/// size of shared memory
#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 200)
const int SHM_SIZE = 48 * 1024;
#else
const int SHM_SIZE = 16 * 1024;
#endif
/// Perrformance and return code tester.
class CudaDWTTester {
private:
static bool testRunning; ///< true if any test is currently running
cudaEvent_t beginEvent; ///< begin CUDA event
cudaEvent_t endEvent; ///< end CUDA event
std::vector<float> times; ///< collected times
const bool disabled; ///< true if this object is disabled
public:
/// Checks CUDA related error.
/// @param status return code to be checked
/// @param message message to be shown if there was an error
/// @return true if there was no error, false otherwise
static bool check(const cudaError_t & status, const char * message) {
#if defined(GPU_DWT_TESTING)
if((!testRunning) && status != cudaSuccess) {
const char * errorString = cudaGetErrorString(status);
fprintf(stderr, "CUDA ERROR: '%s': %s\n", message, errorString);
fflush(stderr);
return false;
}
#endif // GPU_DWT_TESTING
return true;
}
/// Checks last kernel call for errors.
/// @param message description of the kernel call
/// @return true if there was no error, false otherwise
static bool checkLastKernelCall(const char * message) {
#if defined(GPU_DWT_TESTING)
return testRunning ? true : check(cudaThreadSynchronize(), message);
#else // GPU_DWT_TESTING
return true;
#endif // GPU_DWT_TESTING
}
/// Initializes DWT tester for time measurement
CudaDWTTester() : disabled(testRunning) {}
/// Gets rpefered number of iterations
int getNumIterations() {
return disabled ? 1 : 31;
}
/// Starts one test iteration.
void beginTestIteration() {
if(!disabled) {
cudaEventCreate(&beginEvent);
cudaEventCreate(&endEvent);
cudaEventRecord(beginEvent, 0);
testRunning = true;
}
}
/// Ends on etest iteration.
void endTestIteration() {
if(!disabled) {
float time;
testRunning = false;
cudaEventRecord(endEvent, 0);
cudaEventSynchronize(endEvent);
cudaEventElapsedTime(&time, beginEvent, endEvent);
cudaEventDestroy(beginEvent);
cudaEventDestroy(endEvent);
times.push_back(time);
}
}
/// Shows brief info about all iterations.
/// @param name name of processing method
/// @param sizeX width of processed image
/// @param sizeY height of processed image
void showPerformance(const char * name, const int sizeX, const int sizeY) {
if(!disabled) {
// compute mean and median
std::sort(times.begin(), times.end());
double sum = 0;
for(int i = times.size(); i--; ) {
sum += times[i];
}
const double median = (times[times.size() / 2]
+ times[(times.size() - 1) / 2]) * 0.5f;
printf(" %s: %7.3f ms (mean) %7.3f ms (median) %7.3f ms (max) "
"(%d x %d)\n", name, (sum / times.size()), median,
times[times.size() - 1], sizeX, sizeY);
}
}
};
/// Simple cudaMemcpy wrapped in performance tester.
/// @param dest destination bufer
/// @param src source buffer
/// @param sx width of copied image
/// @param sy height of copied image
template <typename T>
inline void memCopy(T * const dest, const T * const src,
const size_t sx, const size_t sy) {
cudaError_t status;
PERF_BEGIN
status = cudaMemcpy(dest, src, sx*sy*sizeof(T), cudaMemcpyDeviceToDevice);
PERF_END(" memcpy", sx, sy)
CudaDWTTester::check(status, "memcpy device > device");
}
} // end of namespace dwt_cuda
#endif // DWT_COMMON_CUDA_H

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///
/// @file dwt.h
/// @author Martin Jirman (207962@mail.muni.cz)
/// @brief Entry points for CUDA implementaion of 9/7 and 5/3 DWT.
/// @date 2011-01-20 11:41
///
///
///
/// Copyright (c) 2011 Martin Jirman
/// All rights reserved.
///
/// Redistribution and use in source and binary forms, with or without
/// modification, are permitted provided that the following conditions are met:
///
/// * Redistributions of source code must retain the above copyright
/// notice, this list of conditions and the following disclaimer.
/// * Redistributions in binary form must reproduce the above copyright
/// notice, this list of conditions and the following disclaimer in the
/// documentation and/or other materials provided with the distribution.
///
/// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
/// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
/// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
/// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
/// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
/// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
/// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
/// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
/// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
/// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
/// POSSIBILITY OF SUCH DAMAGE.
///
///
///
/// Following conditions are common for all four DWT functions:
/// - Both input and output images are stored in GPU memory with no padding
/// of lines or interleaving of pixels.
/// - DWT coefficients are stored as follows: Each band is saved as one
/// consecutive chunk (no padding/stride/interleaving). Deepest level bands
/// (smallest ones) are stored first (at the beginning of the input/output
/// buffers), less deep bands follow. There is no padding between stored
/// bands in the buffer. Order of bands of the same level in the buffer is
/// following: Low-low band (or deeper level subbands) is stored first.
/// Vertical-low/horizontal-high band follows. Vertical-high/horizonal-low
/// band is saved next and finally, the high-high band is saved. Out of all
/// low-low bands, only th edeepest one is saved (right at the beginning of
/// the buffer), others are replaced with deeper level subbands.
/// - Input images of all functions won't be preserved (will be overwritten).
/// - Input and output buffers can't overlap.
/// - Size of output buffer must be greater or equal to size of input buffer.
///
/// There are no common compile time settings (buffer size, etc...) for
/// all DWTs, because each DTW type needs different amount of GPU resources.
/// Instead, each DWT type has its own compile time settings, which can be
/// found in *.cu file, where it is implemented.
///
#ifndef DWT_CUDA_H
#define DWT_CUDA_H
namespace dwt_cuda {
/// Forward 5/3 2D DWT. See common rules (above) for more details.
/// @param in Expected to be normalized into range [-128, 127].
/// Will not be preserved (will be overwritten).
/// @param out output buffer on GPU
/// @param sizeX width of input image (in pixels)
/// @param sizeY height of input image (in pixels)
/// @param levels number of recursive DWT levels
void fdwt53(int * in, int * out, int sizeX, int sizeY, int levels);
/// Reverse 5/3 2D DWT. See common rules (above) for more details.
/// @param in Input DWT coefficients. Format described in common rules.
/// Will not be preserved (will be overwritten).
/// @param out output buffer on GPU - will contain original image
/// in normalized range [-128, 127].
/// @param sizeX width of input image (in pixels)
/// @param sizeY height of input image (in pixels)
/// @param levels number of recursive DWT levels
void rdwt53(int * in, int * out, int sizeX, int sizeY, int levels);
/// Forward 9/7 2D DWT. See common rules (above) for more details.
/// @param in Input DWT coefficients. Should be normalized (in range
/// [-0.5, 0.5]). Will not be preserved (will be overwritten).
/// @param out output buffer on GPU - format specified in common rules
/// @param sizeX width of input image (in pixels)
/// @param sizeY height of input image (in pixels)
/// @param levels number of recursive DWT levels
void fdwt97(float * in, float * out, int sizeX, int sizeY, int levels);
/// Reverse 9/7 2D DWT. See common rules (above) for more details.
/// @param in Input DWT coefficients. Format described in common rules.
/// Will not be preserved (will be overwritten).
/// @param out output buffer on GPU - will contain original image
/// in normalized range [-0.5, 0.5].
/// @param sizeX width of input image (in pixels)
/// @param sizeY height of input image (in pixels)
/// @param levels number of recursive DWT levels
void rdwt97(float * in, float * out, int sizeX, int sizeY, int levels);
} // namespace dwt_cuda
#endif // DWT_CUDA_H

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/// @file fdwt53.cu
/// @brief CUDA implementation of forward 5/3 2D DWT.
/// @author Martin Jirman (207962@mail.muni.cz)
/// @date 2011-02-04 13:23
///
///
/// Copyright (c) 2011 Martin Jirman
/// All rights reserved.
///
/// Redistribution and use in source and binary forms, with or without
/// modification, are permitted provided that the following conditions are met:
///
/// * Redistributions of source code must retain the above copyright
/// notice, this list of conditions and the following disclaimer.
/// * Redistributions in binary form must reproduce the above copyright
/// notice, this list of conditions and the following disclaimer in the
/// documentation and/or other materials provided with the distribution.
///
/// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
/// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
/// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
/// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
/// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
/// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
/// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
/// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
/// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
/// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
/// POSSIBILITY OF SUCH DAMAGE.
///
#include "common.h"
#include "transform_buffer.h"
#include "io.h"
namespace dwt_cuda {
/// Wraps buffer and methods needed for computing one level of 5/3 FDWT
/// using sliding window approach.
/// @tparam WIN_SIZE_X width of sliding window
/// @tparam WIN_SIZE_Y height of sliding window
template <int WIN_SIZE_X, int WIN_SIZE_Y>
class FDWT53 {
private:
/// Info needed for processing of one input column.
/// @tparam CHECKED_LOADER true if column's loader should check boundaries
/// false if there are no near boudnaries to check
template <bool CHECKED_LOADER>
struct FDWT53Column {
/// loader for the column
VerticalDWTPixelLoader<int, CHECKED_LOADER> loader;
/// offset of the column in shared buffer
int offset;
// backup of first 3 loaded pixels (not transformed)
int pixel0, pixel1, pixel2;
/// Sets all fields to anything to prevent 'uninitialized' warnings.
__device__ void clear() {
offset = pixel0 = pixel1 = pixel2 = 0;
loader.clear();
}
};
/// Type of shared memory buffer for 5/3 FDWT transforms.
typedef TransformBuffer<int, WIN_SIZE_X, WIN_SIZE_Y + 3, 2> FDWT53Buffer;
/// Actual shared buffer used for forward 5/3 DWT.
FDWT53Buffer buffer;
/// Difference between indices of two vertical neighbors in buffer.
enum { STRIDE = FDWT53Buffer::VERTICAL_STRIDE };
/// Forward 5/3 DWT predict operation.
struct Forward53Predict {
__device__ void operator() (const int p, int & c, const int n) const {
// c = n;
c -= (p + n) / 2; // F.8, page 126, ITU-T Rec. T.800 final draft the real one
}
};
/// Forward 5/3 DWT update operation.
struct Forward53Update {
__device__ void operator() (const int p, int & c, const int n) const {
c += (p + n + 2) / 4; // F.9, page 126, ITU-T Rec. T.800 final draft
}
};
/// Initializes one column: computes offset of the column in shared memory
/// buffer, initializes loader and finally uses it to load first 3 pixels.
/// @tparam CHECKED true if loader of the column checks boundaries
/// @param column (uninitialized) column info to be initialized
/// @param input input image
/// @param sizeX width of the input image
/// @param sizeY height of the input image
/// @param colIndex x-axis coordinate of the column (relative to the left
/// side of this threadblock's block of input pixels)
/// @param firstY y-axis coordinate of first image row to be transformed
template <bool CHECKED>
__device__ void initColumn(FDWT53Column<CHECKED> & column,
const int * const input,
const int sizeX, const int sizeY,
const int colIndex, const int firstY) {
// get offset of the column with index 'cId'
column.offset = buffer.getColumnOffset(colIndex);
// coordinates of the first pixel to be loaded
const int firstX = blockIdx.x * WIN_SIZE_X + colIndex;
if(blockIdx.y == 0) {
// topmost block - apply mirroring rules when loading first 3 rows
column.loader.init(sizeX, sizeY, firstX, firstY);
// load pixels in mirrored way
column.pixel2 = column.loader.loadFrom(input); // loaded pixel #0
column.pixel1 = column.loader.loadFrom(input); // loaded pixel #1
column.pixel0 = column.loader.loadFrom(input); // loaded pixel #2
// reinitialize loader to start with pixel #1 again
column.loader.init(sizeX, sizeY, firstX, firstY + 1);
} else {
// non-topmost row - regular loading:
column.loader.init(sizeX, sizeY, firstX, firstY - 2);
// load 3 rows into the column
column.pixel0 = column.loader.loadFrom(input);
column.pixel1 = column.loader.loadFrom(input);
column.pixel2 = column.loader.loadFrom(input);
// Now, the next pixel, which will be loaded by loader, is pixel #1.
}
}
/// Loads and vertically transforms given column. Assumes that first 3
/// pixels are already loaded in column fields pixel0 ... pixel2.
/// @tparam CHECKED true if loader of the column checks boundaries
/// @param column column to be loaded and vertically transformed
/// @param input pointer to input image data
template <bool CHECKED>
__device__ void loadAndVerticallyTransform(FDWT53Column<CHECKED> & column,
const int * const input) {
// take 3 loaded pixels and put them into shared memory transform buffer
buffer[column.offset + 0 * STRIDE] = column.pixel0;
buffer[column.offset + 1 * STRIDE] = column.pixel1;
buffer[column.offset + 2 * STRIDE] = column.pixel2;
// load remaining pixels to be able to vertically transform the window
for(int i = 3; i < (3 + WIN_SIZE_Y); i++)
{
buffer[column.offset + i * STRIDE] = column.loader.loadFrom(input);
}
// remember last 3 pixels for use in next iteration
column.pixel0 = buffer[column.offset + (WIN_SIZE_Y + 0) * STRIDE];
column.pixel1 = buffer[column.offset + (WIN_SIZE_Y + 1) * STRIDE];
column.pixel2 = buffer[column.offset + (WIN_SIZE_Y + 2) * STRIDE];
// vertically transform the column in transform buffer
buffer.forEachVerticalOdd(column.offset, Forward53Predict());
buffer.forEachVerticalEven(column.offset, Forward53Update());
}
/// Actual implementation of 5/3 FDWT.
/// @tparam CHECK_LOADS true if input loader must check boundaries
/// @tparam CHECK_WRITES true if output writer must check boundaries
/// @param in input image
/// @param out output buffer
/// @param sizeX width of the input image
/// @param sizeY height of the input image
/// @param winSteps number of sliding window steps
template <bool CHECK_LOADS, bool CHECK_WRITES>
__device__ void transform(const int * const in, int * const out,
const int sizeX, const int sizeY,
const int winSteps) {
// info about one main and one boundary columns processed by this thread
FDWT53Column<CHECK_LOADS> column;
FDWT53Column<CHECK_LOADS> boundaryColumn; // only few threads use this
// Initialize all column info: initialize loaders, compute offset of
// column in shared buffer and initialize loader of column.
const int firstY = blockIdx.y * WIN_SIZE_Y * winSteps;
initColumn(column, in, sizeX, sizeY, threadIdx.x, firstY); //has been checked Mar 9th
// first 3 threads initialize boundary columns, others do not use them
boundaryColumn.clear();
if(threadIdx.x < 3) {
// index of boundary column (relative x-axis coordinate of the column)
const int colId = threadIdx.x + ((threadIdx.x == 0) ? WIN_SIZE_X : -3);
// initialize the column
initColumn(boundaryColumn, in, sizeX, sizeY, colId, firstY);
}
// index of column which will be written into output by this thread
const int outColumnIndex = parityIdx<WIN_SIZE_X>();
// offset of column which will be written by this thread into output
const int outColumnOffset = buffer.getColumnOffset(outColumnIndex);
// initialize output writer for this thread
const int outputFirstX = blockIdx.x * WIN_SIZE_X + outColumnIndex;
VerticalDWTBandWriter<int, CHECK_WRITES> writer;
writer.init(sizeX, sizeY, outputFirstX, firstY);
__syncthreads();
// Sliding window iterations:
// Each iteration assumes that first 3 pixels of each column are loaded.
for(int w = 0; w < winSteps; w++) {
// For each column (including boundary columns): load and vertically
// transform another WIN_SIZE_Y lines.
loadAndVerticallyTransform(column, in);
if(threadIdx.x < 3) {
loadAndVerticallyTransform(boundaryColumn, in);
}
// wait for all columns to be vertically transformed and transform all
// output rows horizontally
__syncthreads();
buffer.forEachHorizontalOdd(2, WIN_SIZE_Y, Forward53Predict());
__syncthreads();
buffer.forEachHorizontalEven(2, WIN_SIZE_Y, Forward53Update());
// wait for all output rows to be transformed horizontally and write
// them into output buffer
__syncthreads();
for(int r = 2; r < (2 + WIN_SIZE_Y); r += 2) {
// Write low coefficients from output column into low band ...
writer.writeLowInto(out, buffer[outColumnOffset + r * STRIDE]);
// ... and high coeficients into the high band.
writer.writeHighInto(out, buffer[outColumnOffset + (r+1) * STRIDE]);
}
// before proceeding to next iteration, wait for all output columns
// to be written into the output
__syncthreads();
}
}
public:
/// Determines, whether this block's pixels touch boundary and selects
/// right version of algorithm according to it - for many threadblocks, it
/// selects version which does not deal with boundary mirroring and thus is
/// slightly faster.
/// @param in input image
/// @param out output buffer
/// @param sx width of the input image
/// @param sy height of the input image
/// @param steps number of sliding window steps
__device__ static void run(const int * const in, int * const out,
const int sx, const int sy, const int steps) {
// if(blockIdx.x==0 && blockIdx.y ==11 && threadIdx.x >=0&&threadIdx.x <64){
// object with transform buffer in shared memory
__shared__ FDWT53<WIN_SIZE_X, WIN_SIZE_Y> fdwt53;
// Compute limits of this threadblock's block of pixels and use them to
// determine, whether this threadblock will have to deal with boundary.
// (1 in next expressions is for radius of impulse response of 9/7 FDWT.)
const int maxX = (blockIdx.x + 1) * WIN_SIZE_X + 1;
const int maxY = (blockIdx.y + 1) * WIN_SIZE_Y * steps + 1;
const bool atRightBoudary = maxX >= sx;
const bool atBottomBoudary = maxY >= sy;
// Select specialized version of code according to distance of this
// threadblock's pixels from image boundary.
// if(threadIdx.x == 0) {
// printf("fdwt53 run");
// }
if(atBottomBoudary)
{
// near bottom boundary => check both writing and reading
fdwt53.transform<true, true>(in, out, sx, sy, steps);
} else if(atRightBoudary)
{
// near right boundary only => check writing only
fdwt53.transform<false, true>(in, out, sx, sy, steps);
} else
{
// no nearby boundary => check nothing
fdwt53.transform<false, false>(in, out, sx, sy, steps);
}
}
// }
}; // end of class FDWT53
/// Main GPU 5/3 FDWT entry point.
/// @tparam WIN_SX width of sliding window to be used
/// @tparam WIN_SY height of sliding window to be used
/// @param input input image
/// @param output output buffer
/// @param sizeX width of the input image
/// @param sizeY height of the input image
/// @param winSteps number of sliding window steps
template <int WIN_SX, int WIN_SY>
__launch_bounds__(WIN_SX, CTMIN(SHM_SIZE/sizeof(FDWT53<WIN_SX, WIN_SY>), 8))
__global__ void fdwt53Kernel(const int * const input, int * const output,
const int sizeX, const int sizeY,
const int winSteps) {
FDWT53<WIN_SX, WIN_SY>::run(input, output, sizeX, sizeY, winSteps);
}
/// Only computes optimal number of sliding window steps,
/// number of threadblocks and then lanches the 5/3 FDWT kernel.
/// @tparam WIN_SX width of sliding window
/// @tparam WIN_SY height of sliding window
/// @param in input image
/// @param out output buffer
/// @param sx width of the input image
/// @param sy height of the input image
template <int WIN_SX, int WIN_SY>
void launchFDWT53Kernel (int * in, int * out, int sx, int sy) {
// compute optimal number of steps of each sliding window
const int steps = divRndUp(sy, 15 * WIN_SY);
int gx = divRndUp(sx, WIN_SX);
int gy = divRndUp(sy, WIN_SY * steps);
printf("\n sliding steps = %d , gx = %d , gy = %d \n", steps, gx, gy);
// prepare grid size
dim3 gSize(divRndUp(sx, WIN_SX), divRndUp(sy, WIN_SY * steps));
// printf("\n globalx=%d, globaly=%d, blocksize=%d\n", gSize.x, gSize.y, WIN_SX);
// run kernel, possibly measure time and finally check the call
// PERF_BEGIN
fdwt53Kernel<WIN_SX, WIN_SY><<<gSize, WIN_SX>>>(in, out, sx, sy, steps);
// PERF_END(" FDWT53", sx, sy)
// CudaDWTTester::checkLastKernelCall("FDWT 5/3 kernel");
printf("fdwt53Kernel in launchFDWT53Kernel has finished");
}
/// Forward 5/3 2D DWT. See common rules (above) for more details.
/// @param in Expected to be normalized into range [-128, 127].
/// Will not be preserved (will be overwritten).
/// @param out output buffer on GPU
/// @param sizeX width of input image (in pixels)
/// @param sizeY height of input image (in pixels)
/// @param levels number of recursive DWT levels
void fdwt53(int * in, int * out, int sizeX, int sizeY, int levels) {
// select right width of kernel for the size of the image
if(sizeX >= 960) {
launchFDWT53Kernel<192, 8>(in, out, sizeX, sizeY);
} else if (sizeX >= 480) {
launchFDWT53Kernel<128, 8>(in, out, sizeX, sizeY);
} else {
launchFDWT53Kernel<64, 8>(in, out, sizeX, sizeY);
}
// if this was not the last level, continue recursively with other levels
if(levels > 1) {
// copy output's LL band back into input buffer
const int llSizeX = divRndUp(sizeX, 2);
const int llSizeY = divRndUp(sizeY, 2);
// printf("\n llSizeX = %d , llSizeY = %d \n", llSizeX, llSizeY);
memCopy(in, out, llSizeX, llSizeY); //the function memCopy in cuda_dwt/common.h line 238
// run remaining levels of FDWT
fdwt53(in, out, llSizeX, llSizeY, levels - 1);
}
}
} // end of namespace dwt_cuda

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

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///
/// @file: io.h
/// @brief Manages loading and saving lineary stored bands and input images.
/// @author Martin Jirman (207962@mail.muni.cz)
/// @date 2011-01-20 22:38
///
///
/// Copyright (c) 2011 Martin Jirman
/// All rights reserved.
///
/// Redistribution and use in source and binary forms, with or without
/// modification, are permitted provided that the following conditions are met:
///
/// * Redistributions of source code must retain the above copyright
/// notice, this list of conditions and the following disclaimer.
/// * Redistributions in binary form must reproduce the above copyright
/// notice, this list of conditions and the following disclaimer in the
/// documentation and/or other materials provided with the distribution.
///
/// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
/// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
/// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
/// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
/// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
/// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
/// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
/// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
/// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
/// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
/// POSSIBILITY OF SUCH DAMAGE.
///
#ifndef IO_H
#define IO_H
#include "common.h"
namespace dwt_cuda {
/// Base for all IO classes - manages mirroring.
class DWTIO {
protected:
/// Handles mirroring of image at edges in a DWT correct way.
/// @param d a position in the image (will be replaced by mirrored d)
/// @param sizeD size of the image along the dimension of 'd'
__device__ static void mirror(int & d, const int & sizeD) {
// TODO: enable multiple mirroring:
// if(sizeD > 1) {
// if(d < 0) {
// const int underflow = -1 - d;
// const int phase = (underflow / (sizeD - 1)) & 1;
// const int remainder = underflow % (sizeD - 1);
// if(phase == 0) {
// d = remainder + 1;
// } else {
// d = sizeD - 2 - remainder;
// }
// } else if(d >= sizeD) {
// const int overflow = d - sizeD;
// const int phase = (overflow / (sizeD - 1)) & 1;
// const int remainder = overflow % (sizeD - 1);
// if(phase == 0) {
// d = sizeD - 2 - remainder;
// } else {
// d = remainder + 1;
// }
// }
// } else {
// d = 0;
// }
//for test the mirror's use Feb 17
if(d >= sizeD) {
d = 2 * sizeD - 2 - d;
} else if(d < 0) {
d = -d;
}
}
};
/// Base class for pixel loader and writer - manages computing start index,
/// stride and end of image for loading column of pixels.
/// @tparam T type of image pixels
/// @tparam CHECKED true = be prepared to image boundary, false = don't care
template <typename T, bool CHECKED>
class VerticalDWTPixelIO : protected DWTIO {
protected:
int end; ///< index of bottom neightbor of last pixel of column
int stride; ///< increment of pointer to get to next pixel
/// Initializes pixel IO - sets end index and a position of first pixel.
/// @param sizeX width of the image
/// @param sizeY height of the image
/// @param firstX x-coordinate of first pixel to use
/// @param firstY y-coordinate of first pixel to use
/// @return index of pixel at position [x, y] in the image
__device__ int initialize(const int sizeX, const int sizeY,
int firstX, int firstY) {
// initialize all pointers and stride
end = CHECKED ? (sizeY * sizeX + firstX) : 0;
stride = sizeX;
return firstX + sizeX * firstY;
}
};
/// Writes reverse transformed pixels directly into output image.
/// @tparam T type of output pixels
/// @tparam CHECKED true = be prepared to image boundary, false = don't care
template <typename T, bool CHECKED>
class VerticalDWTPixelWriter : VerticalDWTPixelIO<T, CHECKED> {
private:
int next; // index of the next pixel to be loaded
public:
/// Initializes writer - sets output buffer and a position of first pixel.
/// @param sizeX width of the image
/// @param sizeY height of the image
/// @param firstX x-coordinate of first pixel to write into
/// @param firstY y-coordinate of first pixel to write into
__device__ void init(const int sizeX, const int sizeY,
int firstX, int firstY) {
if(firstX < sizeX) {
next = this->initialize(sizeX, sizeY, firstX, firstY);
} else {
this->end = 0;
this->stride = 0;
next = 0;
}
}
/// Writes given value at next position and advances internal pointer while
/// correctly handling mirroring.
/// @param output output image to write pixel into
/// @param value value of the pixel to be written
__device__ void writeInto(T * const output, const T & value) {
if((!CHECKED) || (next != this->end)) {
output[next] = value;
next += this->stride;
}
}
};
/// Loads pixels from input image.
/// @tparam T type of image input pixels
/// @tparam CHECKED true = be prepared to image boundary, false = don't care
template <typename T, bool CHECKED>
class VerticalDWTPixelLoader
: protected VerticalDWTPixelIO<const T, CHECKED> {
private:
int last; ///< index of last loaded pixel
public:
//******************* FOR TEST **********************
__device__ int getlast(){
return last;
}
__device__ int getend(){
return this->end;
}
__device__ int getstride(){
return this->stride;
}
__device__ void setend(int a){
this->end=a;
}
//******************* FOR TEST **********************
/// Initializes loader - sets input size and a position of first pixel.
/// @param sizeX width of the image
/// @param sizeY height of the image
/// @param firstX x-coordinate of first pixel to load
/// @param firstY y-coordinate of first pixel to load
__device__ void init(const int sizeX, const int sizeY,
int firstX, int firstY) {
// correctly mirror x coordinate
this->mirror(firstX, sizeX);
// 'last' always points to already loaded pixel (subtract sizeX = stride)
last = this->initialize(sizeX, sizeY, firstX, firstY) - sizeX;
//last = (FirstX + sizeX * FirstY) - sizeX
}
/// Sets all fields to zeros, for compiler not to complain about
/// uninitialized stuff.
__device__ void clear() {
this->end = 0;
this->stride = 0;
this->last = 0;
}
/// Gets another pixel and advancees internal pointer to following one.
/// @param input input image to load next pixel from
/// @return next pixel from given image
__device__ T loadFrom(const T * const input) {
last += this->stride;
if(CHECKED && (last == this->end)) {
last -= 2 * this->stride;
this->stride = -this->stride; // reverse loader's direction
}
// avoid reading from negative indices if loader is checked
// return (CHECKED && (last < 0)) ? 0 : input[last]; // TODO: use this checked variant later
if(last < 0 ) {
return 0;
}
return input[last];
// return this->end;
// return last;
// return this->stride;
}
};
/// Base for band write and loader. Manages computing strides and pointers
/// to first and last pixels in a linearly-stored-bands correct way.
/// @tparam T type of band coefficients
/// @tparam CHECKED true = be prepared to image boundary, false = don't care
template <typename T, bool CHECKED>
class VerticalDWTBandIO : protected DWTIO {
protected:
/// index of bottom neighbor of last pixel of loaded column
int end;
/// increment of index to get from highpass band to the lowpass one
int strideHighToLow;
/// increment of index to get from the lowpass band to the highpass one
int strideLowToHigh;
/// Initializes IO - sets size of image and a position of first pixel.
/// @param imageSizeX width of the image
/// @param imageSizeY height of the image
/// @param firstX x-coordinate of first pixel to use
/// (Parity determines vertically low or high band.)
/// @param firstY y-coordinate of first pixel to use
/// (Parity determines horizontally low or high band.)
/// @return index of first item specified by firstX and firstY
__device__ int initialize(const int imageSizeX, const int imageSizeY,
int firstX, int firstY) {
// index of first pixel (topmost one) of the column with index firstX
int columnOffset = firstX / 2;
// difference between indices of two vertically neighboring pixels
// in the same band
int verticalStride;
// resolve index of first pixel according to horizontal parity
if(firstX & 1) {
// first pixel in one of right bands
verticalStride = imageSizeX / 2;
columnOffset += divRndUp(imageSizeX, 2) * divRndUp(imageSizeY, 2);
strideLowToHigh = (imageSizeX * imageSizeY) / 2;
} else {
// first pixel in one of left bands
verticalStride = imageSizeX / 2 + (imageSizeX & 1);
strideLowToHigh = divRndUp(imageSizeY, 2) * imageSizeX;
}
// set the other stride
strideHighToLow = verticalStride - strideLowToHigh;
// compute index of coefficient which indicates end of image
if(CHECKED) {
end = columnOffset // right column
+ (imageSizeY / 2) * verticalStride // right row
+ (imageSizeY & 1) * strideLowToHigh; // possibly in high band
} else {
end = 0;
}
//***********for test**************
// end = CHECKED;
//***********for test**************
// finally, return index of the first item
return columnOffset // right column
+ (firstY / 2) * verticalStride // right row
+ (firstY & 1) * strideLowToHigh; // possibly in high band
}
};
/// Directly loads coefficients from four consecutively stored transformed
/// bands.
/// @tparam T type of input band coefficients
/// @tparam CHECKED true = be prepared to image boundary, false = don't care
template <typename T, bool CHECKED>
class VerticalDWTBandLoader : public VerticalDWTBandIO<const T, CHECKED> {
private:
int last; ///< index of last loaded pixel
/// Checks internal index and possibly reverses direction of loader.
/// (Handles mirroring at the bottom of the image.)
/// @param input input image to load next coefficient from
/// @param stride stride to use now (one of two loader's strides)
/// @return loaded coefficient
__device__ T updateAndLoad(const T * const input, const int & stride) {
last += stride;
if(CHECKED && (last == this->end)) {
// undo last two updates of index (to get to previous mirrored item)
last -= (this->strideLowToHigh + this->strideHighToLow);
// swap and reverse strides (to move up in the loaded column now)
const int temp = this->strideLowToHigh;
this->strideLowToHigh = -this->strideHighToLow;
this->strideHighToLow = -temp;
}
if(last < 0 ) {
return 0;
}
// avoid reading from negative indices if loader is checked
// return (CHECKED && (last < 0)) ? 0 : input[last]; // TODO: use this checked variant later
return input[last];
}
public:
/// Initializes loader - sets input size and a position of first pixel.
/// @param imageSizeX width of the image
/// @param imageSizeY height of the image
/// @param firstX x-coordinate of first pixel to load
/// (Parity determines vertically low or high band.)
/// @param firstY y-coordinate of first pixel to load
/// (Parity determines horizontally low or high band.)
__device__ void init(const int imageSizeX, const int imageSizeY,
int firstX, const int firstY) {
this->mirror(firstX, imageSizeX);
last = this->initialize(imageSizeX, imageSizeY, firstX, firstY);
// adjust to point to previous item
last -= (firstY & 1) ? this->strideLowToHigh : this->strideHighToLow;
}
/// Sets all fields to zeros, for compiler not to complain about
/// uninitialized stuff.
__device__ void clear() {
this->end = 0;
this->strideHighToLow = 0;
this->strideLowToHigh = 0;
this->last = 0;
}
/// Gets another coefficient from lowpass band and advances internal index.
/// Call this method first if position of first pixel passed to init
/// was in high band.
/// @param input input image to load next coefficient from
/// @return next coefficient from the lowpass band of the given image
__device__ T loadLowFrom(const T * const input) {
return updateAndLoad(input, this->strideHighToLow);
}
/// Gets another coefficient from the highpass band and advances index.
/// Call this method first if position of first pixel passed to init
/// was in high band.
/// @param input input image to load next coefficient from
/// @return next coefficient from the highbass band of the given image
__device__ T loadHighFrom(const T * const input) {
return updateAndLoad(input, this->strideLowToHigh);
}
};
/// Directly saves coefficients into four transformed bands.
/// @tparam T type of output band coefficients
/// @tparam CHECKED true = be prepared to image boundary, false = don't care
template <typename T, bool CHECKED>
class VerticalDWTBandWriter : public VerticalDWTBandIO<T, CHECKED> {
private:
int next; ///< index of last loaded pixel
/// Checks internal index and possibly stops the writer.
/// (Handles mirroring at edges of the image.)
/// @param output output buffer
/// @param item item to put into the output
/// @param stride increment of the pointer to get to next output index
__device__ int saveAndUpdate(T * const output, const T & item,
const int & stride) {
// if(blockIdx.x == 0 && blockIdx.y == 11 && threadIdx.x == 0){ //test, Mar 20
if((!CHECKED) || (next != this->end)) {
// if(next == 4) {
// printf(" next: %d stride: %d val: %f \n", next, stride, item );
// }
output[next] = item;
next += stride;
}
// }
// if((!CHECKED) || (next != this->end)) { //the real one
// output[next] = item;
// next += stride; //stride has been test
// }
return next;
}
public:
/// Initializes writer - sets output size and a position of first pixel.
/// @param output output image
/// @param imageSizeX width of the image
/// @param imageSizeY height of the image
/// @param firstX x-coordinate of first pixel to write
/// (Parity determines vertically low or high band.)
/// @param firstY y-coordinate of first pixel to write
/// (Parity determines horizontally low or high band.)
__device__ void init(const int imageSizeX, const int imageSizeY,
const int firstX, const int firstY) {
if (firstX < imageSizeX) {
next = this->initialize(imageSizeX, imageSizeY, firstX, firstY);
} else {
clear();
}
}
/// Sets all fields to zeros, for compiler not to complain about
/// uninitialized stuff.
__device__ void clear() {
this->end = 0;
this->strideHighToLow = 0;
this->strideLowToHigh = 0;
this->next = 0;
}
/// Writes another coefficient into the band which was specified using
/// init's firstX and firstY parameters and advances internal pointer.
/// Call this method first if position of first pixel passed to init
/// was in lowpass band.
/// @param output output image
/// @param low lowpass coefficient to save into the lowpass band
__device__ int writeLowInto(T * const output, const T & primary) {
return saveAndUpdate(output, primary, this->strideLowToHigh);
}
/// Writes another coefficient from the other band and advances pointer.
/// Call this method first if position of first pixel passed to init
/// was in highpass band.
/// @param output output image
/// @param high highpass coefficient to save into the highpass band
__device__ int writeHighInto(T * const output, const T & other) {
return saveAndUpdate(output, other, this->strideHighToLow);
}
//*******Add three functions to get private values*******
__device__ int getnext(){
return next;
}
__device__ int getend(){
return this->end;
}
__device__ int getstrideHighToLow(){
return this->strideHighToLow;
}
__device__ int getstrideLowToHigh(){
return this->strideLowToHigh;
}
//*******Add three functions to get private values*******
};
} // namespace dwt_cuda
#endif // IO_H

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///
/// @file rdwt53.cu
/// @brief CUDA implementation of reverse 5/3 2D DWT.
/// @author Martin Jirman (207962@mail.muni.cz)
/// @date 2011-02-04 14:19
///
///
/// Copyright (c) 2011 Martin Jirman
/// All rights reserved.
///
/// Redistribution and use in source and binary forms, with or without
/// modification, are permitted provided that the following conditions are met:
///
/// * Redistributions of source code must retain the above copyright
/// notice, this list of conditions and the following disclaimer.
/// * Redistributions in binary form must reproduce the above copyright
/// notice, this list of conditions and the following disclaimer in the
/// documentation and/or other materials provided with the distribution.
///
/// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
/// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
/// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
/// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
/// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
/// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
/// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
/// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
/// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
/// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
/// POSSIBILITY OF SUCH DAMAGE.
///
#include "common.h"
#include "transform_buffer.h"
#include "io.h"
namespace dwt_cuda {
/// Wraps shared momory buffer and algorithms needed for computing 5/3 RDWT
/// using sliding window and lifting schema.
/// @tparam WIN_SIZE_X width of sliding window
/// @tparam WIN_SIZE_Y height of sliding window
template <int WIN_SIZE_X, int WIN_SIZE_Y>
class RDWT53 {
private:
/// Shared memory buffer used for 5/3 DWT transforms.
typedef TransformBuffer<int, WIN_SIZE_X, WIN_SIZE_Y + 3, 2> RDWT53Buffer;
/// Shared buffer used for reverse 5/3 DWT.
RDWT53Buffer buffer;
/// Difference between indices of two vertically neighboring items in buffer.
enum { STRIDE = RDWT53Buffer::VERTICAL_STRIDE };
/// Info needed for loading of one input column from input image.
/// @tparam CHECKED true if loader should check boundaries
template <bool CHECKED>
struct RDWT53Column {
/// loader of pixels from column in input image
VerticalDWTBandLoader<int, CHECKED> loader;
/// Offset of corresponding column in shared buffer.
int offset;
/// Sets all fields to some values to avoid 'uninitialized' warnings.
__device__ void clear() {
offset = 0;
loader.clear();
}
};
/// 5/3 DWT reverse update operation.
struct Reverse53Update {
__device__ void operator() (const int p, int & c, const int n) const {
c -= (p + n + 2) / 4; // F.3, page 118, ITU-T Rec. T.800 final draft
}
};
/// 5/3 DWT reverse predict operation.
struct Reverse53Predict {
__device__ void operator() (const int p, int & c, const int n) const {
c += (p + n) / 2; // F.4, page 118, ITU-T Rec. T.800 final draft
}
};
/// Horizontal 5/3 RDWT on specified lines of transform buffer.
/// @param lines number of lines to be transformed
/// @param firstLine index of the first line to be transformed
__device__ void horizontalTransform(const int lines, const int firstLine) {
__syncthreads();
buffer.forEachHorizontalEven(firstLine, lines, Reverse53Update());
__syncthreads();
buffer.forEachHorizontalOdd(firstLine, lines, Reverse53Predict());
__syncthreads();
}
/// Using given loader, it loads another WIN_SIZE_Y coefficients
/// into specified column.
/// @tparam CHECKED true if loader should check image boundaries
/// @param input input coefficients to load from
/// @param col info about loaded column
template <bool CHECKED>
inline __device__ void loadWindowIntoColumn(const int * const input,
RDWT53Column<CHECKED> & col) {
for(int i = 3; i < (3 + WIN_SIZE_Y); i += 2) {
buffer[col.offset + i * STRIDE] = col.loader.loadLowFrom(input);
buffer[col.offset + (i + 1) * STRIDE] = col.loader.loadHighFrom(input);
}
}
/// Initializes one column of shared transform buffer with 7 input pixels.
/// Those 7 pixels will not be transformed. Also initializes given loader.
/// @tparam CHECKED true if loader should check image boundaries
/// @param columnX x coordinate of column in shared transform buffer
/// @param input input image
/// @param sizeX width of the input image
/// @param sizeY height of the input image
/// @param loader (uninitialized) info about loaded column
template <bool CHECKED>
__device__ void initColumn(const int columnX, const int * const input,
const int sizeX, const int sizeY,
RDWT53Column<CHECKED> & column,
const int firstY) {
// coordinates of the first coefficient to be loaded
const int firstX = blockIdx.x * WIN_SIZE_X + columnX;
// offset of the column with index 'colIndex' in the transform buffer
column.offset = buffer.getColumnOffset(columnX);
if(blockIdx.y == 0) {
// topmost block - apply mirroring rules when loading first 3 rows
column.loader.init(sizeX, sizeY, firstX, firstY);
// load pixels in mirrored way
buffer[column.offset + 1 * STRIDE] = column.loader.loadLowFrom(input);
buffer[column.offset + 0 * STRIDE] =
buffer[column.offset + 2 * STRIDE] = column.loader.loadHighFrom(input);
} else {
// non-topmost row - regular loading:
column.loader.init(sizeX, sizeY, firstX, firstY - 1);
buffer[column.offset + 0 * STRIDE] = column.loader.loadHighFrom(input);
buffer[column.offset + 1 * STRIDE] = column.loader.loadLowFrom(input);
buffer[column.offset + 2 * STRIDE] = column.loader.loadHighFrom(input);
}
// Now, the next coefficient, which will be loaded by loader, is #2.
}
/// Actual GPU 5/3 RDWT implementation.
/// @tparam CHECKED_LOADS true if boundaries must be checked when reading
/// @tparam CHECKED_WRITES true if boundaries must be checked when writing
/// @param in input image (5/3 transformed coefficients)
/// @param out output buffer (for reverse transformed image)
/// @param sizeX width of the output image
/// @param sizeY height of the output image
/// @param winSteps number of sliding window steps
template<bool CHECKED_LOADS, bool CHECKED_WRITES>
__device__ void transform(const int * const in, int * const out,
const int sizeX, const int sizeY,
const int winSteps) {
// info about one main and one boundary column
RDWT53Column<CHECKED_LOADS> column, boundaryColumn;
// index of first row to be transformed
const int firstY = blockIdx.y * WIN_SIZE_Y * winSteps;
// some threads initialize boundary columns
boundaryColumn.clear();
if(threadIdx.x < 3) {
// First 3 threads also handle boundary columns. Thread #0 gets right
// column #0, thread #1 get right column #1 and thread #2 left column.
const int colId = threadIdx.x + ((threadIdx.x != 2) ? WIN_SIZE_X : -3);
// Thread initializes offset of the boundary column (in shared
// buffer), first 3 pixels of the column and a loader for this column.
initColumn(colId, in, sizeX, sizeY, boundaryColumn, firstY);
}
// All threads initialize central columns.
initColumn(parityIdx<WIN_SIZE_X>(), in, sizeX, sizeY, column, firstY);
// horizontally transform first 3 rows
horizontalTransform(3, 0);
// writer of output pixels - initialize it
const int outX = blockIdx.x * WIN_SIZE_X + threadIdx.x;
VerticalDWTPixelWriter<int, CHECKED_WRITES> writer;
writer.init(sizeX, sizeY, outX, firstY);
// offset of column (in transform buffer) saved by this thread
const int outputColumnOffset = buffer.getColumnOffset(threadIdx.x);
// (Each iteration assumes that first 3 rows of transform buffer are
// already loaded with horizontally transformed pixels.)
for(int w = 0; w < winSteps; w++) {
// Load another WIN_SIZE_Y lines of this thread's column
// into the transform buffer.
loadWindowIntoColumn(in, column);
// possibly load boundary columns
if(threadIdx.x < 3) {
loadWindowIntoColumn(in, boundaryColumn);
}
// horizontally transform all newly loaded lines
horizontalTransform(WIN_SIZE_Y, 3);
// Using 3 registers, remember current values of last 3 rows
// of transform buffer. These rows are transformed horizontally
// only and will be used in next iteration.
int last3Lines[3];
last3Lines[0] = buffer[outputColumnOffset + (WIN_SIZE_Y + 0) * STRIDE];
last3Lines[1] = buffer[outputColumnOffset + (WIN_SIZE_Y + 1) * STRIDE];
last3Lines[2] = buffer[outputColumnOffset + (WIN_SIZE_Y + 2) * STRIDE];
// vertically transform all central columns
buffer.forEachVerticalOdd(outputColumnOffset, Reverse53Update());
buffer.forEachVerticalEven(outputColumnOffset, Reverse53Predict());
// Save all results of current window. Results are in transform buffer
// at rows from #1 to #(1 + WIN_SIZE_Y). Other rows are invalid now.
// (They only served as a boundary for vertical RDWT.)
for(int i = 1; i < (1 + WIN_SIZE_Y); i++) {
writer.writeInto(out, buffer[outputColumnOffset + i * STRIDE]);
}
// Use last 3 remembered lines as first 3 lines for next iteration.
// As expected, these lines are already horizontally transformed.
buffer[outputColumnOffset + 0 * STRIDE] = last3Lines[0];
buffer[outputColumnOffset + 1 * STRIDE] = last3Lines[1];
buffer[outputColumnOffset + 2 * STRIDE] = last3Lines[2];
// Wait for all writing threads before proceeding to loading new
// coeficients in next iteration. (Not to overwrite those which
// are not written yet.)
__syncthreads();
}
}
public:
/// Main GPU 5/3 RDWT entry point.
/// @param in input image (5/3 transformed coefficients)
/// @param out output buffer (for reverse transformed image)
/// @param sizeX width of the output image
/// @param sizeY height of the output image
/// @param winSteps number of sliding window steps
__device__ static void run(const int * const input, int * const output,
const int sx, const int sy, const int steps) {
// prepare instance with buffer in shared memory
__shared__ RDWT53<WIN_SIZE_X, WIN_SIZE_Y> rdwt53;
// Compute limits of this threadblock's block of pixels and use them to
// determine, whether this threadblock will have to deal with boundary.
// (1 in next expressions is for radius of impulse response of 5/3 RDWT.)
const int maxX = (blockIdx.x + 1) * WIN_SIZE_X + 1;
const int maxY = (blockIdx.y + 1) * WIN_SIZE_Y * steps + 1;
const bool atRightBoudary = maxX >= sx;
const bool atBottomBoudary = maxY >= sy;
// Select specialized version of code according to distance of this
// threadblock's pixels from image boundary.
if(atBottomBoudary) {
// near bottom boundary => check both writing and reading
rdwt53.transform<true, true>(input, output, sx, sy, steps);
} else if(atRightBoudary) {
// near right boundary only => check writing only
rdwt53.transform<false, true>(input, output, sx, sy, steps);
} else {
// no nearby boundary => check nothing
rdwt53.transform<false, false>(input, output, sx, sy, steps);
}
}
}; // end of class RDWT53
/// Main GPU 5/3 RDWT entry point.
/// @param in input image (5/3 transformed coefficients)
/// @param out output buffer (for reverse transformed image)
/// @param sizeX width of the output image
/// @param sizeY height of the output image
/// @param winSteps number of sliding window steps
template <int WIN_SX, int WIN_SY>
__launch_bounds__(WIN_SX, CTMIN(SHM_SIZE/sizeof(RDWT53<WIN_SX, WIN_SY>), 8))
__global__ void rdwt53Kernel(const int * const in, int * const out,
const int sx, const int sy, const int steps) {
RDWT53<WIN_SX, WIN_SY>::run(in, out, sx, sy, steps);
}
/// Only computes optimal number of sliding window steps,
/// number of threadblocks and then lanches the 5/3 RDWT kernel.
/// @tparam WIN_SX width of sliding window
/// @tparam WIN_SY height of sliding window
/// @param in input image
/// @param out output buffer
/// @param sx width of the input image
/// @param sy height of the input image
template <int WIN_SX, int WIN_SY>
void launchRDWT53Kernel (int * in, int * out, const int sx, const int sy) {
// compute optimal number of steps of each sliding window
const int steps = divRndUp(sy, 15 * WIN_SY);
// prepare grid size
dim3 gSize(divRndUp(sx, WIN_SX), divRndUp(sy, WIN_SY * steps));
// finally transform this level
PERF_BEGIN
rdwt53Kernel<WIN_SX, WIN_SY><<<gSize, WIN_SX>>>(in, out, sx, sy, steps);
PERF_END(" RDWT53", sx, sy)
CudaDWTTester::checkLastKernelCall("RDWT 5/3 kernel");
}
/// Reverse 5/3 2D DWT. See common rules (above) for more details.
/// @param in Input DWT coefficients. Format described in common rules.
/// Will not be preserved (will be overwritten).
/// @param out output buffer on GPU - will contain original image
/// in normalized range [-128, 127].
/// @param sizeX width of input image (in pixels)
/// @param sizeY height of input image (in pixels)
/// @param levels number of recursive DWT levels
void rdwt53(int * in, int * out, int sizeX, int sizeY, int levels) {
if(levels > 1) {
// let this function recursively reverse transform deeper levels first
const int llSizeX = divRndUp(sizeX, 2);
const int llSizeY = divRndUp(sizeY, 2);
rdwt53(in, out, llSizeX, llSizeY, levels - 1);
// copy reverse transformed LL band from output back into the input
memCopy(in, out, llSizeX, llSizeY);
}
// select right width of kernel for the size of the image
if(sizeX >= 960) {
launchRDWT53Kernel<192, 8>(in, out, sizeX, sizeY);
} else if (sizeX >= 480) {
launchRDWT53Kernel<128, 8>(in, out, sizeX, sizeY);
} else {
launchRDWT53Kernel<64, 8>(in, out, sizeX, sizeY);
}
}
} // end of namespace dwt_cuda

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///
/// @file rdwt97.cu
/// @brief CUDA implementation of reverse 9/7 2D DWT.
/// @author Martin Jirman (207962@mail.muni.cz)
/// @date 2011-02-03 21:59
///
///
/// Copyright (c) 2011 Martin Jirman
/// All rights reserved.
///
/// Redistribution and use in source and binary forms, with or without
/// modification, are permitted provided that the following conditions are met:
///
/// * Redistributions of source code must retain the above copyright
/// notice, this list of conditions and the following disclaimer.
/// * Redistributions in binary form must reproduce the above copyright
/// notice, this list of conditions and the following disclaimer in the
/// documentation and/or other materials provided with the distribution.
///
/// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
/// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
/// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
/// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
/// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
/// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
/// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
/// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
/// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
/// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
/// POSSIBILITY OF SUCH DAMAGE.
///
#include "common.h"
#include "transform_buffer.h"
#include "io.h"
namespace dwt_cuda {
/// Wraps shared memory buffer and methods for computing 9/7 RDWT using
/// lifting schema and sliding window.
/// @tparam WIN_SIZE_X width of the sliding window
/// @tparam WIN_SIZE_Y height of the sliding window
template <int WIN_SIZE_X, int WIN_SIZE_Y>
class RDWT97 {
private:
/// Info related to loading of one input column.
/// @tparam CHECKED true if boundary chould be checked,
/// false if there is no near boudnary
template <bool CHECKED>
struct RDWT97Column {
/// laoder of input pxels for given column.
VerticalDWTBandLoader<float, CHECKED> loader;
/// Offset of loaded column in shared memory buffer.
int offset;
/// Sets all fields to some values to avoid 'uninitialized' warnings.
__device__ void clear() {
loader.clear();
offset = 0;
}
};
/// Shared memory buffer used for 9/7 DWT transforms.
typedef TransformBuffer<float, WIN_SIZE_X, WIN_SIZE_Y + 7, 4> RDWT97Buffer;
/// Shared buffer used for reverse 9/7 DWT.
RDWT97Buffer buffer;
/// Difference between indices of two vertical neighbors in buffer.
enum { STRIDE = RDWT97Buffer::VERTICAL_STRIDE };
/// Horizontal 9/7 RDWT on specified lines of transform buffer.
/// @param lines number of lines to be transformed
/// @param firstLine index of the first line to be transformed
__device__ void horizontalRDWT97(int lines, int firstLine) {
__syncthreads();
buffer.scaleHorizontal(scale97Mul, scale97Div, firstLine, lines);
__syncthreads();
buffer.forEachHorizontalEven(firstLine, lines, AddScaledSum(r97update2));
__syncthreads();
buffer.forEachHorizontalOdd(firstLine, lines, AddScaledSum(r97predict2));
__syncthreads();
buffer.forEachHorizontalEven(firstLine, lines, AddScaledSum(r97update1));
__syncthreads();
buffer.forEachHorizontalOdd(firstLine, lines, AddScaledSum(r97Predict1));
__syncthreads();
}
/// Initializes one column of shared transform buffer with 7 input pixels.
/// Those 7 pixels will not be transformed. Also initializes given loader.
/// @tparam CHECKED true if there are near image boundaries
/// @param colIndex index of column in shared transform buffer
/// @param input input image
/// @param sizeX width of the input image
/// @param sizeY height of the input image
/// @param column (uninitialized) info about loading one column
/// @param firstY index of first image row to be transformed
template <bool CHECKED>
__device__ void initColumn(const int colIndex, const float * const input,
const int sizeX, const int sizeY,
RDWT97Column<CHECKED> & column,
const int firstY) {
// coordinates of the first coefficient to be loaded
const int firstX = blockIdx.x * WIN_SIZE_X + colIndex;
// offset of the column with index 'colIndex' in the transform buffer
column.offset = buffer.getColumnOffset(colIndex);
if(blockIdx.y == 0) {
// topmost block - apply mirroring rules when loading first 7 rows
column.loader.init(sizeX, sizeY, firstX, firstY);
// load pixels in mirrored way
buffer[column.offset + 3 * STRIDE] = column.loader.loadLowFrom(input);
buffer[column.offset + 4 * STRIDE] =
buffer[column.offset + 2 * STRIDE] = column.loader.loadHighFrom(input);
buffer[column.offset + 5 * STRIDE] =
buffer[column.offset + 1 * STRIDE] = column.loader.loadLowFrom(input);
buffer[column.offset + 6 * STRIDE] =
buffer[column.offset + 0 * STRIDE] = column.loader.loadHighFrom(input);
} else {
// non-topmost row - regular loading:
column.loader.init(sizeX, sizeY, firstX, firstY - 3);
buffer[column.offset + 0 * STRIDE] = column.loader.loadHighFrom(input);
buffer[column.offset + 1 * STRIDE] = column.loader.loadLowFrom(input);
buffer[column.offset + 2 * STRIDE] = column.loader.loadHighFrom(input);
buffer[column.offset + 3 * STRIDE] = column.loader.loadLowFrom(input);
buffer[column.offset + 4 * STRIDE] = column.loader.loadHighFrom(input);
buffer[column.offset + 5 * STRIDE] = column.loader.loadLowFrom(input);
buffer[column.offset + 6 * STRIDE] = column.loader.loadHighFrom(input);
}
// Now, the next coefficient, which will be loaded by loader, is #4.
}
/// Using given loader, it loads another WIN_SIZE_Y coefficients
/// into specified column.
/// @tparam CHECKED true if there are near image boundaries
/// @param col info about loaded column
/// @param input buffer with input coefficients
template <bool CHECKED>
inline __device__ void loadWindowIntoColumn(RDWT97Column<CHECKED> & col,
const float * const input) {
for(int i = 7; i < (7 + WIN_SIZE_Y); i += 2) {
buffer[col.offset + i * STRIDE] = col.loader.loadLowFrom(input);
buffer[col.offset + (i + 1) * STRIDE] = col.loader.loadHighFrom(input);
}
}
/// Actual GPU 9/7 RDWT sliding window lifting schema implementation.
/// @tparam CHECKED_LOADS true if loader should check boundaries
/// @tparam CHECKED_WRITES true if boundaries should be taken into account
/// when writing into output buffer
/// @param in input image (9/7 transformed coefficients)
/// @param out output buffer (for reverse transformed image)
/// @param sizeX width of the output image
/// @param sizeY height of the output image
/// @param winSteps number of steps of sliding window
template <bool CHECKED_LOADS, bool CHECKED_WRITES>
__device__ void transform(const float * const in, float * const out,
const int sizeX, const int sizeY,
const int winSteps) {
// info about one main column and one boundary column
RDWT97Column<CHECKED_LOADS> column;
RDWT97Column<CHECKED_LOADS> boundaryColumn;
// index of first image row to be transformed
const int firstY = blockIdx.y * WIN_SIZE_Y * winSteps;
// initialize boundary columns
boundaryColumn.clear();
if(threadIdx.x < 7) {
// each thread among first 7 ones gets index of one of boundary columns
const int colId = threadIdx.x + ((threadIdx.x < 4) ? WIN_SIZE_X : -7);
// Thread initializes offset of the boundary column (in shared
// buffer), first 7 pixels of the column and a loader for this column.
initColumn(colId, in, sizeX, sizeY, boundaryColumn, firstY);
}
// All threads initialize central columns.
initColumn(parityIdx<WIN_SIZE_X>(), in, sizeX, sizeY, column, firstY);
// horizontally transform first 7 rows
horizontalRDWT97(7, 0);
// writer of output pixels - initialize it
const int outputX = blockIdx.x * WIN_SIZE_X + threadIdx.x;
VerticalDWTPixelWriter<float, CHECKED_WRITES> writer;
writer.init(sizeX, sizeY, outputX, firstY);
// offset of column (in transform buffer) saved by this thread
const int outColumnOffset = buffer.getColumnOffset(threadIdx.x);
// (Each iteration assumes that first 7 rows of transform buffer are
// already loaded with horizontally transformed pixels.)
for(int w = 0; w < winSteps; w++) {
// Load another WIN_SIZE_Y lines of this thread's column
// into the transform buffer.
loadWindowIntoColumn(column, in);
// possibly load boundary columns
if(threadIdx.x < 7) {
loadWindowIntoColumn(boundaryColumn, in);
}
// horizontally transform all newly loaded lines
horizontalRDWT97(WIN_SIZE_Y, 7);
// Using 7 registers, remember current values of last 7 rows
// of transform buffer. These rows are transformed horizontally
// only and will be used in next iteration.
float last7Lines[7];
for(int i = 0; i < 7; i++) {
last7Lines[i] = buffer[outColumnOffset + (WIN_SIZE_Y + i) * STRIDE];
}
// vertically transform all central columns
buffer.scaleVertical(scale97Div, scale97Mul, outColumnOffset,
WIN_SIZE_Y + 7, 0);
buffer.forEachVerticalOdd(outColumnOffset, AddScaledSum(r97update2));
buffer.forEachVerticalEven(outColumnOffset, AddScaledSum(r97predict2));
buffer.forEachVerticalOdd(outColumnOffset, AddScaledSum(r97update1));
buffer.forEachVerticalEven(outColumnOffset, AddScaledSum(r97Predict1));
// Save all results of current window. Results are in transform buffer
// at rows from #3 to #(3 + WIN_SIZE_Y). Other rows are invalid now.
// (They only served as a boundary for vertical RDWT.)
for(int i = 3; i < (3 + WIN_SIZE_Y); i++) {
writer.writeInto(out, buffer[outColumnOffset + i * STRIDE]);
}
// Use last 7 remembered lines as first 7 lines for next iteration.
// As expected, these lines are already horizontally transformed.
for(int i = 0; i < 7; i++) {
buffer[outColumnOffset + i * STRIDE] = last7Lines[i];
}
// Wait for all writing threads before proceeding to loading new
// coeficients in next iteration. (Not to overwrite those which
// are not written yet.)
__syncthreads();
}
}
public:
/// Main GPU 9/7 RDWT entry point.
/// @param in input image (9/7 transformed coefficients)
/// @param out output buffer (for reverse transformed image)
/// @param sizeX width of the output image
/// @param sizeY height of the output image
__device__ static void run(const float * const input, float * const output,
const int sx, const int sy, const int steps) {
// prepare instance with buffer in shared memory
__shared__ RDWT97<WIN_SIZE_X, WIN_SIZE_Y> rdwt97;
// Compute limits of this threadblock's block of pixels and use them to
// determine, whether this threadblock will have to deal with boundary.
// (3 in next expressions is for radius of impulse response of 9/7 RDWT.)
const int maxX = (blockIdx.x + 1) * WIN_SIZE_X + 3;
const int maxY = (blockIdx.y + 1) * WIN_SIZE_Y * steps + 3;
const bool atRightBoudary = maxX >= sx;
const bool atBottomBoudary = maxY >= sy;
// Select specialized version of code according to distance of this
// threadblock's pixels from image boundary.
if(atBottomBoudary) {
// near bottom boundary => check both writing and reading
rdwt97.transform<true, true>(input, output, sx, sy, steps);
} else if(atRightBoudary) {
// near right boundary only => check writing only
rdwt97.transform<false, true>(input, output, sx, sy, steps);
} else {
// no nearby boundary => check nothing
rdwt97.transform<false, false>(input, output, sx, sy, steps);
}
}
}; // end of class RDWT97
/// Main GPU 9/7 RDWT entry point.
/// @param in input image (9/7 transformed coefficients)
/// @param out output buffer (for reverse transformed image)
/// @param sizeX width of the output image
/// @param sizeY height of the output image
template <int WIN_SX, int WIN_SY>
__launch_bounds__(WIN_SX, CTMIN(SHM_SIZE/sizeof(RDWT97<WIN_SX, WIN_SY>), 8))
__global__ void rdwt97Kernel(const float * const in, float * const out,
const int sx, const int sy, const int steps) {
RDWT97<WIN_SX, WIN_SY>::run(in, out, sx, sy, steps);
}
/// Only computes optimal number of sliding window steps,
/// number of threadblocks and then lanches the 9/7 RDWT kernel.
/// @tparam WIN_SX width of sliding window
/// @tparam WIN_SY height of sliding window
/// @param in input image
/// @param out output buffer
/// @param sx width of the input image
/// @param sy height of the input image
template <int WIN_SX, int WIN_SY>
void launchRDWT97Kernel (float * in, float * out, int sx, int sy) {
// compute optimal number of steps of each sliding window
const int steps = divRndUp(sy, 15 * WIN_SY);
// prepare grid size
dim3 gSize(divRndUp(sx, WIN_SX), divRndUp(sy, WIN_SY * steps));
// finally launch kernel
PERF_BEGIN
rdwt97Kernel<WIN_SX, WIN_SY><<<gSize, WIN_SX>>>(in, out, sx, sy, steps);
PERF_END(" RDWT97", sx, sy)
CudaDWTTester::checkLastKernelCall("RDWT 9/7 kernel");
}
/// Reverse 9/7 2D DWT. See common rules (dwt.h) for more details.
/// @param in Input DWT coefficients. Format described in common rules.
/// Will not be preserved (will be overwritten).
/// @param out output buffer on GPU - will contain original image
/// in normalized range [-0.5, 0.5].
/// @param sizeX width of input image (in pixels)
/// @param sizeY height of input image (in pixels)
/// @param levels number of recursive DWT levels
void rdwt97(float * in, float * out, int sizeX, int sizeY, int levels) {
if(levels > 1) {
// let this function recursively reverse transform deeper levels first
const int llSizeX = divRndUp(sizeX, 2);
const int llSizeY = divRndUp(sizeY, 2);
rdwt97(in, out, llSizeX, llSizeY, levels - 1);
// copy reverse transformed LL band from output back into the input
memCopy(in, out, llSizeX, llSizeY);
}
// select right width of kernel for the size of the image
if(sizeX >= 960) {
launchRDWT97Kernel<192, 8>(in, out, sizeX, sizeY);
} else if (sizeX >= 480) {
launchRDWT97Kernel<128, 6>(in, out, sizeX, sizeY);
} else {
launchRDWT97Kernel<64, 6>(in, out, sizeX, sizeY);
}
}
} // end of namespace dwt_cuda

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/// line 248 the index
/// @file transform_buffer.h
/// @brief Buffer with separated even and odd columns and related algorithms.
/// @author Martin Jirman (207962@mail.muni.cz)
/// @date 2011-01-20 18:33
///
///
/// Copyright (c) 2011 Martin Jirman
/// All rights reserved.
///
/// Redistribution and use in source and binary forms, with or without
/// modification, are permitted provided that the following conditions are met:
///
/// * Redistributions of source code must retain the above copyright
/// notice, this list of conditions and the following disclaimer.
/// * Redistributions in binary form must reproduce the above copyright
/// notice, this list of conditions and the following disclaimer in the
/// documentation and/or other materials provided with the distribution.
///
/// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
/// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
/// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
/// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
/// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
/// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
/// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
/// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
/// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
/// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
/// POSSIBILITY OF SUCH DAMAGE.
///
#ifndef TRANSFORM_BUFFER_H
#define TRANSFORM_BUFFER_H
namespace dwt_cuda {
/// Buffer (in shared memory of GPU) where block of input image is stored,
/// but odd and even lines are separated. (Generates less bank conflicts when
/// using lifting schema.) All operations expect SIZE_X threads.
/// Also implements basic building blocks of lifting schema.
/// @tparam SIZE_X width of the buffer excluding two boundaries (Also
/// a number of threads participating on all operations.)
/// Must be divisible by 4.
/// @tparam SIZE_Y height of buffer (total number of lines)
/// @tparam BOUNDARY_X number of extra pixels at the left and right side
/// boundary is expected to be smaller than half SIZE_X
/// Must be divisible by 2.
template <typename T, int SIZE_X, int SIZE_Y, int BOUNDARY_X>
class TransformBuffer {
public:
enum {
/// difference between pointers to two vertical neigbors
VERTICAL_STRIDE = BOUNDARY_X + (SIZE_X / 2)
};
private:
enum {
/// number of shared memory banks - needed for correct padding
#ifdef __CUDA_ARCH__
SHM_BANKS = ((__CUDA_ARCH__ >= 200) ? 32 : 16),
#else
SHM_BANKS = 16, // for host code only - can be anything, won't be used
#endif
/// size of one of two buffers (odd or even)
BUFFER_SIZE = VERTICAL_STRIDE * SIZE_Y,
/// unused space between two buffers
PADDING = SHM_BANKS - ((BUFFER_SIZE + SHM_BANKS / 2) % SHM_BANKS),
/// offset of the odd columns buffer from the beginning of data buffer
ODD_OFFSET = BUFFER_SIZE + PADDING,
};
/// buffer for both even and odd columns
T data[2 * BUFFER_SIZE + PADDING];
/// Applies specified function to all central elements while also passing
/// previous and next elements as parameters.
/// @param count count of central elements to apply function to
/// @param prevOffset offset of first central element
/// @param midOffset offset of first central element's predecessor
/// @param nextOffset offset of first central element's successor
/// @param function the function itself
template <typename FUNC>
__device__ void horizontalStep(const int count, const int prevOffset,
const int midOffset, const int nextOffset,
const FUNC & function) {
// number of unchecked iterations
const int STEPS = count / SIZE_X;
// items remaining after last unchecked iteration
const int finalCount = count % SIZE_X;
// offset of items processed in last (checked) iteration
const int finalOffset = count - finalCount;
// all threads perform fixed number of iterations ...
for(int i = 0; i < STEPS; i++) {
// for(int i = 0; i < 3; i++) {
const T previous = data[prevOffset + i * SIZE_X + threadIdx.x];
const T next = data[nextOffset + i * SIZE_X + threadIdx.x];
T & center = data[midOffset + i * SIZE_X + threadIdx.x];
// function(previous, center, (nextOffset + i*SIZE_X+threadIdx.x));
function(previous, center, next);// the real one
}
// ... but not all threads participate on final iteration
if(threadIdx.x < finalCount) {
const T previous = data[prevOffset + finalOffset + threadIdx.x];
const T next = data[nextOffset + finalOffset + threadIdx.x];
T & center = data[midOffset + finalOffset + threadIdx.x];
// function(previous, center, (nextOffset+finalOffset+threadIdx.x));
// kaixi
function(previous, center, next);//the real one
}
}
public:
__device__ void getPrintData() {
//
for(int i = 0 ; i< 2 * BUFFER_SIZE + PADDING ; i++) {
printf(" index: %d data: %f \n ", i ,data[i]);
}
}
/// Gets offset of the column with given index. Central columns have
/// indices from 0 to NUM_LINES - 1, left boundary columns have negative
/// indices and right boundary columns indices start with NUM_LINES.
/// @param columnIndex index of column to get pointer to
/// @return offset of the first item of column with specified index
__device__ int getColumnOffset(int columnIndex) {
columnIndex += BOUNDARY_X; // skip boundary
return columnIndex / 2 // select right column
+ (columnIndex & 1) * ODD_OFFSET; // select odd or even buffer
}
/// Provides access to data of the transform buffer.
/// @param index index of the item to work with
/// @return reference to item at given index
__device__ T & operator[] (const int index) {
return data[index];
}
/// Applies specified function to all horizontally even elements in
/// specified lines. (Including even elements in boundaries except
/// first even element in first left boundary.) SIZE_X threads participate
/// and synchronization is needed before result can be used.
/// @param firstLine index of first line
/// @param numLines count of lines
/// @param func function to be applied on all even elements
/// parameters: previous (odd) element, the even
/// element itself and finally next (odd) element
template <typename FUNC>
__device__ void forEachHorizontalEven(const int firstLine,
const int numLines,
const FUNC & func) {
// number of even elemens to apply function to
const int count = numLines * VERTICAL_STRIDE - 1;
// offset of first even element
const int centerOffset = firstLine * VERTICAL_STRIDE + 1;
// offset of odd predecessor of first even element
const int prevOffset = firstLine * VERTICAL_STRIDE + ODD_OFFSET;
// offset of odd successor of first even element
const int nextOffset = prevOffset + 1;
// if(threadIdx.x == 0) {
// printf("forEachHorizontalEven count %d, centerOffset %d prevOffset %d nextOffset %d \n", count, centerOffset, prevOffset, nextOffset);
// }
// call generic horizontal step function
horizontalStep(count, prevOffset, centerOffset, nextOffset, func);
}
/// Applies given function to all horizontally odd elements in specified
/// lines. (Including odd elements in boundaries except last odd element
/// in last right boundary.) SIZE_X threads participate and synchronization
/// is needed before result can be used.
/// @param firstLine index of first line
/// @param numLines count of lines
/// @param func function to be applied on all odd elements
/// parameters: previous (even) element, the odd
/// element itself and finally next (even) element
template <typename FUNC>
__device__ void forEachHorizontalOdd(const int firstLine,
const int numLines,
const FUNC & func) {
// numbet of odd elements to apply function to
const int count = numLines * VERTICAL_STRIDE - 1;
// offset of even predecessor of first odd element
const int prevOffset = firstLine * VERTICAL_STRIDE;
// offset of first odd element
const int centerOffset = prevOffset + ODD_OFFSET;
// offset of even successor of first odd element
const int nextOffset = prevOffset + 1;
// if(threadIdx.x == 0) {
// printf("forEachHorizontalOdd count %d, centerOffset %d prevOffset %d nextOffset %d \n", count, centerOffset, prevOffset, nextOffset);
// }
// call generic horizontal step function
horizontalStep(count, prevOffset, centerOffset, nextOffset, func);
}
/// Applies specified function to all even elements (except element #0)
/// of given column. Each thread takes care of one column, so there's
/// no need for synchronization.
/// @param columnOffset offset of thread's column
/// @param f function to be applied on all even elements
/// parameters: previous (odd) element, the even
/// element itself and finally next (odd) element
template <typename F>
__device__ void forEachVerticalEven(const int columnOffset, const F & f) {
if(SIZE_Y > 3) { // makes no sense otherwise
const int steps = SIZE_Y / 2 - 1;
for(int i = 0; i < steps; i++) {
const int row = 2 + i * 2;
const T prev = data[columnOffset + (row - 1) * VERTICAL_STRIDE];
const T next = data[columnOffset + (row + 1) * VERTICAL_STRIDE];
f(prev, data[columnOffset + row * VERTICAL_STRIDE] , next);
//--------------- FOR TEST -----------------
/* __syncthreads();
if ((blockIdx.x * blockDim.x + threadIdx.x) == 0){
diffOut[2500]++;
diffOut[diffOut[2500]] = 2;//data[columnOffset + row * VERTICAL_STRIDE];
}
__syncthreads();
*/ //--------------- FOR TEST -----------------
}
}
}
/// Applies specified function to all odd elements of given column.
/// Each thread takes care of one column, so there's no need for
/// synchronization.
/// @param columnOffset offset of thread's column
/// @param f function to be applied on all odd elements
/// parameters: previous (even) element, the odd
/// element itself and finally next (even) element
template <typename F>
__device__ void forEachVerticalOdd(const int columnOffset, const F & f) {
const int steps = (SIZE_Y - 1) / 2;
for(int i = 0; i < steps; i++) {
const int row = i * 2 + 1;
const T prev = data[columnOffset + (row - 1) * VERTICAL_STRIDE];
const T next = data[columnOffset + (row + 1) * VERTICAL_STRIDE];
f(prev, data[columnOffset + row * VERTICAL_STRIDE], next);
//--------------- FOR TEST -----------------
/* __syncthreads();
if ((blockIdx.x * blockDim.x + threadIdx.x) == 0){
diffOut[2500]++;
diffOut[diffOut[2500]] = 1; //data[columnOffset + row * VERTICAL_STRIDE];
}
__syncthreads();
*/ //--------------- FOR TEST -----------------
}
}
/// Scales elements at specified lines.
/// @param evenScale scaling factor for horizontally even elements
/// @param oddScale scaling factor for horizontally odd elements
/// @param numLines number of lines, whose elements should be scaled
/// @param firstLine index of first line to scale elements in
__device__ void scaleHorizontal(const T evenScale, const T oddScale,
const int firstLine, const int numLines) {
const int offset = firstLine * VERTICAL_STRIDE;
const int count = numLines * VERTICAL_STRIDE;
const int steps = count / SIZE_X;
const int finalCount = count % SIZE_X;
const int finalOffset = count - finalCount;
// printf("scaleHorizontal sizeX: %d offset %d, count, %d, steps, %d, finalCount %d, finalOffset %d \n", SIZE_X, offset, count, steps, finalCount, finalOffset);
// run iterations, whete all threads participate
for(int i = 0; i < steps; i++) {
data[threadIdx.x + i * SIZE_X + offset] *= evenScale;
// if(threadIdx.x + i * SIZE_X + offset == 531) {
// printf("threadidx 531: %d \n", threadIdx.x);
// }
// if(threadIdx.x + i * SIZE_X + offset + ODD_OFFSET == 531) {
// printf("threadidx 531: %d \n", threadIdx.x);
// }
data[threadIdx.x + i * SIZE_X + offset + ODD_OFFSET] *= oddScale;
}
// some threads also finish remaining unscaled items
if(threadIdx.x < finalCount) {
data[threadIdx.x + finalOffset + offset] *= evenScale;
// if(threadIdx.x + finalOffset + offset == 531) {
// printf("threadidx 531: %d \n", threadIdx.x);
// }
// if(threadIdx.x + finalOffset + offset + ODD_OFFSET == 531) {
// printf("threadidx 531: %d \n", threadIdx.x);
// }
data[threadIdx.x + finalOffset + offset + ODD_OFFSET] *= oddScale;
}
}
/// Scales elements in specified column.
/// @param evenScale scaling factor for vertically even elements
/// @param oddScale scaling factor for vertically odd elements
/// @param columnOffset offset of the column to work with
/// @param numLines number of lines, whose elements should be scaled
/// @param firstLine index of first line to scale elements in
__device__ void scaleVertical(const T evenScale, const T oddScale,
const int columnOffset, const int numLines,
const int firstLine) {
for(int i = firstLine; i < (numLines + firstLine); i++) {
if(i & 1) {
data[columnOffset + i * VERTICAL_STRIDE] *= oddScale;
} else {
data[columnOffset + i * VERTICAL_STRIDE] *= evenScale;
}
}
}
//****************For Test(Feb23), test inter parameters*************
__device__ int getVERTICAL_STRIDE(){
return VERTICAL_STRIDE;
}
__device__ int getSHM_BANKS(){
return SHM_BANKS;
}
__device__ int getBuffersize(){
return BUFFER_SIZE;
}
__device__ int getPADDING(){
return PADDING;
}
__device__ int getODD_OFFSET(){
return ODD_OFFSET;
}
//****************For Test(Feb23), test inter parameters*************
}; // end of class TransformBuffer
} // namespace dwt_cuda
#endif // TRANSFORM_BUFFER_H

401
examples/dwt2d/main.cu Executable file
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@ -0,0 +1,401 @@
/*
* Copyright (c) 2009, Jiri Matela
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*/
#include <unistd.h>
#include <error.h>
#include <stdio.h>
#include <stdlib.h>
#include <fcntl.h>
#include <errno.h>
#include <string.h>
#include <assert.h>
#include <sys/time.h>
#include <getopt.h>
#include "common.h"
#include "components.h"
#include "dwt.h"
struct dwt {
char * srcFilename;
char * outFilename;
unsigned char *srcImg;
int pixWidth;
int pixHeight;
int components;
int dwtLvls;
};
int getImg(char * srcFilename, unsigned char *srcImg, int inputSize)
{
// printf("Loading ipnput: %s\n", srcFilename);
char *path = "../../data/dwt2d/";
char *newSrc = NULL;
if((newSrc = (char *)malloc(strlen(srcFilename)+strlen(path)+1)) != NULL)
{
newSrc[0] = '\0';
strcat(newSrc, path);
strcat(newSrc, srcFilename);
srcFilename= newSrc;
}
printf("Loading ipnput: %s\n", srcFilename);
//srcFilename = strcat("../../data/dwt2d/",srcFilename);
//read image
int i = open(srcFilename, O_RDONLY, 0644);
if (i == -1) {
error(0,errno,"cannot access %s", srcFilename);
return -1;
}
int ret = read(i, srcImg, inputSize);
printf("precteno %d, inputsize %d\n", ret, inputSize);
close(i);
return 0;
}
void usage() {
printf("dwt [otpions] src_img.rgb <out_img.dwt>\n\
-d, --dimension\t\tdimensions of src img, e.g. 1920x1080\n\
-c, --components\t\tnumber of color components, default 3\n\
-b, --depth\t\t\tbit depth, default 8\n\
-l, --level\t\t\tDWT level, default 3\n\
-D, --device\t\t\tcuda device\n\
-f, --forward\t\t\tforward transform\n\
-r, --reverse\t\t\treverse transform\n\
-9, --97\t\t\t9/7 transform\n\
-5, --53\t\t\t5/3 transform\n\
-w --write-visual\t\twrite output in visual (tiled) fashion instead of the linear\n");
}
template <typename T>
void processDWT(struct dwt *d, int forward, int writeVisual)
{
int componentSize = d->pixWidth*d->pixHeight*sizeof(T);
T *c_r_out, *backup ;
cudaMalloc((void**)&c_r_out, componentSize); //< aligned component size
cudaCheckError("Alloc device memory");
cudaMemset(c_r_out, 0, componentSize);
cudaCheckError("Memset device memory");
cudaMalloc((void**)&backup, componentSize); //< aligned component size
cudaCheckError("Alloc device memory");
cudaMemset(backup, 0, componentSize);
cudaCheckError("Memset device memory");
if (d->components == 3) {
/* Alloc two more buffers for G and B */
T *c_g_out, *c_b_out;
cudaMalloc((void**)&c_g_out, componentSize); //< aligned component size
cudaCheckError("Alloc device memory");
cudaMemset(c_g_out, 0, componentSize);
cudaCheckError("Memset device memory");
cudaMalloc((void**)&c_b_out, componentSize); //< aligned component size
cudaCheckError("Alloc device memory");
cudaMemset(c_b_out, 0, componentSize);
cudaCheckError("Memset device memory");
/* Load components */
T *c_r, *c_g, *c_b;
cudaMalloc((void**)&c_r, componentSize); //< R, aligned component size
cudaCheckError("Alloc device memory");
cudaMemset(c_r, 0, componentSize);
cudaCheckError("Memset device memory");
cudaMalloc((void**)&c_g, componentSize); //< G, aligned component size
cudaCheckError("Alloc device memory");
cudaMemset(c_g, 0, componentSize);
cudaCheckError("Memset device memory");
cudaMalloc((void**)&c_b, componentSize); //< B, aligned component size
cudaCheckError("Alloc device memory");
cudaMemset(c_b, 0, componentSize);
cudaCheckError("Memset device memory");
rgbToComponents(c_r, c_g, c_b, d->srcImg, d->pixWidth, d->pixHeight);
/* Compute DWT and always store into file */
nStage2dDWT(c_r, c_r_out, backup, d->pixWidth, d->pixHeight, d->dwtLvls, forward);
nStage2dDWT(c_g, c_g_out, backup, d->pixWidth, d->pixHeight, d->dwtLvls, forward);
nStage2dDWT(c_b, c_b_out, backup, d->pixWidth, d->pixHeight, d->dwtLvls, forward);
// -------test----------
// T *h_r_out=(T*)malloc(componentSize);
// cudaMemcpy(h_r_out, c_g_out, componentSize, cudaMemcpyDeviceToHost);
// int ii;
// for(ii=0;ii<componentSize/sizeof(T);ii++) {
// fprintf(stderr, "%d ", h_r_out[ii]);
// if((ii+1) % (d->pixWidth) == 0) fprintf(stderr, "\n");
// }
// -------test----------
/* Store DWT to file */
writeLinear(c_r_out, d->pixWidth, d->pixHeight, d->outFilename, ".r");
// writeLinear(c_g_out, d->pixWidth, d->pixHeight, d->outFilename, ".g");
// writeLinear(c_b_out, d->pixWidth, d->pixHeight, d->outFilename, ".b");
#ifdef OUTPUT
if (writeVisual) {
writeNStage2DDWT(c_r_out, d->pixWidth, d->pixHeight, d->dwtLvls, d->outFilename, ".r");
writeNStage2DDWT(c_g_out, d->pixWidth, d->pixHeight, d->dwtLvls, d->outFilename, ".g");
writeNStage2DDWT(c_b_out, d->pixWidth, d->pixHeight, d->dwtLvls, d->outFilename, ".b");
} else {
writeLinear(c_r_out, d->pixWidth, d->pixHeight, d->outFilename, ".r");
writeLinear(c_g_out, d->pixWidth, d->pixHeight, d->outFilename, ".g");
writeLinear(c_b_out, d->pixWidth, d->pixHeight, d->outFilename, ".b");
}
#endif
cudaFree(c_r);
cudaCheckError("Cuda free");
cudaFree(c_g);
cudaCheckError("Cuda free");
cudaFree(c_b);
cudaCheckError("Cuda free");
cudaFree(c_g_out);
cudaCheckError("Cuda free");
cudaFree(c_b_out);
cudaCheckError("Cuda free");
}
else if (d->components == 1) {
//Load component
T *c_r;
cudaMalloc((void**)&(c_r), componentSize); //< R, aligned component size
cudaCheckError("Alloc device memory");
cudaMemset(c_r, 0, componentSize);
cudaCheckError("Memset device memory");
bwToComponent(c_r, d->srcImg, d->pixWidth, d->pixHeight);
// Compute DWT
nStage2dDWT(c_r, c_r_out, backup, d->pixWidth, d->pixHeight, d->dwtLvls, forward);
// Store DWT to file
// #ifdef OUTPUT
if (writeVisual) {
writeNStage2DDWT(c_r_out, d->pixWidth, d->pixHeight, d->dwtLvls, d->outFilename, ".out");
} else {
writeLinear(c_r_out, d->pixWidth, d->pixHeight, d->outFilename, ".lin.out");
}
// #endif
cudaFree(c_r);
cudaCheckError("Cuda free");
}
cudaFree(c_r_out);
cudaCheckError("Cuda free device");
cudaFree(backup);
cudaCheckError("Cuda free device");
}
int main(int argc, char **argv)
{
int optindex = 0;
char ch;
struct option longopts[] = {
{"dimension", required_argument, 0, 'd'}, //dimensions of src img
{"components", required_argument, 0, 'c'}, //numger of components of src img
{"depth", required_argument, 0, 'b'}, //bit depth of src img
{"level", required_argument, 0, 'l'}, //level of dwt
{"device", required_argument, 0, 'D'}, //cuda device
{"forward", no_argument, 0, 'f'}, //forward transform
{"reverse", no_argument, 0, 'r'}, //reverse transform
{"97", no_argument, 0, '9'}, //9/7 transform
{"53", no_argument, 0, '5' }, //5/3transform
{"write-visual",no_argument, 0, 'w' }, //write output (subbands) in visual (tiled) order instead of linear
{"help", no_argument, 0, 'h'}
};
int pixWidth = 0; //<real pixWidth
int pixHeight = 0; //<real pixHeight
int compCount = 3; //number of components; 3 for RGB or YUV, 4 for RGBA
int bitDepth = 8;
int dwtLvls = 3; //default numuber of DWT levels
int device = 0;
int forward = 1; //forward transform
int dwt97 = 1; //1=dwt9/7, 0=dwt5/3 transform
int writeVisual = 0; //write output (subbands) in visual (tiled) order instead of linear
char * pos;
while ((ch = getopt_long(argc, argv, "d:c:b:l:D:fr95wh", longopts, &optindex)) != -1) {
switch (ch) {
case 'd':
pixWidth = atoi(optarg);
pos = strstr(optarg, "x");
if (pos == NULL || pixWidth == 0 || (strlen(pos) >= strlen(optarg))) {
usage();
return -1;
}
pixHeight = atoi(pos+1);
break;
case 'c':
compCount = atoi(optarg);
break;
case 'b':
bitDepth = atoi(optarg);
break;
case 'l':
dwtLvls = atoi(optarg);
break;
case 'D':
device = atoi(optarg);
break;
case 'f':
forward = 1;
break;
case 'r':
forward = 0;
break;
case '9':
dwt97 = 1;
break;
case '5':
dwt97 = 0;
break;
case 'w':
writeVisual = 1;
break;
case 'h':
usage();
return 0;
case '?':
return -1;
default :
usage();
return -1;
}
}
argc -= optind;
argv += optind;
if (argc == 0) { // at least one filename is expected
printf("Please supply src file name\n");
usage();
return -1;
}
if (pixWidth <= 0 || pixHeight <=0) {
printf("Wrong or missing dimensions\n");
usage();
return -1;
}
if (forward == 0) {
writeVisual = 0; //do not write visual when RDWT
}
// device init
int devCount;
cudaSetDevice(0);
cudaGetDeviceCount(&devCount);
cudaCheckError("Get device count");
if (devCount == 0) {
printf("No CUDA enabled device\n");
return -1;
}
if (device < 0 || device > devCount -1) {
printf("Selected device %d is out of bound. Devices on your system are in range %d - %d\n",
device, 0, devCount -1);
return -1;
}
cudaDeviceProp devProp;
cudaGetDeviceProperties(&devProp, device);
cudaCheckError("Get device properties");
// if (devProp.major < 1) {
// printf("Device %d does not support CUDA\n", device);
// return -1;
// }
printf("Using device %d: %s\n", device, devProp.name);
cudaSetDevice(device);
cudaCheckError("Set selected device");
struct dwt *d;
d = (struct dwt *)malloc(sizeof(struct dwt));
d->srcImg = NULL;
d->pixWidth = pixWidth;
d->pixHeight = pixHeight;
d->components = compCount;
d->dwtLvls = dwtLvls;
// file names
d->srcFilename = (char *)malloc(strlen(argv[0]));
strcpy(d->srcFilename, argv[0]);
if (argc == 1) { // only one filename supplyed
d->outFilename = (char *)malloc(strlen(d->srcFilename)+4);
strcpy(d->outFilename, d->srcFilename);
strcpy(d->outFilename+strlen(d->srcFilename), ".dwt");
} else {
d->outFilename = strdup(argv[1]);
}
//Input review
printf("Source file:\t\t%s\n", d->srcFilename);
printf(" Dimensions:\t\t%dx%d\n", pixWidth, pixHeight);
printf(" Components count:\t%d\n", compCount);
printf(" Bit depth:\t\t%d\n", bitDepth);
printf(" DWT levels:\t\t%d\n", dwtLvls);
printf(" Forward transform:\t%d\n", forward);
printf(" 9/7 transform:\t\t%d\n", dwt97);
//data sizes
int inputSize = pixWidth*pixHeight*compCount; //<amount of data (in bytes) to proccess
//load img source image
cudaMallocHost((void **)&d->srcImg, inputSize);
cudaCheckError("Alloc host memory");
if (getImg(d->srcFilename, d->srcImg, inputSize) == -1)
return -1;
/* DWT */
if (forward == 1) {
if(dwt97 == 1 )
processDWT<float>(d, forward, writeVisual);
else // 5/3
processDWT<int>(d, forward, writeVisual);
}
else { // reverse
if(dwt97 == 1 )
processDWT<float>(d, forward, writeVisual);
else // 5/3
processDWT<int>(d, forward, writeVisual);
}
//writeComponent(r_cuda, pixWidth, pixHeight, srcFilename, ".g");
//writeComponent(g_wave_cuda, 512000, ".g");
//writeComponent(g_cuda, componentSize, ".g");
//writeComponent(b_wave_cuda, componentSize, ".b");
cudaFreeHost(d->srcImg);
cudaCheckError("Cuda free host");
return 0;
}

8
examples/dwt2d/run.sh Executable file
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@ -0,0 +1,8 @@
./dwt2d 4.bmp z.dwt -d 4x4 -f -5 -l 3
# ./dwt2d 8.bmp -d 8x8 -f -5 -l 3
# ./dwt2d 16.bmp -d 16x16 -f -5 -l 3
# ./dwt2d 64.bmp -d 64x64 -f -5 -l 3
# ./dwt2d 192.bmp -d 192x192 -f -5 -l 3
# ls
# ./dwt2d rgb.bmp -d 1024x1024 -f -5 -l 3

8
examples/dwt2d/run_cpu.sh Executable file
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@ -0,0 +1,8 @@
# ./dwt2d 192.bmp -d 192x192 -f -5 -l 3
# ls
# ./dwt2d rgb.bmp -d 1024x1024 -f -5 -l 3
# ./dwt2d 16.bmp -d 16x16 -f -9 -l 3\
./dwt2d 4.bmp -d 4x4 -r -5 -l 3
# ./dwt2d 4.bmp -d 4x4 -r -9 -l 3
# ./dwt2d 8.bmp -d 8x8 -f -9 -l 3

14
examples/dwt2d/run_nvcc.sh Normal file
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@ -0,0 +1,14 @@
# ./nvcc_dwt2d 192.bmp -d 192x192 -f -5 -l 3
# ls
# ./nvcc_dwt2d rgb.bmp -d 1024x1024 -f -5 -l 3
# ./nvcc_dwt2d 4.bmp -d 4x4 -f -9 -l 3
./nvcc_dwt2d 4.bmp -d 4x4 -f -5 -l 3
# ./nvcc_dwt2d 8.bmp -d 8x8 -f -9 -l 3
# ./nvcc_dwt2d 16.bmp -d 16x16 -f -5 -l 3
# ./nvcc_dwt2d 16.bmp -d 16x16 -r -5 -l 3
# ./nvcc_dwt2d 16.bmp -d 16x16 -f -9 -l 3
# ./nvcc_dwt2d 4.bmp -d 4x4 -r -9 -l 3
# ./nvcc_dwt2d 64.bmp -d 64x64 -f -5 -l 3
# ./nvcc_dwt2d 192.bmp -d 192x192 -f -5 -l 3
# ls
# ./nvcc_dwt2d rgb.bmp -d 1024x1024 -f -5 -l 3

51
examples/dwt2d/test_compile_cpu.sh Normal file
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@ -0,0 +1,51 @@
#!/bin/bash
clang++ -I. -I/include -fno-strict-aliasing dwt_cuda/fdwt53.cu dwt_cuda/fdwt97.cu dwt_cuda/common.cu dwt_cuda/rdwt97.cu dwt_cuda/rdwt53.cu components.cu dwt.cu main.cu -c --cuda-path=/usr/local/cuda-10.1 --cuda-gpu-arch=sm_50 -I. -I/include -L/usr/local/cuda-10.1/lib64 -lcudart_static -ldl -lrt -pthread -save-temps -v
export LD_LIBRARY_PATH=../../build/runtime:../../build/runtime/threadPool:$LD_LIBRARY_PATH
../../build/compilation/kernelTranslator common-cuda-nvptx64-nvidia-cuda-sm_50.bc common.bc
../../build/compilation/kernelTranslator components-cuda-nvptx64-nvidia-cuda-sm_50.bc components.bc
../../build/compilation/kernelTranslator fdwt53-cuda-nvptx64-nvidia-cuda-sm_50.bc fdwt53.bc
../../build/compilation/kernelTranslator dwt-cuda-nvptx64-nvidia-cuda-sm_50.bc dwt.bc
../../build/compilation/hostTranslator main-host-x86_64-unknown-linux-gnu.bc host.bc
../../build/compilation/hostTranslator common-host-x86_64-unknown-linux-gnu.bc common_host.bc
../../build/compilation/hostTranslator components-host-x86_64-unknown-linux-gnu.bc components_host.bc
../../build/compilation/hostTranslator dwt-host-x86_64-unknown-linux-gnu.bc dwt_host.bc
../../build/compilation/hostTranslator fdwt53-host-x86_64-unknown-linux-gnu.bc fdwt53_host.bc
../../build/compilation/hostTranslator fdwt97-host-x86_64-unknown-linux-gnu.bc fdwt97_host.bc
../../build/compilation/hostTranslator rdwt53-host-x86_64-unknown-linux-gnu.bc rdwt53_host.bc
../../build/compilation/hostTranslator rdwt97-host-x86_64-unknown-linux-gnu.bc rdwt97_host.bc
../../build/compilation/kernelTranslator fdwt97-cuda-nvptx64-nvidia-cuda-sm_50.bc fdwt97.bc
../../build/compilation/kernelTranslator rdwt97-cuda-nvptx64-nvidia-cuda-sm_50.bc rdwt97.bc
../../build/compilation/kernelTranslator rdwt53-cuda-nvptx64-nvidia-cuda-sm_50.bc rdwt53.bc
llc --relocation-model=pic --filetype=obj common.bc
llc --relocation-model=pic --filetype=obj components.bc
llc --relocation-model=pic --filetype=obj fdwt53.bc
llc --relocation-model=pic --filetype=obj dwt.bc
llc --relocation-model=pic --filetype=obj host.bc
llc --relocation-model=pic --filetype=obj common_host.bc
llc --relocation-model=pic --filetype=obj components_host.bc
llc --relocation-model=pic --filetype=obj fdwt53_host.bc
llc --relocation-model=pic --filetype=obj dwt_host.bc
llc --relocation-model=pic --filetype=obj fdwt97_host.bc
llc --relocation-model=pic --filetype=obj rdwt97_host.bc
llc --relocation-model=pic --filetype=obj rdwt53_host.bc
llc --relocation-model=pic --filetype=obj fdwt97.bc
llc --relocation-model=pic --filetype=obj rdwt97.bc
llc --relocation-model=pic --filetype=obj rdwt53.bc
g++ -g -Wall -L../../build/runtime -L../../build/runtime/threadPool -o dwt2d -fPIC -no-pie common.o components.o dwt.o fdwt53.o fdwt97.o rdwt97.o rdwt53.o host.o common_host.o components_host.o dwt_host.o fdwt53_host.o fdwt97_host.o rdwt97_host.o rdwt53_host.o -lc -lx86Runtime -lthreadPool -lpthread

18
examples/dwt2d/test_compile_nvcc.sh Executable file
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@ -0,0 +1,18 @@
/usr/local/cuda/bin/nvcc -arch sm_50 -I. -I/include -O2 --compiler-options -fno-strict-aliasing -c main.cu -o main.cu.o
/usr/local/cuda/bin/nvcc -arch sm_50 -I. -I/include -O2 --compiler-options -fno-strict-aliasing -c dwt.cu -o dwt.cu.o
/usr/local/cuda/bin/nvcc -arch sm_50 -I. -I/include -O2 --compiler-options -fno-strict-aliasing -c components.cu -o components.cu.o
/usr/local/cuda/bin/nvcc -arch sm_50 -I. -I/include -O2 --compiler-options -fno-strict-aliasing -c dwt_cuda/fdwt53.cu -o dwt_cuda/fdwt53.cu.o
/usr/local/cuda/bin/nvcc -arch sm_50 -I. -I/include -O2 --compiler-options -fno-strict-aliasing -c dwt_cuda/fdwt97.cu -o dwt_cuda/fdwt97.cu.o
/usr/local/cuda/bin/nvcc -arch sm_50 -I. -I/include -O2 --compiler-options -fno-strict-aliasing -c dwt_cuda/common.cu -o dwt_cuda/common.cu.o
/usr/local/cuda/bin/nvcc -arch sm_50 -I. -I/include -O2 --compiler-options -fno-strict-aliasing -c dwt_cuda/rdwt97.cu -o dwt_cuda/rdwt97.cu.o
/usr/local/cuda/bin/nvcc -arch sm_50 -I. -I/include -O2 --compiler-options -fno-strict-aliasing -c dwt_cuda/rdwt53.cu -o dwt_cuda/rdwt53.cu.o
g++ -fPIC -o nvcc_dwt2d main.cu.o dwt.cu.o components.cu.o dwt_cuda/fdwt53.cu.o dwt_cuda/fdwt97.cu.o dwt_cuda/common.cu.o dwt_cuda/rdwt97.cu.o dwt_cuda/rdwt53.cu.o -L/usr/local/cuda/lib64 -lcudart

8
runtime/lib/cudaRuntimeImpl.cpp
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@ -39,6 +39,12 @@ cudaError_t cudaMalloc(void **devPtr, size_t size) {
return cudaErrorMemoryAllocation;
return cudaSuccess;
}
cudaError_t cudaMallocHost(void **devPtr, size_t size) {
*devPtr = malloc(size);
if (devPtr == NULL)
return cudaErrorMemoryAllocation;
return cudaSuccess;
}
cudaError_t cudaMemset(void *devPtr, int value, size_t count) {
memset(devPtr, value, count);
return cudaSuccess;
@ -58,7 +64,7 @@ cudaError_t cudaMemcpy(void *dst, const void *src, size_t count,
memcpy(dst, src, count);
} else if (kind == cudaMemcpyDeviceToDevice) {
memcpy(dst, dst, count);
memcpy(dst, src, count);
} else if (kind == cudaMemcpyDefault) {
memcpy(dst, src, count);
}