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ocl: adjust worksize for filter2D and boxFilter

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This commit is contained in:
Alexander Alekhin 2013-10-30 14:57:46 +04:00
parent 8a4f1bbbdf
commit 7b0f018a74
3 changed files with 227 additions and 171 deletions
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4
modules/ocl/include/opencv2/ocl/private/util.hpp
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@ -103,7 +103,11 @@ CV_EXPORTS cl_kernel openCLGetKernelFromSource(const Context *clCxt,
const cv::ocl::ProgramEntry* source, std::string kernelName);
CV_EXPORTS cl_kernel openCLGetKernelFromSource(const Context *clCxt,
const cv::ocl::ProgramEntry* source, std::string kernelName, const char *build_options);
CV_EXPORTS cl_kernel openCLGetKernelFromSource(Context *ctx, const cv::ocl::ProgramEntry* source,
string kernelName, int channels, int depth, const char *build_options);
CV_EXPORTS void openCLVerifyKernel(const Context *clCxt, cl_kernel kernel, size_t *localThreads);
CV_EXPORTS void openCLExecuteKernel(Context *ctx, cl_kernel kernel, size_t globalThreads[3],
size_t localThreads[3], std::vector< std::pair<size_t, const void *> > &args);
CV_EXPORTS void openCLExecuteKernel(Context *clCxt , const cv::ocl::ProgramEntry* source, string kernelName, std::vector< std::pair<size_t, const void *> > &args,
int globalcols , int globalrows, size_t blockSize = 16, int kernel_expand_depth = -1, int kernel_expand_channel = -1);
CV_EXPORTS void openCLExecuteKernel_(Context *clCxt, const cv::ocl::ProgramEntry* source, std::string kernelName,

20
modules/ocl/src/cl_operations.cpp
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@ -336,8 +336,7 @@ static std::string removeDuplicatedWhiteSpaces(const char * buildOptions)
return opt;
}
void openCLExecuteKernel_(Context *ctx, const cv::ocl::ProgramEntry* source, string kernelName, size_t globalThreads[3],
size_t localThreads[3], vector< pair<size_t, const void *> > &args, int channels,
cl_kernel openCLGetKernelFromSource(Context *ctx, const cv::ocl::ProgramEntry* source, string kernelName, int channels,
int depth, const char *build_options)
{
//construct kernel name
@ -350,10 +349,14 @@ void openCLExecuteKernel_(Context *ctx, const cv::ocl::ProgramEntry* source, str
idxStr << "_D" << depth;
kernelName += idxStr.str();
cl_kernel kernel;
std::string fixedOptions = removeDuplicatedWhiteSpaces(build_options);
kernel = openCLGetKernelFromSource(ctx, source, kernelName, fixedOptions.c_str());
cl_kernel kernel = openCLGetKernelFromSource(ctx, source, kernelName, fixedOptions.c_str());
return kernel;
}
void openCLExecuteKernel(Context *ctx, cl_kernel kernel, size_t globalThreads[3],
size_t localThreads[3], vector< pair<size_t, const void *> > &args)
{
if ( localThreads != NULL)
{
globalThreads[0] = roundUp(globalThreads[0], localThreads[0]);
@ -399,6 +402,15 @@ void openCLExecuteKernel_(Context *ctx, const cv::ocl::ProgramEntry* source, str
openCLSafeCall(clReleaseKernel(kernel));
}
void openCLExecuteKernel_(Context *ctx, const cv::ocl::ProgramEntry* source, string kernelName, size_t globalThreads[3],
size_t localThreads[3], vector< pair<size_t, const void *> > &args, int channels,
int depth, const char *build_options)
{
cl_kernel kernel = openCLGetKernelFromSource(ctx, source, kernelName, channels, depth, build_options);
openCLExecuteKernel(ctx, kernel, globalThreads, localThreads, args);
}
void openCLExecuteKernel(Context *ctx, const cv::ocl::ProgramEntry* source, string kernelName,
size_t globalThreads[3], size_t localThreads[3],
vector< pair<size_t, const void *> > &args, int channels, int depth)

52
modules/ocl/src/filtering.cpp
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@ -578,7 +578,11 @@ static void GPUFilter2D(const oclMat &src, oclMat &dst, const Mat &kernel,
kernelDataFloat.size()*sizeof(float), 1, clMemcpyHostToDevice);
}
size_t BLOCK_SIZE = src.clCxt->getDeviceInfo().maxWorkItemSizes[0];
size_t tryWorkItems = src.clCxt->getDeviceInfo().maxWorkItemSizes[0];
do {
size_t BLOCK_SIZE = tryWorkItems;
while (BLOCK_SIZE > 32 && BLOCK_SIZE >= (size_t)ksize.width * 2 && BLOCK_SIZE > (size_t)src.cols * 2)
BLOCK_SIZE /= 2;
#if 1 // TODO Mode with several blocks requires a much more VGPRs, so this optimization is not actual for the current devices
size_t BLOCK_SIZE_Y = 1;
#else
@ -674,8 +678,24 @@ static void GPUFilter2D(const oclMat &src, oclMat &dst, const Mat &kernel,
extra_extrapolation ? "EXTRA_EXTRAPOLATION" : "NO_EXTRA_EXTRAPOLATION",
isIsolatedBorder ? "BORDER_ISOLATED" : "NO_BORDER_ISOLATED");
size_t gt[3] = {divUp(dst.cols, BLOCK_SIZE - (ksize.width - 1)) * BLOCK_SIZE, divUp(dst.rows, BLOCK_SIZE_Y), 1}, lt[3] = {BLOCK_SIZE, 1, 1};
openCLExecuteKernel(src.clCxt, &filtering_filter2D, "filter2D", gt, lt, args, -1, -1, build_options);
size_t lt[3] = {BLOCK_SIZE, 1, 1};
size_t gt[3] = {divUp(dst.cols, BLOCK_SIZE - (ksize.width - 1)) * BLOCK_SIZE, divUp(dst.rows, BLOCK_SIZE_Y), 1};
cl_kernel kernel = openCLGetKernelFromSource(src.clCxt, &filtering_filter2D, "filter2D", -1, -1, build_options);
size_t kernelWorkGroupSize;
openCLSafeCall(clGetKernelWorkGroupInfo(kernel, getClDeviceID(src.clCxt),
CL_KERNEL_WORK_GROUP_SIZE, sizeof(size_t), &kernelWorkGroupSize, 0));
if (lt[0] > kernelWorkGroupSize)
{
clReleaseKernel(kernel);
CV_Assert(BLOCK_SIZE > kernelWorkGroupSize);
tryWorkItems = kernelWorkGroupSize;
continue;
}
openCLExecuteKernel(src.clCxt, kernel, gt, lt, args); // kernel will be released here
} while (false);
}
Ptr<BaseFilter_GPU> cv::ocl::getLinearFilter_GPU(int /*srcType*/, int /*dstType*/, const Mat &kernel, const Size &ksize,
@ -770,7 +790,11 @@ static void GPUFilterBox(const oclMat &src, oclMat &dst,
(src.rows == dst.rows));
CV_Assert(src.oclchannels() == dst.oclchannels());
size_t BLOCK_SIZE = src.clCxt->getDeviceInfo().maxWorkItemSizes[0];
size_t tryWorkItems = src.clCxt->getDeviceInfo().maxWorkItemSizes[0];
do {
size_t BLOCK_SIZE = tryWorkItems;
while (BLOCK_SIZE > 32 && BLOCK_SIZE >= (size_t)ksize.width * 2 && BLOCK_SIZE > (size_t)src.cols * 2)
BLOCK_SIZE /= 2;
size_t BLOCK_SIZE_Y = 8; // TODO Check heuristic value on devices
while (BLOCK_SIZE_Y < BLOCK_SIZE / 8 && BLOCK_SIZE_Y * src.clCxt->getDeviceInfo().maxComputeUnits * 32 < (size_t)src.rows)
BLOCK_SIZE_Y *= 2;
@ -868,8 +892,24 @@ static void GPUFilterBox(const oclMat &src, oclMat &dst,
extra_extrapolation ? "EXTRA_EXTRAPOLATION" : "NO_EXTRA_EXTRAPOLATION",
isIsolatedBorder ? "BORDER_ISOLATED" : "NO_BORDER_ISOLATED");
size_t gt[3] = {divUp(dst.cols, BLOCK_SIZE - (ksize.width - 1)) * BLOCK_SIZE, divUp(dst.rows, BLOCK_SIZE_Y), 1}, lt[3] = {BLOCK_SIZE, 1, 1};
openCLExecuteKernel(src.clCxt, &filtering_boxFilter, "boxFilter", gt, lt, args, -1, -1, build_options);
size_t lt[3] = {BLOCK_SIZE, 1, 1};
size_t gt[3] = {divUp(dst.cols, BLOCK_SIZE - (ksize.width - 1)) * BLOCK_SIZE, divUp(dst.rows, BLOCK_SIZE_Y), 1};
cl_kernel kernel = openCLGetKernelFromSource(src.clCxt, &filtering_boxFilter, "boxFilter", -1, -1, build_options);
size_t kernelWorkGroupSize;
openCLSafeCall(clGetKernelWorkGroupInfo(kernel, getClDeviceID(src.clCxt),
CL_KERNEL_WORK_GROUP_SIZE, sizeof(size_t), &kernelWorkGroupSize, 0));
if (lt[0] > kernelWorkGroupSize)
{
clReleaseKernel(kernel);
CV_Assert(BLOCK_SIZE > kernelWorkGroupSize);
tryWorkItems = kernelWorkGroupSize;
continue;
}
openCLExecuteKernel(src.clCxt, kernel, gt, lt, args); // kernel will be released here
} while (false);
}
Ptr<BaseFilter_GPU> cv::ocl::getBoxFilter_GPU(int /*srcType*/, int /*dstType*/,