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ocl: split initialization.cpp into 3 files: context, operations, programcache

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This commit is contained in:
Alexander Alekhin 2013-09-20 19:19:52 +04:00
parent 8e75947a7d
commit e8d9ed8955
36 changed files with 1699 additions and 1534 deletions
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2
modules/nonfree/src/surf.ocl.cpp
View File

@ -74,7 +74,7 @@ namespace cv
}
cl_kernel kernel;
kernel = openCLGetKernelFromSource(clCxt, source, kernelName, optBufPtr);
size_t wave_size = queryDeviceInfo<WAVEFRONT_SIZE, size_t>(kernel);
size_t wave_size = queryWaveFrontSize(kernel);
CV_Assert(clReleaseKernel(kernel) == CL_SUCCESS);
sprintf(optBufPtr, "-D WAVE_SIZE=%d", static_cast<int>(wave_size));
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, channels, depth, optBufPtr);

148
modules/ocl/include/opencv2/ocl/ocl.hpp
View File

@ -57,8 +57,7 @@ namespace cv
{
namespace ocl
{
using std::auto_ptr;
enum
enum DeviceType
{
CVCL_DEVICE_TYPE_DEFAULT = (1 << 0),
CVCL_DEVICE_TYPE_CPU = (1 << 1),
@ -93,77 +92,113 @@ namespace cv
//return -1 if the target type is unsupported, otherwise return 0
CV_EXPORTS int setDevMemType(DevMemRW rw_type = DEVICE_MEM_R_W, DevMemType mem_type = DEVICE_MEM_DEFAULT);
//this class contains ocl runtime information
class CV_EXPORTS Info
// these classes contain OpenCL runtime information
struct PlatformInfo;
struct DeviceInfo
{
public:
struct Impl;
Impl *impl;
int _id; // reserved, don't use it
Info();
Info(const Info &m);
~Info();
void release();
Info &operator = (const Info &m);
std::vector<string> DeviceName;
DeviceType deviceType;
std::string deviceProfile;
std::string deviceVersion;
std::string deviceName;
std::string deviceVendor;
int deviceVendorId;
std::string deviceDriverVersion;
std::string deviceExtensions;
size_t maxWorkGroupSize;
std::vector<size_t> maxWorkItemSizes;
int maxComputeUnits;
size_t localMemorySize;
int deviceVersionMajor;
int deviceVersionMinor;
bool haveDoubleSupport;
bool isUnifiedMemory; // 1 means integrated GPU, otherwise this value is 0
std::string compilationExtraOptions;
const PlatformInfo* platform;
DeviceInfo();
};
struct PlatformInfo
{
int _id; // reserved, don't use it
std::string platformProfile;
std::string platformVersion;
std::string platformName;
std::string platformVendor;
std::string platformExtensons;
int platformVersionMajor;
int platformVersionMinor;
std::vector<const DeviceInfo*> devices;
PlatformInfo();
};
//////////////////////////////// Initialization & Info ////////////////////////
//this function may be obsoleted
//CV_EXPORTS cl_device_id getDevice();
//the function must be called before any other cv::ocl::functions, it initialize ocl runtime
//each Info relates to an OpenCL platform
//there is one or more devices in each platform, each one has a separate name
CV_EXPORTS int getDevice(std::vector<Info> &oclinfo, int devicetype = CVCL_DEVICE_TYPE_GPU);
typedef std::vector<const PlatformInfo*> PlatformsInfo;
//set device you want to use, optional function after getDevice be called
//the devnum is the index of the selected device in DeviceName vector of INfo
CV_EXPORTS void setDevice(Info &oclinfo, int devnum = 0);
CV_EXPORTS int getOpenCLPlatforms(PlatformsInfo& platforms);
//The two functions below enable other opencl program to use ocl module's cl_context and cl_command_queue
//returns cl_context *
CV_EXPORTS void* getoclContext();
//returns cl_command_queue *
CV_EXPORTS void* getoclCommandQueue();
typedef std::vector<const DeviceInfo*> DevicesInfo;
//explicit call clFinish. The global command queue will be used.
CV_EXPORTS void finish();
CV_EXPORTS int getOpenCLDevices(DevicesInfo& devices, int deviceType = CVCL_DEVICE_TYPE_GPU,
const PlatformInfo* platform = NULL);
//this function enable ocl module to use customized cl_context and cl_command_queue
//getDevice also need to be called before this function
CV_EXPORTS void setDeviceEx(Info &oclinfo, void *ctx, void *qu, int devnum = 0);
//returns true when global OpenCL context is initialized
CV_EXPORTS bool initialized();
// set device you want to use
CV_EXPORTS void setDevice(const DeviceInfo* info);
//////////////////////////////// Error handling ////////////////////////
CV_EXPORTS void error(const char *error_string, const char *file, const int line, const char *func);
//////////////////////////////// OpenCL context ////////////////////////
//This is a global singleton class used to represent a OpenCL context.
enum FEATURE_TYPE
{
FEATURE_CL_DOUBLE = 1,
FEATURE_CL_UNIFIED_MEM,
FEATURE_CL_VER_1_2
};
// Represents OpenCL context, interface
class CV_EXPORTS Context
{
protected:
Context();
friend class auto_ptr<Context>;
friend bool initialized();
private:
static auto_ptr<Context> clCxt;
static int val;
Context() { }
~Context() { }
public:
~Context();
void release();
Info::Impl* impl;
static Context* getContext();
static void setContext(Info &oclinfo);
enum {CL_DOUBLE, CL_UNIFIED_MEM, CL_VER_1_2};
bool supportsFeature(int ftype) const;
size_t computeUnits() const;
void* oclContext();
void* oclCommandQueue();
bool supportsFeature(FEATURE_TYPE featureType) const;
const DeviceInfo& getDeviceInfo() const;
const void* getOpenCLContextPtr() const;
const void* getOpenCLCommandQueuePtr() const;
const void* getOpenCLDeviceIDPtr() const;
};
inline const void *getClContextPtr()
{
return Context::getContext()->getOpenCLContextPtr();
}
inline const void *getClCommandQueuePtr()
{
return Context::getContext()->getOpenCLCommandQueuePtr();
}
bool CV_EXPORTS supportsFeature(FEATURE_TYPE featureType);
void CV_EXPORTS finish();
//! Calls a kernel, by string. Pass globalThreads = NULL, and cleanUp = true, to finally clean-up without executing.
CV_EXPORTS double openCLExecuteKernelInterop(Context *clCxt ,
const char **source, string kernelName,
@ -384,7 +419,7 @@ namespace cv
uchar *dataend;
//! OpenCL context associated with the oclMat object.
Context *clCxt;
Context *clCxt; // TODO clCtx
//add offset for handle ROI, calculated in byte
int offset;
//add wholerows and wholecols for the whole matrix, datastart and dataend are no longer used
@ -1879,11 +1914,6 @@ namespace cv
oclMat temp5;
};
static inline size_t divUp(size_t total, size_t grain)
{
return (total + grain - 1) / grain;
}
/*!***************K Nearest Neighbour*************!*/
class CV_EXPORTS KNearestNeighbour: public CvKNearest
{

228
modules/ocl/include/opencv2/ocl/private/util.hpp
View File

@ -52,120 +52,138 @@
namespace cv
{
namespace ocl
namespace ocl
{
inline cl_device_id getClDeviceID(const Context *ctx)
{
return *(cl_device_id*)(ctx->getOpenCLDeviceIDPtr());
}
inline cl_context getClContext(const Context *ctx)
{
return *(cl_context*)(ctx->getOpenCLContextPtr());
}
inline cl_command_queue getClCommandQueue(const Context *ctx)
{
return *(cl_command_queue*)(ctx->getOpenCLCommandQueuePtr());
}
enum openCLMemcpyKind
{
clMemcpyHostToDevice = 0,
clMemcpyDeviceToHost,
clMemcpyDeviceToDevice
};
///////////////////////////OpenCL call wrappers////////////////////////////
void CV_EXPORTS openCLMallocPitch(Context *clCxt, void **dev_ptr, size_t *pitch,
size_t widthInBytes, size_t height);
void CV_EXPORTS openCLMallocPitchEx(Context *clCxt, void **dev_ptr, size_t *pitch,
size_t widthInBytes, size_t height, DevMemRW rw_type, DevMemType mem_type);
void CV_EXPORTS openCLMemcpy2D(Context *clCxt, void *dst, size_t dpitch,
const void *src, size_t spitch,
size_t width, size_t height, openCLMemcpyKind kind, int channels = -1);
void CV_EXPORTS openCLCopyBuffer2D(Context *clCxt, void *dst, size_t dpitch, int dst_offset,
const void *src, size_t spitch,
size_t width, size_t height, int src_offset);
void CV_EXPORTS openCLFree(void *devPtr);
cl_mem CV_EXPORTS openCLCreateBuffer(Context *clCxt, size_t flag, size_t size);
void CV_EXPORTS openCLReadBuffer(Context *clCxt, cl_mem dst_buffer, void *host_buffer, size_t size);
cl_kernel CV_EXPORTS openCLGetKernelFromSource(const Context *clCxt,
const char **source, std::string kernelName);
cl_kernel CV_EXPORTS openCLGetKernelFromSource(const Context *clCxt,
const char **source, std::string kernelName, const char *build_options);
void CV_EXPORTS openCLVerifyKernel(const Context *clCxt, cl_kernel kernel, size_t *localThreads);
void CV_EXPORTS openCLExecuteKernel(Context *clCxt , const char **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);
void CV_EXPORTS openCLExecuteKernel_(Context *clCxt , const char **source, std::string kernelName,
size_t globalThreads[3], size_t localThreads[3],
std::vector< std::pair<size_t, const void *> > &args, int channels, int depth, const char *build_options);
void CV_EXPORTS openCLExecuteKernel(Context *clCxt , const char **source, std::string kernelName, size_t globalThreads[3],
size_t localThreads[3], std::vector< std::pair<size_t, const void *> > &args, int channels, int depth);
void CV_EXPORTS openCLExecuteKernel(Context *clCxt , const char **source, std::string kernelName, size_t globalThreads[3],
size_t localThreads[3], std::vector< std::pair<size_t, const void *> > &args, int channels,
int depth, const char *build_options);
cl_mem CV_EXPORTS load_constant(cl_context context, cl_command_queue command_queue, const void *value,
const size_t size);
cl_mem CV_EXPORTS openCLMalloc(cl_context clCxt, size_t size, cl_mem_flags flags, void *host_ptr);
int CV_EXPORTS savetofile(const Context *clcxt, cl_program &program, const char *fileName);
enum FLUSH_MODE
{
CLFINISH = 0,
CLFLUSH,
DISABLE
};
void CV_EXPORTS openCLExecuteKernel2(Context *clCxt , const char **source, std::string kernelName, size_t globalThreads[3],
size_t localThreads[3], std::vector< std::pair<size_t, const void *> > &args, int channels, int depth, FLUSH_MODE finish_mode = DISABLE);
void CV_EXPORTS openCLExecuteKernel2(Context *clCxt , const char **source, std::string kernelName, size_t globalThreads[3],
size_t localThreads[3], std::vector< std::pair<size_t, const void *> > &args, int channels,
int depth, char *build_options, FLUSH_MODE finish_mode = DISABLE);
// bind oclMat to OpenCL image textures
// note:
// 1. there is no memory management. User need to explicitly release the resource
// 2. for faster clamping, there is no buffer padding for the constructed texture
cl_mem CV_EXPORTS bindTexture(const oclMat &mat);
void CV_EXPORTS releaseTexture(cl_mem& texture);
//Represents an image texture object
class CV_EXPORTS TextureCL
{
public:
TextureCL(cl_mem tex, int r, int c, int t)
: tex_(tex), rows(r), cols(c), type(t) {}
~TextureCL()
{
enum openCLMemcpyKind
{
clMemcpyHostToDevice = 0,
clMemcpyDeviceToHost,
clMemcpyDeviceToDevice
};
///////////////////////////OpenCL call wrappers////////////////////////////
void CV_EXPORTS openCLMallocPitch(Context *clCxt, void **dev_ptr, size_t *pitch,
size_t widthInBytes, size_t height);
void CV_EXPORTS openCLMallocPitchEx(Context *clCxt, void **dev_ptr, size_t *pitch,
size_t widthInBytes, size_t height, DevMemRW rw_type, DevMemType mem_type);
void CV_EXPORTS openCLMemcpy2D(Context *clCxt, void *dst, size_t dpitch,
const void *src, size_t spitch,
size_t width, size_t height, openCLMemcpyKind kind, int channels = -1);
void CV_EXPORTS openCLCopyBuffer2D(Context *clCxt, void *dst, size_t dpitch, int dst_offset,
const void *src, size_t spitch,
size_t width, size_t height, int src_offset);
void CV_EXPORTS openCLFree(void *devPtr);
cl_mem CV_EXPORTS openCLCreateBuffer(Context *clCxt, size_t flag, size_t size);
void CV_EXPORTS openCLReadBuffer(Context *clCxt, cl_mem dst_buffer, void *host_buffer, size_t size);
cl_kernel CV_EXPORTS openCLGetKernelFromSource(const Context *clCxt,
const char **source, std::string kernelName);
cl_kernel CV_EXPORTS openCLGetKernelFromSource(const Context *clCxt,
const char **source, std::string kernelName, const char *build_options);
void CV_EXPORTS openCLVerifyKernel(const Context *clCxt, cl_kernel kernel, size_t *localThreads);
void CV_EXPORTS openCLExecuteKernel(Context *clCxt , const char **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);
void CV_EXPORTS openCLExecuteKernel_(Context *clCxt , const char **source, std::string kernelName,
size_t globalThreads[3], size_t localThreads[3],
std::vector< std::pair<size_t, const void *> > &args, int channels, int depth, const char *build_options);
void CV_EXPORTS openCLExecuteKernel(Context *clCxt , const char **source, std::string kernelName, size_t globalThreads[3],
size_t localThreads[3], std::vector< std::pair<size_t, const void *> > &args, int channels, int depth);
void CV_EXPORTS openCLExecuteKernel(Context *clCxt , const char **source, std::string kernelName, size_t globalThreads[3],
size_t localThreads[3], std::vector< std::pair<size_t, const void *> > &args, int channels,
int depth, const char *build_options);
openCLFree(tex_);
}
operator cl_mem()
{
return tex_;
}
cl_mem const tex_;
const int rows;
const int cols;
const int type;
private:
//disable assignment
void operator=(const TextureCL&);
};
// bind oclMat to OpenCL image textures and retunrs an TextureCL object
// note:
// for faster clamping, there is no buffer padding for the constructed texture
Ptr<TextureCL> CV_EXPORTS bindTexturePtr(const oclMat &mat);
cl_mem CV_EXPORTS load_constant(cl_context context, cl_command_queue command_queue, const void *value,
const size_t size);
// returns whether the current context supports image2d_t format or not
bool CV_EXPORTS support_image2d(Context *clCxt = Context::getContext());
cl_mem CV_EXPORTS openCLMalloc(cl_context clCxt, size_t size, cl_mem_flags flags, void *host_ptr);
bool CV_EXPORTS isCpuDevice();
int CV_EXPORTS savetofile(const Context *clcxt, cl_program &program, const char *fileName);
size_t CV_EXPORTS queryWaveFrontSize(cl_kernel kernel);
enum FLUSH_MODE
{
CLFINISH = 0,
CLFLUSH,
DISABLE
};
void CV_EXPORTS openCLExecuteKernel2(Context *clCxt , const char **source, std::string kernelName, size_t globalThreads[3],
size_t localThreads[3], std::vector< std::pair<size_t, const void *> > &args, int channels, int depth, FLUSH_MODE finish_mode = DISABLE);
void CV_EXPORTS openCLExecuteKernel2(Context *clCxt , const char **source, std::string kernelName, size_t globalThreads[3],
size_t localThreads[3], std::vector< std::pair<size_t, const void *> > &args, int channels,
int depth, char *build_options, FLUSH_MODE finish_mode = DISABLE);
// bind oclMat to OpenCL image textures
// note:
// 1. there is no memory management. User need to explicitly release the resource
// 2. for faster clamping, there is no buffer padding for the constructed texture
cl_mem CV_EXPORTS bindTexture(const oclMat &mat);
void CV_EXPORTS releaseTexture(cl_mem& texture);
//Represents an image texture object
class CV_EXPORTS TextureCL
{
public:
TextureCL(cl_mem tex, int r, int c, int t)
: tex_(tex), rows(r), cols(c), type(t) {}
~TextureCL()
{
openCLFree(tex_);
}
operator cl_mem()
{
return tex_;
}
cl_mem const tex_;
const int rows;
const int cols;
const int type;
private:
//disable assignment
void operator=(const TextureCL&);
};
// bind oclMat to OpenCL image textures and retunrs an TextureCL object
// note:
// for faster clamping, there is no buffer padding for the constructed texture
Ptr<TextureCL> CV_EXPORTS bindTexturePtr(const oclMat &mat);
inline size_t divUp(size_t total, size_t grain)
{
return (total + grain - 1) / grain;
}
// returns whether the current context supports image2d_t format or not
bool CV_EXPORTS support_image2d(Context *clCxt = Context::getContext());
// the enums are used to query device information
// currently only support wavefront size queries
enum DEVICE_INFO
{
WAVEFRONT_SIZE, //in AMD speak
IS_CPU_DEVICE //check if the device is CPU
};
template<DEVICE_INFO _it, typename _ty>
_ty queryDeviceInfo(cl_kernel kernel = NULL);
template<>
int CV_EXPORTS queryDeviceInfo<WAVEFRONT_SIZE, int>(cl_kernel kernel);
template<>
size_t CV_EXPORTS queryDeviceInfo<WAVEFRONT_SIZE, size_t>(cl_kernel kernel);
template<>
bool CV_EXPORTS queryDeviceInfo<IS_CPU_DEVICE, bool>(cl_kernel kernel);
unsigned long CV_EXPORTS queryLocalMemInfo();
}//namespace ocl
inline size_t roundUp(size_t sz, size_t n)
{
// we don't assume that n is a power of 2 (see alignSize)
// equal to divUp(sz, n) * n
size_t t = sz + n - 1;
size_t rem = t % n;
size_t result = t - rem;
return result;
}
}//namespace ocl
}//namespace cv
#endif //__OPENCV_OCL_PRIVATE_UTIL__

28
modules/ocl/perf/main.cpp
View File

@ -56,7 +56,7 @@ int main(int argc, char ** argv)
const char * keys =
"{ h | help | false | print help message }"
"{ t | type | gpu | set device type:cpu or gpu}"
"{ p | platform | 0 | set platform id }"
"{ p | platform | -1 | set platform id }"
"{ d | device | 0 | set device id }";
CommandLineParser cmd(argc, argv, keys);
@ -68,28 +68,34 @@ int main(int argc, char ** argv)
}
string type = cmd.get<string>("type");
unsigned int pid = cmd.get<unsigned int>("platform");
int pid = cmd.get<int>("platform");
int device = cmd.get<int>("device");
int flag = type == "cpu" ? cv::ocl::CVCL_DEVICE_TYPE_CPU :
cv::ocl::CVCL_DEVICE_TYPE_GPU;
std::vector<cv::ocl::Info> oclinfo;
int devnums = cv::ocl::getDevice(oclinfo, flag);
if (devnums <= device || device < 0)
cv::ocl::PlatformsInfo platformsInfo;
cv::ocl::getOpenCLPlatforms(platformsInfo);
if (pid >= (int)platformsInfo.size())
{
std::cout << "device invalid\n";
return -1;
std::cout << "platform is invalid\n";
return 1;
}
if (pid >= oclinfo.size())
cv::ocl::DevicesInfo devicesInfo;
int devnums = cv::ocl::getOpenCLDevices(devicesInfo, flag, (pid < 0) ? NULL : platformsInfo[pid]);
if (device < 0 || device >= devnums)
{
std::cout << "platform invalid\n";
return -1;
std::cout << "device/platform invalid\n";
return 1;
}
cv::ocl::setDevice(oclinfo[pid], device);
cv::ocl::setDevice(devicesInfo[device]);
cv::ocl::setBinaryDiskCache(cv::ocl::CACHE_UPDATE);
cout << "Device type:" << type << endl
<< "Platform name:" << devicesInfo[device]->platform->platformName << endl
<< "Device name:" << devicesInfo[device]->deviceName << endl;
CV_PERF_TEST_MAIN_INTERNALS(ocl, impls)
}

122
modules/ocl/src/arithm.cpp
View File

@ -51,50 +51,10 @@
//M*/
#include "precomp.hpp"
#include <iomanip>
#include "opencl_kernels.hpp"
using namespace cv;
using namespace cv::ocl;
using namespace std;
namespace cv
{
namespace ocl
{
//////////////////////////////// OpenCL kernel strings /////////////////////
extern const char *arithm_absdiff_nonsaturate;
extern const char *arithm_nonzero;
extern const char *arithm_sum;
extern const char *arithm_minMax;
extern const char *arithm_minMaxLoc;
extern const char *arithm_minMaxLoc_mask;
extern const char *arithm_LUT;
extern const char *arithm_add;
extern const char *arithm_add_mask;
extern const char *arithm_add_scalar;
extern const char *arithm_add_scalar_mask;
extern const char *arithm_bitwise_binary;
extern const char *arithm_bitwise_binary_mask;
extern const char *arithm_bitwise_binary_scalar;
extern const char *arithm_bitwise_binary_scalar_mask;
extern const char *arithm_bitwise_not;
extern const char *arithm_compare;
extern const char *arithm_transpose;
extern const char *arithm_flip;
extern const char *arithm_flip_rc;
extern const char *arithm_magnitude;
extern const char *arithm_cartToPolar;
extern const char *arithm_polarToCart;
extern const char *arithm_exp;
extern const char *arithm_log;
extern const char *arithm_addWeighted;
extern const char *arithm_phase;
extern const char *arithm_pow;
extern const char *arithm_setidentity;
}
}
//////////////////////////////////////////////////////////////////////////////
/////////////////////// add subtract multiply divide /////////////////////////
@ -106,7 +66,7 @@ static void arithmetic_run_generic(const oclMat &src1, const oclMat &src2, const
oclMat &dst, int op_type, bool use_scalar = false)
{
Context *clCxt = src1.clCxt;
bool hasDouble = clCxt->supportsFeature(Context::CL_DOUBLE);
bool hasDouble = clCxt->supportsFeature(FEATURE_CL_DOUBLE);
if (!hasDouble && (src1.depth() == CV_64F || src2.depth() == CV_64F || dst.depth() == CV_64F))
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double\r\n");
@ -264,7 +224,7 @@ void cv::ocl::absdiff(const oclMat &src1, const Scalar &src2, oclMat &dst)
//////////////////////////////////////////////////////////////////////////////
static void compare_run(const oclMat &src1, const oclMat &src2, oclMat &dst, int cmpOp,
string kernelName, const char **kernelString)
string kernelName, const cv::ocl::ProgramEntry* source)
{
CV_Assert(src1.type() == src2.type());
dst.create(src1.size(), CV_8UC1);
@ -295,13 +255,13 @@ static void compare_run(const oclMat &src1, const oclMat &src2, oclMat &dst, int
args.push_back( make_pair( sizeof(cl_int), (void *)&src1.cols ));
args.push_back( make_pair( sizeof(cl_int), (void *)&src1.rows ));
openCLExecuteKernel(clCxt, kernelString, kernelName, globalThreads, localThreads,
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads,
args, -1, -1, buildOptions.c_str());
}
void cv::ocl::compare(const oclMat &src1, const oclMat &src2, oclMat &dst , int cmpOp)
{
if (!src1.clCxt->supportsFeature(Context::CL_DOUBLE) && src1.depth() == CV_64F)
if (!src1.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src1.depth() == CV_64F)
{
cout << "Selected device do not support double" << endl;
return;
@ -358,7 +318,7 @@ Scalar arithmetic_sum(const oclMat &src, int type, int ddepth)
{
CV_Assert(src.step % src.elemSize() == 0);
size_t groupnum = src.clCxt->computeUnits();
size_t groupnum = src.clCxt->getDeviceInfo().maxComputeUnits;
CV_Assert(groupnum != 0);
int dbsize = groupnum * src.oclchannels();
@ -385,7 +345,7 @@ typedef Scalar (*sumFunc)(const oclMat &src, int type, int ddepth);
Scalar cv::ocl::sum(const oclMat &src)
{
if (!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.depth() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double");
}
@ -396,7 +356,7 @@ Scalar cv::ocl::sum(const oclMat &src)
arithmetic_sum<double>
};
bool hasDouble = src.clCxt->supportsFeature(Context::CL_DOUBLE);
bool hasDouble = src.clCxt->supportsFeature(FEATURE_CL_DOUBLE);
int ddepth = std::max(src.depth(), CV_32S);
if (!hasDouble && ddepth == CV_64F)
ddepth = CV_32F;
@ -407,7 +367,7 @@ Scalar cv::ocl::sum(const oclMat &src)
Scalar cv::ocl::absSum(const oclMat &src)
{
if (!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.depth() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double");
}
@ -418,7 +378,7 @@ Scalar cv::ocl::absSum(const oclMat &src)
arithmetic_sum<double>
};
bool hasDouble = src.clCxt->supportsFeature(Context::CL_DOUBLE);
bool hasDouble = src.clCxt->supportsFeature(FEATURE_CL_DOUBLE);
int ddepth = std::max(src.depth(), CV_32S);
if (!hasDouble && ddepth == CV_64F)
ddepth = CV_32F;
@ -429,7 +389,7 @@ Scalar cv::ocl::absSum(const oclMat &src)
Scalar cv::ocl::sqrSum(const oclMat &src)
{
if (!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.depth() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double");
}
@ -440,7 +400,7 @@ Scalar cv::ocl::sqrSum(const oclMat &src)
arithmetic_sum<double>
};
bool hasDouble = src.clCxt->supportsFeature(Context::CL_DOUBLE);
bool hasDouble = src.clCxt->supportsFeature(FEATURE_CL_DOUBLE);
int ddepth = src.depth() <= CV_32S ? CV_32S : (hasDouble ? CV_64F : CV_32F);
sumFunc func = functab[ddepth - CV_32S];
@ -524,7 +484,7 @@ template <typename T, typename WT>
void arithmetic_minMax(const oclMat &src, double *minVal, double *maxVal,
const oclMat &mask, oclMat &buf)
{
size_t groupnum = src.clCxt->computeUnits();
size_t groupnum = src.clCxt->getDeviceInfo().maxComputeUnits;
CV_Assert(groupnum != 0);
int dbsize = groupnum * 2 * src.elemSize();
@ -566,7 +526,7 @@ void cv::ocl::minMax_buf(const oclMat &src, double *minVal, double *maxVal, cons
if (minVal == NULL && maxVal == NULL)
return;
if (!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.depth() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double");
}
@ -699,7 +659,7 @@ double cv::ocl::norm(const oclMat &src1, const oclMat &src2, int normType)
static void arithmetic_flip_rows_run(const oclMat &src, oclMat &dst, string kernelName)
{
if (!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.type() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.type() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double\r\n");
return;
@ -746,7 +706,7 @@ static void arithmetic_flip_rows_run(const oclMat &src, oclMat &dst, string kern
static void arithmetic_flip_cols_run(const oclMat &src, oclMat &dst, string kernelName, bool isVertical)
{
if (!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.type() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.type() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double\r\n");
return;
@ -792,9 +752,9 @@ static void arithmetic_flip_cols_run(const oclMat &src, oclMat &dst, string kern
args.push_back( make_pair( sizeof(cl_int), (void *)&dst_step1 ));
const char **kernelString = isVertical ? &arithm_flip_rc : &arithm_flip;
const cv::ocl::ProgramEntry* source = isVertical ? &arithm_flip_rc : &arithm_flip;
openCLExecuteKernel(clCxt, kernelString, kernelName, globalThreads, localThreads, args, src.oclchannels(), depth);
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, src.oclchannels(), depth);
}
void cv::ocl::flip(const oclMat &src, oclMat &dst, int flipCode)
@ -860,10 +820,10 @@ void cv::ocl::LUT(const oclMat &src, const oclMat &lut, oclMat &dst)
//////////////////////////////// exp log /////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////
static void arithmetic_exp_log_run(const oclMat &src, oclMat &dst, string kernelName, const char **kernelString)
static void arithmetic_exp_log_run(const oclMat &src, oclMat &dst, string kernelName, const cv::ocl::ProgramEntry* source)
{
Context *clCxt = src.clCxt;
if (!clCxt->supportsFeature(Context::CL_DOUBLE) && src.depth() == CV_64F)
if (!clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double\r\n");
return;
@ -893,7 +853,7 @@ static void arithmetic_exp_log_run(const oclMat &src, oclMat &dst, string kernel
args.push_back( make_pair( sizeof(cl_int), (void *)&srcstep1 ));
args.push_back( make_pair( sizeof(cl_int), (void *)&dststep1 ));
openCLExecuteKernel(clCxt, kernelString, kernelName, globalThreads, localThreads,
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads,
args, src.oclchannels(), -1, buildOptions.c_str());
}
@ -913,7 +873,7 @@ void cv::ocl::log(const oclMat &src, oclMat &dst)
static void arithmetic_magnitude_phase_run(const oclMat &src1, const oclMat &src2, oclMat &dst, string kernelName)
{
if (!src1.clCxt->supportsFeature(Context::CL_DOUBLE) && src1.type() == CV_64F)
if (!src1.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src1.type() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double\r\n");
return;
@ -955,9 +915,9 @@ void cv::ocl::magnitude(const oclMat &src1, const oclMat &src2, oclMat &dst)
arithmetic_magnitude_phase_run(src1, src2, dst, "arithm_magnitude");
}
static void arithmetic_phase_run(const oclMat &src1, const oclMat &src2, oclMat &dst, string kernelName, const char **kernelString)
static void arithmetic_phase_run(const oclMat &src1, const oclMat &src2, oclMat &dst, string kernelName, const cv::ocl::ProgramEntry* source)
{
if (!src1.clCxt->supportsFeature(Context::CL_DOUBLE) && src1.type() == CV_64F)
if (!src1.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src1.type() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double\r\n");
return;
@ -985,7 +945,7 @@ static void arithmetic_phase_run(const oclMat &src1, const oclMat &src2, oclMat
args.push_back( make_pair( sizeof(cl_int), (void *)&cols1 ));
args.push_back( make_pair( sizeof(cl_int), (void *)&dst.rows ));
openCLExecuteKernel(clCxt, kernelString, kernelName, globalThreads, localThreads, args, -1, depth);
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, -1, depth);
}
void cv::ocl::phase(const oclMat &x, const oclMat &y, oclMat &Angle, bool angleInDegrees)
@ -1004,7 +964,7 @@ void cv::ocl::phase(const oclMat &x, const oclMat &y, oclMat &Angle, bool angleI
static void arithmetic_cartToPolar_run(const oclMat &src1, const oclMat &src2, oclMat &dst_mag, oclMat &dst_cart,
string kernelName, bool angleInDegrees)
{
if (!src1.clCxt->supportsFeature(Context::CL_DOUBLE) && src1.type() == CV_64F)
if (!src1.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src1.type() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double\r\n");
return;
@ -1057,7 +1017,7 @@ void cv::ocl::cartToPolar(const oclMat &x, const oclMat &y, oclMat &mag, oclMat
static void arithmetic_ptc_run(const oclMat &src1, const oclMat &src2, oclMat &dst1, oclMat &dst2, bool angleInDegrees,
string kernelName)
{
if (!src1.clCxt->supportsFeature(Context::CL_DOUBLE) && src1.type() == CV_64F)
if (!src1.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src1.type() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double\r\n");
return;
@ -1176,7 +1136,7 @@ void arithmetic_minMaxLoc(const oclMat &src, double *minVal, double *maxVal,
Point *minLoc, Point *maxLoc, const oclMat &mask)
{
CV_Assert(src.oclchannels() == 1);
size_t groupnum = src.clCxt->computeUnits();
size_t groupnum = src.clCxt->getDeviceInfo().maxComputeUnits;
CV_Assert(groupnum != 0);
int minloc = -1 , maxloc = -1;
int vlen = 4, dbsize = groupnum * vlen * 4 * sizeof(T) ;
@ -1238,7 +1198,7 @@ typedef void (*minMaxLocFunc)(const oclMat &src, double *minVal, double *maxVal,
void cv::ocl::minMaxLoc(const oclMat &src, double *minVal, double *maxVal,
Point *minLoc, Point *maxLoc, const oclMat &mask)
{
if (!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.depth() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double");
return;
@ -1251,7 +1211,7 @@ void cv::ocl::minMaxLoc(const oclMat &src, double *minVal, double *maxVal,
};
minMaxLocFunc func;
func = functab[(int)src.clCxt->supportsFeature(Context::CL_DOUBLE)];
func = functab[(int)src.clCxt->supportsFeature(FEATURE_CL_DOUBLE)];
func(src, minVal, maxVal, minLoc, maxLoc, mask);
}
@ -1296,7 +1256,7 @@ int cv::ocl::countNonZero(const oclMat &src)
CV_Assert(src.channels() == 1);
Context *clCxt = src.clCxt;
if (!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.depth() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "selected device doesn't support double");
}
@ -1327,7 +1287,7 @@ int cv::ocl::countNonZero(const oclMat &src)
////////////////////////////////bitwise_op////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////
static void bitwise_unary_run(const oclMat &src1, oclMat &dst, string kernelName, const char **kernelString)
static void bitwise_unary_run(const oclMat &src1, oclMat &dst, string kernelName, const cv::ocl::ProgramEntry* source)
{
dst.create(src1.size(), src1.type());
@ -1361,7 +1321,7 @@ static void bitwise_unary_run(const oclMat &src1, oclMat &dst, string kernelName
args.push_back( make_pair( sizeof(cl_int), (void *)&cols ));
args.push_back( make_pair( sizeof(cl_int), (void *)&dst_step1 ));
openCLExecuteKernel(clCxt, kernelString, kernelName, globalThreads, localThreads, args, -1, depth);
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, -1, depth);
}
enum { AND = 0, OR, XOR };
@ -1370,7 +1330,7 @@ static void bitwise_binary_run(const oclMat &src1, const oclMat &src2, const Sca
oclMat &dst, int operationType)
{
Context *clCxt = src1.clCxt;
if (!clCxt->supportsFeature(Context::CL_DOUBLE) && src1.depth() == CV_64F)
if (!clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src1.depth() == CV_64F)
{
cout << "Selected device does not support double" << endl;
return;
@ -1442,7 +1402,7 @@ static void bitwise_binary_run(const oclMat &src1, const oclMat &src2, const Sca
void cv::ocl::bitwise_not(const oclMat &src, oclMat &dst)
{
if (!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.type() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.type() == CV_64F)
{
cout << "Selected device does not support double" << endl;
return;
@ -1571,7 +1531,7 @@ oclMatExpr::operator oclMat() const
static void transpose_run(const oclMat &src, oclMat &dst, string kernelName, bool inplace = false)
{
Context *clCxt = src.clCxt;
if (!clCxt->supportsFeature(Context::CL_DOUBLE) && src.depth() == CV_64F)
if (!clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double\r\n");
return;
@ -1623,7 +1583,7 @@ void cv::ocl::transpose(const oclMat &src, oclMat &dst)
void cv::ocl::addWeighted(const oclMat &src1, double alpha, const oclMat &src2, double beta, double gama, oclMat &dst)
{
Context *clCxt = src1.clCxt;
bool hasDouble = clCxt->supportsFeature(Context::CL_DOUBLE);
bool hasDouble = clCxt->supportsFeature(FEATURE_CL_DOUBLE);
if (!hasDouble && src1.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device doesn't support double\r\n");
@ -1688,7 +1648,7 @@ void cv::ocl::addWeighted(const oclMat &src1, double alpha, const oclMat &src2,
/////////////////////////////////// Pow //////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////
static void arithmetic_pow_run(const oclMat &src1, double p, oclMat &dst, string kernelName, const char **kernelString)
static void arithmetic_pow_run(const oclMat &src1, double p, oclMat &dst, string kernelName, const cv::ocl::ProgramEntry* source)
{
CV_Assert(src1.cols == dst.cols && src1.rows == dst.rows);
CV_Assert(src1.type() == dst.type());
@ -1718,17 +1678,17 @@ static void arithmetic_pow_run(const oclMat &src1, double p, oclMat &dst, string
args.push_back( make_pair( sizeof(cl_int), (void *)&dst_step1 ));
float pf = static_cast<float>(p);
if (!src1.clCxt->supportsFeature(Context::CL_DOUBLE))
if (!src1.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
args.push_back( make_pair( sizeof(cl_float), (void *)&pf ));
else
args.push_back( make_pair( sizeof(cl_double), (void *)&p ));
openCLExecuteKernel(clCxt, kernelString, kernelName, globalThreads, localThreads, args, -1, depth);
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, -1, depth);
}
void cv::ocl::pow(const oclMat &x, double p, oclMat &y)
{
if (!x.clCxt->supportsFeature(Context::CL_DOUBLE) && x.type() == CV_64F)
if (!x.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && x.type() == CV_64F)
{
cout << "Selected device do not support double" << endl;
return;

4
modules/ocl/src/bgfg_mog.cpp
View File

@ -392,7 +392,7 @@ void cv::ocl::device::mog::loadConstants(float Tb, float TB, float Tg, float var
constants->c_tau = tau;
constants->c_shadowVal = shadowVal;
cl_constants = load_constant(*((cl_context*)getoclContext()), *((cl_command_queue*)getoclCommandQueue()),
cl_constants = load_constant(*((cl_context*)getClContextPtr()), *((cl_command_queue*)getClCommandQueuePtr()),
(void *)constants, sizeof(_contant_struct));
}
@ -635,4 +635,4 @@ void cv::ocl::MOG2::release()
mean_.release();
bgmodelUsedModes_.release();
}
}

55
modules/ocl/src/binarycaching.hpp
View File

@ -50,41 +50,36 @@ using namespace std;
using std::cout;
using std::endl;
namespace cv
namespace cv { namespace ocl {
class ProgramCache
{
namespace ocl
{
class ProgramCache
{
protected:
ProgramCache();
friend class auto_ptr<ProgramCache>;
static auto_ptr<ProgramCache> programCache;
protected:
ProgramCache();
~ProgramCache();
friend class std::auto_ptr<ProgramCache>;
public:
static ProgramCache *getProgramCache();
public:
~ProgramCache();
static ProgramCache *getProgramCache()
{
if( NULL == programCache.get())
programCache.reset(new ProgramCache());
return programCache.get();
}
cl_program getProgram(const Context *ctx, const char **source, string kernelName,
const char *build_options);
//lookup the binary given the file name
cl_program progLookup(string srcsign);
void releaseProgram();
protected:
//lookup the binary given the file name
cl_program progLookup(string srcsign);
//add program to the cache
void addProgram(string srcsign, cl_program program);
void releaseProgram();
//add program to the cache
void addProgram(string srcsign, cl_program program);
map <string, cl_program> codeCache;
unsigned int cacheSize;
//The presumed watermark for the cache volume (256MB). Is it enough?
//We may need more delicate algorithms when necessary later.
//Right now, let's just leave it along.
static const unsigned MAX_PROG_CACHE_SIZE = 1024;
};
map <string, cl_program> codeCache;
unsigned int cacheSize;
}//namespace ocl
//The presumed watermark for the cache volume (256MB). Is it enough?
//We may need more delicate algorithms when necessary later.
//Right now, let's just leave it along.
static const unsigned MAX_PROG_CACHE_SIZE = 1024;
};
}//namespace ocl
}//namespace cv

8
modules/ocl/src/brute_force_matcher.cpp
View File

@ -245,7 +245,7 @@ static void matchDispatcher(const oclMat &query, const oclMat &train, const oclM
{
const oclMat zeroMask;
const oclMat &tempMask = mask.data ? mask : zeroMask;
bool is_cpu = queryDeviceInfo<IS_CPU_DEVICE, bool>();
bool is_cpu = isCpuDevice();
if (query.cols <= 64)
{
matchUnrolledCached<16, 64>(query, train, tempMask, trainIdx, distance, distType);
@ -265,7 +265,7 @@ static void matchDispatcher(const oclMat &query, const oclMat *trains, int n, co
{
const oclMat zeroMask;
const oclMat &tempMask = mask.data ? mask : zeroMask;
bool is_cpu = queryDeviceInfo<IS_CPU_DEVICE, bool>();
bool is_cpu = isCpuDevice();
if (query.cols <= 64)
{
matchUnrolledCached<16, 64>(query, trains, n, tempMask, trainIdx, imgIdx, distance, distType);
@ -286,7 +286,7 @@ static void matchDispatcher(const oclMat &query, const oclMat &train, float maxD
{
const oclMat zeroMask;
const oclMat &tempMask = mask.data ? mask : zeroMask;
bool is_cpu = queryDeviceInfo<IS_CPU_DEVICE, bool>();
bool is_cpu = isCpuDevice();
if (query.cols <= 64)
{
matchUnrolledCached<16, 64>(query, train, maxDistance, tempMask, trainIdx, distance, nMatches, distType);
@ -469,7 +469,7 @@ static void calcDistanceDispatcher(const oclMat &query, const oclMat &train, con
static void match2Dispatcher(const oclMat &query, const oclMat &train, const oclMat &mask,
const oclMat &trainIdx, const oclMat &distance, int distType)
{
bool is_cpu = queryDeviceInfo<IS_CPU_DEVICE, bool>();
bool is_cpu = isCpuDevice();
if (query.cols <= 64)
{
knn_matchUnrolledCached<16, 64>(query, train, mask, trainIdx, distance, distType);

8
modules/ocl/src/canny.cpp
View File

@ -98,7 +98,7 @@ void cv::ocl::CannyBuf::create(const Size &image_size, int apperture_size)
{
openCLFree(counter);
}
counter = clCreateBuffer( *((cl_context*)getoclContext()), CL_MEM_COPY_HOST_PTR, sizeof(int), counter_i, &err );
counter = clCreateBuffer( *((cl_context*)getClContextPtr()), CL_MEM_COPY_HOST_PTR, sizeof(int), counter_i, &err );
openCLSafeCall(err);
}
@ -354,7 +354,7 @@ void canny::edgesHysteresisLocal_gpu(oclMat &map, oclMat &st1, void *counter, in
void canny::edgesHysteresisGlobal_gpu(oclMat &map, oclMat &st1, oclMat &st2, void *counter, int rows, int cols)
{
unsigned int count;
openCLSafeCall(clEnqueueReadBuffer(*(cl_command_queue*)getoclCommandQueue(), (cl_mem)counter, 1, 0, sizeof(float), &count, 0, NULL, NULL));
openCLSafeCall(clEnqueueReadBuffer(*(cl_command_queue*)getClCommandQueuePtr(), (cl_mem)counter, 1, 0, sizeof(float), &count, 0, NULL, NULL));
Context *clCxt = map.clCxt;
string kernelName = "edgesHysteresisGlobal";
vector< pair<size_t, const void *> > args;
@ -363,7 +363,7 @@ void canny::edgesHysteresisGlobal_gpu(oclMat &map, oclMat &st1, oclMat &st2, voi
int count_i[1] = {0};
while(count > 0)
{
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)getoclCommandQueue(), (cl_mem)counter, 1, 0, sizeof(int), &count_i, 0, NULL, NULL));
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)getClCommandQueuePtr(), (cl_mem)counter, 1, 0, sizeof(int), &count_i, 0, NULL, NULL));
args.clear();
size_t globalThreads[3] = {std::min(count, 65535u) * 128, divUp(count, 65535), 1};
@ -378,7 +378,7 @@ void canny::edgesHysteresisGlobal_gpu(oclMat &map, oclMat &st1, oclMat &st2, voi
args.push_back( make_pair( sizeof(cl_int), (void *)&map.offset));
openCLExecuteKernel(clCxt, &imgproc_canny, kernelName, globalThreads, localThreads, args, -1, -1);
openCLSafeCall(clEnqueueReadBuffer(*(cl_command_queue*)getoclCommandQueue(), (cl_mem)counter, 1, 0, sizeof(int), &count, 0, NULL, NULL));
openCLSafeCall(clEnqueueReadBuffer(*(cl_command_queue*)getClCommandQueuePtr(), (cl_mem)counter, 1, 0, sizeof(int), &count, 0, NULL, NULL));
std::swap(st1, st2);
}
}

507
modules/ocl/src/cl_context.cpp Normal file
View File

@ -0,0 +1,507 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Guoping Long, longguoping@gmail.com
// Niko Li, newlife20080214@gmail.com
// Yao Wang, bitwangyaoyao@gmail.com
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other oclMaterials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// 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 Intel Corporation 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.
//
//M*/
#include "precomp.hpp"
#include <iomanip>
#include <fstream>
#include "binarycaching.hpp"
#undef __CL_ENABLE_EXCEPTIONS
#include <CL/cl.hpp>
namespace cv { namespace ocl {
extern void fft_teardown();
extern void clBlasTeardown();
struct PlatformInfoImpl
{
cl_platform_id platform_id;
std::vector<int> deviceIDs;
PlatformInfo info;
PlatformInfoImpl()
: platform_id(NULL)
{
}
};
struct DeviceInfoImpl
{
cl_platform_id platform_id;
cl_device_id device_id;
DeviceInfo info;
DeviceInfoImpl()
: platform_id(NULL), device_id(NULL)
{
}
};
static std::vector<PlatformInfoImpl> global_platforms;
static std::vector<DeviceInfoImpl> global_devices;
static bool parseOpenCLVersion(const std::string& versionStr, int& major, int& minor)
{
size_t p0 = versionStr.find(' ');
while (true)
{
if (p0 == std::string::npos)
break;
if (p0 + 1 >= versionStr.length())
break;
char c = versionStr[p0 + 1];
if (isdigit(c))
break;
p0 = versionStr.find(' ', p0 + 1);
}
size_t p1 = versionStr.find('.', p0);
size_t p2 = versionStr.find(' ', p1);
if (p0 == std::string::npos || p1 == std::string::npos || p2 == std::string::npos)
{
major = 0;
minor = 0;
return false;
}
std::string majorStr = versionStr.substr(p0 + 1, p1 - p0 - 1);
std::string minorStr = versionStr.substr(p1 + 1, p2 - p1 - 1);
major = atoi(majorStr.c_str());
minor = atoi(minorStr.c_str());
return true;
}
static int initializeOpenCLDevices()
{
assert(global_devices.size() == 0);
std::vector<cl::Platform> platforms;
try
{
openCLSafeCall(cl::Platform::get(&platforms));
}
catch (cv::Exception& e)
{
return 0; // OpenCL not found
}
global_platforms.resize(platforms.size());
for (size_t i = 0; i < platforms.size(); ++i)
{
PlatformInfoImpl& platformInfo = global_platforms[i];
platformInfo.info._id = i;
cl::Platform& platform = platforms[i];
platformInfo.platform_id = platform();
openCLSafeCall(platform.getInfo(CL_PLATFORM_PROFILE, &platformInfo.info.platformProfile));
openCLSafeCall(platform.getInfo(CL_PLATFORM_VERSION, &platformInfo.info.platformVersion));
openCLSafeCall(platform.getInfo(CL_PLATFORM_NAME, &platformInfo.info.platformName));
openCLSafeCall(platform.getInfo(CL_PLATFORM_VENDOR, &platformInfo.info.platformVendor));
openCLSafeCall(platform.getInfo(CL_PLATFORM_EXTENSIONS, &platformInfo.info.platformExtensons));
parseOpenCLVersion(platformInfo.info.platformVersion,
platformInfo.info.platformVersionMajor, platformInfo.info.platformVersionMinor);
std::vector<cl::Device> devices;
cl_int status = platform.getDevices(CL_DEVICE_TYPE_ALL, &devices);
if(status != CL_DEVICE_NOT_FOUND)
openCLVerifyCall(status);
if(devices.size() > 0)
{
int baseIndx = global_devices.size();
global_devices.resize(baseIndx + devices.size());
platformInfo.deviceIDs.resize(devices.size());
platformInfo.info.devices.resize(devices.size());
for(size_t j = 0; j < devices.size(); ++j)
{
cl::Device& device = devices[j];
DeviceInfoImpl& deviceInfo = global_devices[baseIndx + j];
deviceInfo.info._id = baseIndx + j;
deviceInfo.platform_id = platform();
deviceInfo.device_id = device();
deviceInfo.info.platform = &platformInfo.info;
platformInfo.deviceIDs[j] = deviceInfo.info._id;
cl_device_type type = -1;
openCLSafeCall(device.getInfo(CL_DEVICE_TYPE, &type));
deviceInfo.info.deviceType = DeviceType(type);
openCLSafeCall(device.getInfo(CL_DEVICE_PROFILE, &deviceInfo.info.deviceProfile));
openCLSafeCall(device.getInfo(CL_DEVICE_VERSION, &deviceInfo.info.deviceVersion));
openCLSafeCall(device.getInfo(CL_DEVICE_NAME, &deviceInfo.info.deviceName));
openCLSafeCall(device.getInfo(CL_DEVICE_VENDOR, &deviceInfo.info.deviceVendor));
cl_uint vendorID = -1;
openCLSafeCall(device.getInfo(CL_DEVICE_VENDOR_ID, &vendorID));
deviceInfo.info.deviceVendorId = vendorID;
openCLSafeCall(device.getInfo(CL_DRIVER_VERSION, &deviceInfo.info.deviceDriverVersion));
openCLSafeCall(device.getInfo(CL_DEVICE_EXTENSIONS, &deviceInfo.info.deviceExtensions));
parseOpenCLVersion(deviceInfo.info.deviceVersion,
deviceInfo.info.deviceVersionMajor, deviceInfo.info.deviceVersionMinor);
size_t maxWorkGroupSize = 0;
openCLSafeCall(device.getInfo(CL_DEVICE_MAX_WORK_GROUP_SIZE, &maxWorkGroupSize));
deviceInfo.info.maxWorkGroupSize = maxWorkGroupSize;
cl_uint maxDimensions = 0;
openCLSafeCall(device.getInfo(CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS, &maxDimensions));
std::vector<size_t> maxWorkItemSizes(maxDimensions);
openCLSafeCall(clGetDeviceInfo(device(), CL_DEVICE_MAX_WORK_ITEM_SIZES, sizeof(size_t) * maxDimensions,
(void *)&maxWorkItemSizes[0], 0));
deviceInfo.info.maxWorkItemSizes = maxWorkItemSizes;
cl_uint maxComputeUnits = 0;
openCLSafeCall(device.getInfo(CL_DEVICE_MAX_COMPUTE_UNITS, &maxComputeUnits));
deviceInfo.info.maxComputeUnits = maxComputeUnits;
cl_ulong localMemorySize = 0;
openCLSafeCall(device.getInfo(CL_DEVICE_LOCAL_MEM_SIZE, &localMemorySize));
deviceInfo.info.localMemorySize = (size_t)localMemorySize;
cl_bool unifiedMemory = false;
openCLSafeCall(device.getInfo(CL_DEVICE_HOST_UNIFIED_MEMORY, &unifiedMemory));
deviceInfo.info.isUnifiedMemory = unifiedMemory != 0;
//initialize extra options for compilation. Currently only fp64 is included.
//Assume 4KB is enough to store all possible extensions.
openCLSafeCall(device.getInfo(CL_DEVICE_EXTENSIONS, &deviceInfo.info.deviceExtensions));
size_t fp64_khr = deviceInfo.info.deviceExtensions.find("cl_khr_fp64");
if(fp64_khr != std::string::npos)
{
deviceInfo.info.compilationExtraOptions += "-D DOUBLE_SUPPORT";
deviceInfo.info.haveDoubleSupport = true;
}
else
{
deviceInfo.info.haveDoubleSupport = false;
}
}
}
}
for (size_t i = 0; i < platforms.size(); ++i)
{
PlatformInfoImpl& platformInfo = global_platforms[i];
for(size_t j = 0; j < platformInfo.deviceIDs.size(); ++j)
{
DeviceInfoImpl& deviceInfo = global_devices[platformInfo.deviceIDs[j]];
platformInfo.info.devices[j] = &deviceInfo.info;
}
}
return global_devices.size();
}
DeviceInfo::DeviceInfo()
: _id(-1), deviceType(DeviceType(0)),
deviceVendorId(-1),
maxWorkGroupSize(0), maxComputeUnits(0), localMemorySize(0),
deviceVersionMajor(0), deviceVersionMinor(0),
haveDoubleSupport(false), isUnifiedMemory(false),
platform(NULL)
{
// nothing
}
PlatformInfo::PlatformInfo()
: _id(-1),
platformVersionMajor(0), platformVersionMinor(0)
{
// nothing
}
//////////////////////////////// OpenCL context ////////////////////////
//This is a global singleton class used to represent a OpenCL context.
class ContextImpl : public Context
{
public:
const cl_device_id clDeviceID;
cl_context clContext;
cl_command_queue clCmdQueue;
const DeviceInfo& deviceInfo;
protected:
ContextImpl(const DeviceInfo& deviceInfo, cl_device_id clDeviceID)
: clDeviceID(clDeviceID), clContext(NULL), clCmdQueue(NULL), deviceInfo(deviceInfo)
{
// nothing
}
~ContextImpl();
public:
static ContextImpl* getContext();
static void setContext(const DeviceInfo* deviceInfo);
bool supportsFeature(FEATURE_TYPE featureType) const;
static void cleanupContext(void);
};
static cv::Mutex currentContextMutex;
static ContextImpl* currentContext = NULL;
Context* Context::getContext()
{
return currentContext;
}
bool Context::supportsFeature(FEATURE_TYPE featureType) const
{
return ((ContextImpl*)this)->supportsFeature(featureType);
}
const DeviceInfo& Context::getDeviceInfo() const
{
return ((ContextImpl*)this)->deviceInfo;
}
const void* Context::getOpenCLContextPtr() const
{
return &(((ContextImpl*)this)->clContext);
}
const void* Context::getOpenCLCommandQueuePtr() const
{
return &(((ContextImpl*)this)->clCmdQueue);
}
const void* Context::getOpenCLDeviceIDPtr() const
{
return &(((ContextImpl*)this)->clDeviceID);
}
bool ContextImpl::supportsFeature(FEATURE_TYPE featureType) const
{
switch (featureType)
{
case FEATURE_CL_DOUBLE:
return deviceInfo.haveDoubleSupport;
case FEATURE_CL_UNIFIED_MEM:
return deviceInfo.isUnifiedMemory;
case FEATURE_CL_VER_1_2:
return deviceInfo.deviceVersionMajor > 1 || (deviceInfo.deviceVersionMajor == 1 && deviceInfo.deviceVersionMinor >= 2);
}
CV_Error(CV_StsBadArg, "Invalid feature type");
return false;
}
#if defined(WIN32)
static bool __termination = false;
#endif
ContextImpl::~ContextImpl()
{
fft_teardown();
clBlasTeardown();
#ifdef WIN32
// if process is on termination stage (ExitProcess was called and other threads were terminated)
// then disable command queue release because it may cause program hang
if (!__termination)
#endif
{
if(clCmdQueue)
{
openCLSafeCall(clReleaseCommandQueue(clCmdQueue)); // some cleanup problems are here
}
if(clContext)
{
openCLSafeCall(clReleaseContext(clContext));
}
}
clCmdQueue = NULL;
clContext = NULL;
}
void ContextImpl::cleanupContext(void)
{
cv::AutoLock lock(currentContextMutex);
if (currentContext)
delete currentContext;
currentContext = NULL;
}
void ContextImpl::setContext(const DeviceInfo* deviceInfo)
{
CV_Assert(deviceInfo->_id >= 0 && deviceInfo->_id < (int)global_devices.size());
DeviceInfoImpl& infoImpl = global_devices[deviceInfo->_id];
CV_Assert(deviceInfo == &infoImpl.info);
cl_int status = 0;
cl_context_properties cps[3] = { CL_CONTEXT_PLATFORM, (cl_context_properties)(infoImpl.platform_id), 0 };
cl_context clContext = clCreateContext(cps, 1, &infoImpl.device_id, NULL, NULL, &status);
openCLVerifyCall(status);
// TODO add CL_QUEUE_PROFILING_ENABLE
cl_command_queue clCmdQueue = clCreateCommandQueue(clContext, infoImpl.device_id, 0, &status);
openCLVerifyCall(status);
ContextImpl* ctx = new ContextImpl(infoImpl.info, infoImpl.device_id);
ctx->clCmdQueue = clCmdQueue;
ctx->clContext = clContext;
ContextImpl* old = NULL;
{
cv::AutoLock lock(currentContextMutex);
old = currentContext;
currentContext = ctx;
}
if (old != NULL)
{
delete old;
}
}
ContextImpl* ContextImpl::getContext()
{
return currentContext;
}
int getOpenCLPlatforms(PlatformsInfo& platforms)
{
platforms.clear();
for (size_t id = 0; id < global_platforms.size(); ++id)
{
PlatformInfoImpl& impl = global_platforms[id];
platforms.push_back(&impl.info);
}
return platforms.size();
}
int getOpenCLDevices(std::vector<const DeviceInfo*> &devices, int deviceType, const PlatformInfo* platform)
{
devices.clear();
switch(deviceType)
{
case CVCL_DEVICE_TYPE_DEFAULT:
case CVCL_DEVICE_TYPE_CPU:
case CVCL_DEVICE_TYPE_GPU:
case CVCL_DEVICE_TYPE_ACCELERATOR:
case CVCL_DEVICE_TYPE_ALL:
break;
default:
return 0;
}
if (platform == NULL)
{
for (size_t id = 0; id < global_devices.size(); ++id)
{
DeviceInfoImpl& deviceInfo = global_devices[id];
if (((int)deviceInfo.info.deviceType & deviceType) == deviceType)
{
devices.push_back(&deviceInfo.info);
}
}
}
else
{
for (size_t id = 0; id < platform->devices.size(); ++id)
{
const DeviceInfo* deviceInfo = platform->devices[id];
if (((int)deviceInfo->deviceType & deviceType) == deviceType)
{
devices.push_back(deviceInfo);
}
}
}
return (int)devices.size();
}
void setDevice(const DeviceInfo* info)
{
ContextImpl::setContext(info);
}
bool supportsFeature(FEATURE_TYPE featureType)
{
return Context::getContext()->supportsFeature(featureType);
}
struct __Module
{
__Module() { initializeOpenCLDevices(); }
~__Module() { ContextImpl::cleanupContext(); }
};
static __Module __module;
}//namespace ocl
}//namespace cv
#if defined(WIN32) && defined(CVAPI_EXPORTS)
extern "C"
BOOL WINAPI DllMain(HINSTANCE /*hInst*/, DWORD fdwReason, LPVOID lpReserved)
{
if (fdwReason == DLL_PROCESS_DETACH)
{
if (lpReserved != NULL) // called after ExitProcess() call
cv::ocl::__termination = true;
}
return TRUE;
}
#endif

434
modules/ocl/src/cl_operations.cpp Normal file
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@ -0,0 +1,434 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Guoping Long, longguoping@gmail.com
// Niko Li, newlife20080214@gmail.com
// Yao Wang, bitwangyaoyao@gmail.com
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other oclMaterials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// 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 Intel Corporation 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.
//
//M*/
#include "precomp.hpp"
#include <iomanip>
#include <fstream>
#include "binarycaching.hpp"
#undef __CL_ENABLE_EXCEPTIONS
#include <CL/cl.hpp>
//#define PRINT_KERNEL_RUN_TIME
#define RUN_TIMES 100
#ifndef CL_MEM_USE_PERSISTENT_MEM_AMD
#define CL_MEM_USE_PERSISTENT_MEM_AMD 0
#endif
//#define AMD_DOUBLE_DIFFER
namespace cv { namespace ocl {
DevMemType gDeviceMemType = DEVICE_MEM_DEFAULT;
DevMemRW gDeviceMemRW = DEVICE_MEM_R_W;
int gDevMemTypeValueMap[5] = {0,
CL_MEM_ALLOC_HOST_PTR,
CL_MEM_USE_HOST_PTR,
CL_MEM_COPY_HOST_PTR,
CL_MEM_USE_PERSISTENT_MEM_AMD};
int gDevMemRWValueMap[3] = {CL_MEM_READ_WRITE, CL_MEM_READ_ONLY, CL_MEM_WRITE_ONLY};
void finish()
{
clFinish(getClCommandQueue(Context::getContext()));
}
bool isCpuDevice()
{
const DeviceInfo& info = Context::getContext()->getDeviceInfo();
return (info.deviceType == CVCL_DEVICE_TYPE_CPU);
}
size_t queryWaveFrontSize(cl_kernel kernel)
{
const DeviceInfo& info = Context::getContext()->getDeviceInfo();
if (info.deviceType == CVCL_DEVICE_TYPE_CPU)
return 1;
size_t wavefront = 0;
CV_Assert(kernel != NULL);
openCLSafeCall(clGetKernelWorkGroupInfo(kernel, getClDeviceID(Context::getContext()),
CL_KERNEL_PREFERRED_WORK_GROUP_SIZE_MULTIPLE, sizeof(size_t), &wavefront, NULL));
return wavefront;
}
void openCLReadBuffer(Context *ctx, cl_mem dst_buffer, void *host_buffer, size_t size)
{
cl_int status;
status = clEnqueueReadBuffer(getClCommandQueue(ctx), dst_buffer, CL_TRUE, 0,
size, host_buffer, 0, NULL, NULL);
openCLVerifyCall(status);
}
cl_mem openCLCreateBuffer(Context *ctx, size_t flag , size_t size)
{
cl_int status;
cl_mem buffer = clCreateBuffer(getClContext(ctx), (cl_mem_flags)flag, size, NULL, &status);
openCLVerifyCall(status);
return buffer;
}
void openCLMallocPitch(Context *ctx, void **dev_ptr, size_t *pitch,
size_t widthInBytes, size_t height)
{
openCLMallocPitchEx(ctx, dev_ptr, pitch, widthInBytes, height, gDeviceMemRW, gDeviceMemType);
}
void openCLMallocPitchEx(Context *ctx, void **dev_ptr, size_t *pitch,
size_t widthInBytes, size_t height, DevMemRW rw_type, DevMemType mem_type)
{
cl_int status;
*dev_ptr = clCreateBuffer(getClContext(ctx), gDevMemRWValueMap[rw_type]|gDevMemTypeValueMap[mem_type],
widthInBytes * height, 0, &status);
openCLVerifyCall(status);
*pitch = widthInBytes;
}
void openCLMemcpy2D(Context *ctx, void *dst, size_t dpitch,
const void *src, size_t spitch,
size_t width, size_t height, openCLMemcpyKind kind, int channels)
{
size_t buffer_origin[3] = {0, 0, 0};
size_t host_origin[3] = {0, 0, 0};
size_t region[3] = {width, height, 1};
if(kind == clMemcpyHostToDevice)
{
if(dpitch == width || channels == 3 || height == 1)
{
openCLSafeCall(clEnqueueWriteBuffer(getClCommandQueue(ctx), (cl_mem)dst, CL_TRUE,
0, width * height, src, 0, NULL, NULL));
}
else
{
openCLSafeCall(clEnqueueWriteBufferRect(getClCommandQueue(ctx), (cl_mem)dst, CL_TRUE,
buffer_origin, host_origin, region, dpitch, 0, spitch, 0, src, 0, 0, 0));
}
}
else if(kind == clMemcpyDeviceToHost)
{
if(spitch == width || channels == 3 || height == 1)
{
openCLSafeCall(clEnqueueReadBuffer(getClCommandQueue(ctx), (cl_mem)src, CL_TRUE,
0, width * height, dst, 0, NULL, NULL));
}
else
{
openCLSafeCall(clEnqueueReadBufferRect(getClCommandQueue(ctx), (cl_mem)src, CL_TRUE,
buffer_origin, host_origin, region, spitch, 0, dpitch, 0, dst, 0, 0, 0));
}
}
}
void openCLCopyBuffer2D(Context *ctx, void *dst, size_t dpitch, int dst_offset,
const void *src, size_t spitch,
size_t width, size_t height, int src_offset)
{
size_t src_origin[3] = {src_offset % spitch, src_offset / spitch, 0};
size_t dst_origin[3] = {dst_offset % dpitch, dst_offset / dpitch, 0};
size_t region[3] = {width, height, 1};
openCLSafeCall(clEnqueueCopyBufferRect(getClCommandQueue(ctx), (cl_mem)src, (cl_mem)dst, src_origin, dst_origin,
region, spitch, 0, dpitch, 0, 0, 0, 0));
}
void openCLFree(void *devPtr)
{
openCLSafeCall(clReleaseMemObject((cl_mem)devPtr));
}
cl_kernel openCLGetKernelFromSource(const Context *ctx, const char **source, string kernelName)
{
return openCLGetKernelFromSource(ctx, source, kernelName, NULL);
}
cl_kernel openCLGetKernelFromSource(const Context *ctx, const char **source, string kernelName,
const char *build_options)
{
cl_kernel kernel;
cl_int status = 0;
CV_Assert(ProgramCache::getProgramCache() != NULL);
cl_program program = ProgramCache::getProgramCache()->getProgram(ctx, source, kernelName, build_options);
CV_Assert(program != NULL);
kernel = clCreateKernel(program, kernelName.c_str(), &status);
openCLVerifyCall(status);
return kernel;
}
void openCLVerifyKernel(const Context *ctx, cl_kernel kernel, size_t *localThreads)
{
size_t kernelWorkGroupSize;
openCLSafeCall(clGetKernelWorkGroupInfo(kernel, getClDeviceID(ctx),
CL_KERNEL_WORK_GROUP_SIZE, sizeof(size_t), &kernelWorkGroupSize, 0));
CV_Assert( localThreads[0] <= ctx->getDeviceInfo().maxWorkItemSizes[0] );
CV_Assert( localThreads[1] <= ctx->getDeviceInfo().maxWorkItemSizes[1] );
CV_Assert( localThreads[2] <= ctx->getDeviceInfo().maxWorkItemSizes[2] );
CV_Assert( localThreads[0] * localThreads[1] * localThreads[2] <= kernelWorkGroupSize );
CV_Assert( localThreads[0] * localThreads[1] * localThreads[2] <= ctx->getDeviceInfo().maxWorkGroupSize );
}
#ifdef PRINT_KERNEL_RUN_TIME
static double total_execute_time = 0;
static double total_kernel_time = 0;
#endif
void openCLExecuteKernel_(Context *ctx , const char **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)
{
//construct kernel name
//The rule is functionName_Cn_Dn, C represent Channels, D Represent DataType Depth, n represent an integer number
//for exmaple split_C2_D2, represent the split kernel with channels =2 and dataType Depth = 2(Data type is char)
stringstream idxStr;
if(channels != -1)
idxStr << "_C" << channels;
if(depth != -1)
idxStr << "_D" << depth;
kernelName += idxStr.str();
cl_kernel kernel;
kernel = openCLGetKernelFromSource(ctx, source, kernelName, build_options);
if ( localThreads != NULL)
{
globalThreads[0] = roundUp(globalThreads[0], localThreads[0]);
globalThreads[1] = roundUp(globalThreads[1], localThreads[1]);
globalThreads[2] = roundUp(globalThreads[2], localThreads[2]);
cv::ocl::openCLVerifyKernel(ctx, kernel, localThreads);
}
for(size_t i = 0; i < args.size(); i ++)
openCLSafeCall(clSetKernelArg(kernel, i, args[i].first, args[i].second));
#ifndef PRINT_KERNEL_RUN_TIME
openCLSafeCall(clEnqueueNDRangeKernel(getClCommandQueue(ctx), kernel, 3, NULL, globalThreads,
localThreads, 0, NULL, NULL));
#else
cl_event event = NULL;
openCLSafeCall(clEnqueueNDRangeKernel(getClCommandQueue(ctx), kernel, 3, NULL, globalThreads,
localThreads, 0, NULL, &event));
cl_ulong start_time, end_time, queue_time;
double execute_time = 0;
double total_time = 0;
openCLSafeCall(clWaitForEvents(1, &event));
openCLSafeCall(clGetEventProfilingInfo(event, CL_PROFILING_COMMAND_START,
sizeof(cl_ulong), &start_time, 0));
openCLSafeCall(clGetEventProfilingInfo(event, CL_PROFILING_COMMAND_END,
sizeof(cl_ulong), &end_time, 0));
openCLSafeCall(clGetEventProfilingInfo(event, CL_PROFILING_COMMAND_QUEUED,
sizeof(cl_ulong), &queue_time, 0));
execute_time = (double)(end_time - start_time) / (1000 * 1000);
total_time = (double)(end_time - queue_time) / (1000 * 1000);
total_execute_time += execute_time;
total_kernel_time += total_time;
clReleaseEvent(event);
#endif
clFlush(getClCommandQueue(ctx));
openCLSafeCall(clReleaseKernel(kernel));
}
void openCLExecuteKernel(Context *ctx , const char **source, string kernelName,
size_t globalThreads[3], size_t localThreads[3],
vector< pair<size_t, const void *> > &args, int channels, int depth)
{
openCLExecuteKernel(ctx, source, kernelName, globalThreads, localThreads, args,
channels, depth, NULL);
}
void openCLExecuteKernel(Context *ctx , const char **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)
{
#ifndef PRINT_KERNEL_RUN_TIME
openCLExecuteKernel_(ctx, source, kernelName, globalThreads, localThreads, args, channels, depth,
build_options);
#else
string data_type[] = { "uchar", "char", "ushort", "short", "int", "float", "double"};
cout << endl;
cout << "Function Name: " << kernelName;
if(depth >= 0)
cout << " |data type: " << data_type[depth];
cout << " |channels: " << channels;
cout << " |Time Unit: " << "ms" << endl;
total_execute_time = 0;
total_kernel_time = 0;
cout << "-------------------------------------" << endl;
cout << setiosflags(ios::left) << setw(15) << "excute time";
cout << setiosflags(ios::left) << setw(15) << "lauch time";
cout << setiosflags(ios::left) << setw(15) << "kernel time" << endl;
int i = 0;
for(i = 0; i < RUN_TIMES; i++)
openCLExecuteKernel_(ctx, source, kernelName, globalThreads, localThreads, args, channels, depth,
build_options);
cout << "average kernel excute time: " << total_execute_time / RUN_TIMES << endl; // "ms" << endl;
cout << "average kernel total time: " << total_kernel_time / RUN_TIMES << endl; // "ms" << endl;
#endif
}
double openCLExecuteKernelInterop(Context *ctx , const char **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,
bool finish, bool measureKernelTime, bool cleanUp)
{
//construct kernel name
//The rule is functionName_Cn_Dn, C represent Channels, D Represent DataType Depth, n represent an integer number
//for exmaple split_C2_D2, represent the split kernel with channels =2 and dataType Depth = 2(Data type is char)
stringstream idxStr;
if(channels != -1)
idxStr << "_C" << channels;
if(depth != -1)
idxStr << "_D" << depth;
kernelName += idxStr.str();
cl_kernel kernel;
kernel = openCLGetKernelFromSource(ctx, source, kernelName, build_options);
double kernelTime = 0.0;
if( globalThreads != NULL)
{
if ( localThreads != NULL)
{
globalThreads[0] = divUp(globalThreads[0], localThreads[0]) * localThreads[0];
globalThreads[1] = divUp(globalThreads[1], localThreads[1]) * localThreads[1];
globalThreads[2] = divUp(globalThreads[2], localThreads[2]) * localThreads[2];
//size_t blockSize = localThreads[0] * localThreads[1] * localThreads[2];
cv::ocl::openCLVerifyKernel(ctx, kernel, localThreads);
}
for(size_t i = 0; i < args.size(); i ++)
openCLSafeCall(clSetKernelArg(kernel, i, args[i].first, args[i].second));
if(measureKernelTime == false)
{
openCLSafeCall(clEnqueueNDRangeKernel(getClCommandQueue(ctx), kernel, 3, NULL, globalThreads,
localThreads, 0, NULL, NULL));
}
else
{
cl_event event = NULL;
openCLSafeCall(clEnqueueNDRangeKernel(getClCommandQueue(ctx), kernel, 3, NULL, globalThreads,
localThreads, 0, NULL, &event));
cl_ulong end_time, queue_time;
openCLSafeCall(clWaitForEvents(1, &event));
openCLSafeCall(clGetEventProfilingInfo(event, CL_PROFILING_COMMAND_END,
sizeof(cl_ulong), &end_time, 0));
openCLSafeCall(clGetEventProfilingInfo(event, CL_PROFILING_COMMAND_QUEUED,
sizeof(cl_ulong), &queue_time, 0));
kernelTime = (double)(end_time - queue_time) / (1000 * 1000);
clReleaseEvent(event);
}
}
if(finish)
{
clFinish(getClCommandQueue(ctx));
}
if(cleanUp)
{
openCLSafeCall(clReleaseKernel(kernel));
}
return kernelTime;
}
//double openCLExecuteKernelInterop(Context *ctx , const char **fileName, const int numFiles, 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,
// bool finish, bool measureKernelTime, bool cleanUp)
//
//{
// std::vector<std::string> fsource;
// for (int i = 0 ; i < numFiles ; i++)
// {
// std::string str;
// if (convertToString(fileName[i], str) >= 0)
// fsource.push_back(str);
// }
// const char **source = new const char *[numFiles];
// for (int i = 0 ; i < numFiles ; i++)
// source[i] = fsource[i].c_str();
// double kernelTime = openCLExecuteKernelInterop(ctx ,source, kernelName, globalThreads, localThreads,
// args, channels, depth, build_options, finish, measureKernelTime, cleanUp);
// fsource.clear();
// delete []source;
// return kernelTime;
//}
cl_mem load_constant(cl_context context, cl_command_queue command_queue, const void *value,
const size_t size)
{
int status;
cl_mem con_struct;
con_struct = clCreateBuffer(context, CL_MEM_READ_ONLY, size, NULL, &status);
openCLSafeCall(status);
openCLSafeCall(clEnqueueWriteBuffer(command_queue, con_struct, 1, 0, size,
value, 0, 0, 0));
return con_struct;
}
}//namespace ocl
}//namespace cv

311
modules/ocl/src/cl_programcache.cpp Normal file
View File

@ -0,0 +1,311 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Guoping Long, longguoping@gmail.com
// Niko Li, newlife20080214@gmail.com
// Yao Wang, bitwangyaoyao@gmail.com
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other oclMaterials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// 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 Intel Corporation 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.
//
//M*/
#include "precomp.hpp"
#include <iomanip>
#include <fstream>
#include "binarycaching.hpp"
#undef __CL_ENABLE_EXCEPTIONS
#include <CL/cl.hpp>
namespace cv { namespace ocl {
/*
* The binary caching system to eliminate redundant program source compilation.
* Strictly, this is not a cache because we do not implement evictions right now.
* We shall add such features to trade-off memory consumption and performance when necessary.
*/
std::auto_ptr<ProgramCache> _programCache;
ProgramCache* ProgramCache::getProgramCache()
{
if (NULL == _programCache.get())
_programCache.reset(new ProgramCache());
return _programCache.get();
}
ProgramCache::ProgramCache()
{
codeCache.clear();
cacheSize = 0;
}
ProgramCache::~ProgramCache()
{
releaseProgram();
}
cl_program ProgramCache::progLookup(string srcsign)
{
map<string, cl_program>::iterator iter;
iter = codeCache.find(srcsign);
if(iter != codeCache.end())
return iter->second;
else
return NULL;
}
void ProgramCache::addProgram(string srcsign , cl_program program)
{
if(!progLookup(srcsign))
{
codeCache.insert(map<string, cl_program>::value_type(srcsign, program));
}
}
void ProgramCache::releaseProgram()
{
map<string, cl_program>::iterator iter;
for(iter = codeCache.begin(); iter != codeCache.end(); iter++)
{
openCLSafeCall(clReleaseProgram(iter->second));
}
codeCache.clear();
cacheSize = 0;
}
static int enable_disk_cache =
#ifdef _DEBUG
false;
#else
true;
#endif
static int update_disk_cache = false;
static String binpath = "";
void setBinaryDiskCache(int mode, String path)
{
if(mode == CACHE_NONE)
{
update_disk_cache = 0;
enable_disk_cache = 0;
return;
}
update_disk_cache |= (mode & CACHE_UPDATE) == CACHE_UPDATE;
enable_disk_cache |=
#ifdef _DEBUG
(mode & CACHE_DEBUG) == CACHE_DEBUG;
#else
(mode & CACHE_RELEASE) == CACHE_RELEASE;
#endif
if(enable_disk_cache && !path.empty())
{
binpath = path;
}
}
void setBinpath(const char *path)
{
binpath = path;
}
int savetofile(const Context*, cl_program &program, const char *fileName)
{
size_t binarySize;
openCLSafeCall(clGetProgramInfo(program,
CL_PROGRAM_BINARY_SIZES,
sizeof(size_t),
&binarySize, NULL));
char* binary = (char*)malloc(binarySize);
if(binary == NULL)
{
CV_Error(CV_StsNoMem, "Failed to allocate host memory.");
}
openCLSafeCall(clGetProgramInfo(program,
CL_PROGRAM_BINARIES,
sizeof(char *),
&binary,
NULL));
FILE *fp = fopen(fileName, "wb+");
if(fp != NULL)
{
fwrite(binary, binarySize, 1, fp);
free(binary);
fclose(fp);
}
return 1;
}
cl_program ProgramCache::getProgram(const Context *ctx, const char **source, string kernelName,
const char *build_options)
{
cl_program program;
cl_int status = 0;
stringstream src_sign;
string srcsign;
string filename;
if (NULL != build_options)
{
src_sign << (int64)(*source) << getClContext(ctx) << "_" << build_options;
}
else
{
src_sign << (int64)(*source) << getClContext(ctx);
}
srcsign = src_sign.str();
program = NULL;
program = ProgramCache::getProgramCache()->progLookup(srcsign);
if (!program)
{
//config build programs
std::string all_build_options;
if (!ctx->getDeviceInfo().compilationExtraOptions.empty())
all_build_options += ctx->getDeviceInfo().compilationExtraOptions;
if (build_options != NULL)
{
all_build_options += " ";
all_build_options += build_options;
}
filename = binpath + kernelName + "_" + ctx->getDeviceInfo().deviceName + all_build_options + ".clb";
FILE *fp = enable_disk_cache ? fopen(filename.c_str(), "rb") : NULL;
if(fp == NULL || update_disk_cache)
{
if(fp != NULL)
fclose(fp);
program = clCreateProgramWithSource(
getClContext(ctx), 1, source, NULL, &status);
openCLVerifyCall(status);
cl_device_id device = getClDeviceID(ctx);
status = clBuildProgram(program, 1, &device, all_build_options.c_str(), NULL, NULL);
if(status == CL_SUCCESS && enable_disk_cache)
savetofile(ctx, program, filename.c_str());
}
else
{
fseek(fp, 0, SEEK_END);
size_t binarySize = ftell(fp);
fseek(fp, 0, SEEK_SET);
char *binary = new char[binarySize];
CV_Assert(1 == fread(binary, binarySize, 1, fp));
fclose(fp);
cl_int status = 0;
cl_device_id device = getClDeviceID(ctx);
program = clCreateProgramWithBinary(getClContext(ctx),
1,
&device,
(const size_t *)&binarySize,
(const unsigned char **)&binary,
NULL,
&status);
openCLVerifyCall(status);
status = clBuildProgram(program, 1, &device, all_build_options.c_str(), NULL, NULL);
delete[] binary;
}
if(status != CL_SUCCESS)
{
if(status == CL_BUILD_PROGRAM_FAILURE)
{
cl_int logStatus;
char *buildLog = NULL;
size_t buildLogSize = 0;
logStatus = clGetProgramBuildInfo(program,
getClDeviceID(ctx), CL_PROGRAM_BUILD_LOG, buildLogSize,
buildLog, &buildLogSize);
if(logStatus != CL_SUCCESS)
std::cout << "Failed to build the program and get the build info." << endl;
buildLog = new char[buildLogSize];
CV_DbgAssert(!!buildLog);
memset(buildLog, 0, buildLogSize);
openCLSafeCall(clGetProgramBuildInfo(program, getClDeviceID(ctx),
CL_PROGRAM_BUILD_LOG, buildLogSize, buildLog, NULL));
std::cout << "\n\t\t\tBUILD LOG\n";
std::cout << buildLog << endl;
delete [] buildLog;
}
openCLVerifyCall(status);
}
//Cache the binary for future use if build_options is null
if( (this->cacheSize += 1) < MAX_PROG_CACHE_SIZE)
this->addProgram(srcsign, program);
else
cout << "Warning: code cache has been full.\n";
}
return program;
}
//// Converts the contents of a file into a string
//static int convertToString(const char *filename, std::string& s)
//{
// size_t size;
// char* str;
//
// std::fstream f(filename, (std::fstream::in | std::fstream::binary));
// if(f.is_open())
// {
// size_t fileSize;
// f.seekg(0, std::fstream::end);
// size = fileSize = (size_t)f.tellg();
// f.seekg(0, std::fstream::beg);
//
// str = new char[size+1];
// if(!str)
// {
// f.close();
// return -1;
// }
//
// f.read(str, fileSize);
// f.close();
// str[size] = '\0';
//
// s = str;
// delete[] str;
// return 0;
// }
// printf("Error: Failed to open file %s\n", filename);
// return -1;
//}
} // namespace ocl
} // namespace cv

16
modules/ocl/src/error.cpp
View File

@ -152,19 +152,19 @@ namespace cv
case CL_INVALID_GLOBAL_WORK_SIZE:
return "CL_INVALID_GLOBAL_WORK_SIZE";
//case CL_INVALID_PROPERTY:
// return "CL_INVALID_PROPERTY";
// return "CL_INVALID_PROPERTY";
//case CL_INVALID_GL_SHAREGROUP_REFERENCE_KHR:
// return "CL_INVALID_GL_SHAREGROUP_REFERENCE_KHR";
// return "CL_INVALID_GL_SHAREGROUP_REFERENCE_KHR";
//case CL_PLATFORM_NOT_FOUND_KHR:
// return "CL_PLATFORM_NOT_FOUND_KHR";
// //case CL_INVALID_PROPERTY_EXT:
// // return "CL_INVALID_PROPERTY_EXT";
// return "CL_PLATFORM_NOT_FOUND_KHR";
// //case CL_INVALID_PROPERTY_EXT:
// // return "CL_INVALID_PROPERTY_EXT";
//case CL_DEVICE_PARTITION_FAILED_EXT:
// return "CL_DEVICE_PARTITION_FAILED_EXT";
// return "CL_DEVICE_PARTITION_FAILED_EXT";
//case CL_INVALID_PARTITION_COUNT_EXT:
// return "CL_INVALID_PARTITION_COUNT_EXT";
// return "CL_INVALID_PARTITION_COUNT_EXT";
//default:
// return "unknown error code";
// return "unknown error code";
}
static char buf[256];
sprintf(buf, "%d", err);

44
modules/ocl/src/fft.cpp
View File

@ -156,25 +156,25 @@ cv::ocl::FftPlan::FftPlan(Size _dft_size, int _src_step, int _dst_step, int _fla
{
fft_setup();
bool is_1d_input = (_dft_size.height == 1);
int is_row_dft = flags & DFT_ROWS;
bool is_1d_input = (_dft_size.height == 1);
int is_row_dft = flags & DFT_ROWS;
int is_scaled_dft = flags & DFT_SCALE;
int is_inverse = flags & DFT_INVERSE;
int is_inverse = flags & DFT_INVERSE;
//clAmdFftResultLocation place;
clAmdFftLayout inLayout;
clAmdFftLayout outLayout;
clAmdFftDim dim = is_1d_input || is_row_dft ? CLFFT_1D : CLFFT_2D;
//clAmdFftResultLocation place;
clAmdFftLayout inLayout;
clAmdFftLayout outLayout;
clAmdFftDim dim = is_1d_input || is_row_dft ? CLFFT_1D : CLFFT_2D;
size_t batchSize = is_row_dft ? dft_size.height : 1;
size_t batchSize = is_row_dft ? dft_size.height : 1;
size_t clLengthsIn[ 3 ] = {1, 1, 1};
size_t clStridesIn[ 3 ] = {1, 1, 1};
//size_t clLengthsOut[ 3 ] = {1, 1, 1};
size_t clStridesOut[ 3 ] = {1, 1, 1};
clLengthsIn[0] = dft_size.width;
clLengthsIn[1] = is_row_dft ? 1 : dft_size.height;
clStridesIn[0] = 1;
clStridesOut[0] = 1;
clLengthsIn[0] = dft_size.width;
clLengthsIn[1] = is_row_dft ? 1 : dft_size.height;
clStridesIn[0] = 1;
clStridesOut[0] = 1;
switch(_type)
{
@ -206,7 +206,7 @@ cv::ocl::FftPlan::FftPlan(Size _dft_size, int _src_step, int _dst_step, int _fla
clStridesIn[2] = is_row_dft ? clStridesIn[1] : dft_size.width * clStridesIn[1];
clStridesOut[2] = is_row_dft ? clStridesOut[1] : dft_size.width * clStridesOut[1];
openCLSafeCall( clAmdFftCreateDefaultPlan( &plHandle, *(cl_context*)getoclContext(), dim, clLengthsIn ) );
openCLSafeCall( clAmdFftCreateDefaultPlan( &plHandle, *(cl_context*)getClContextPtr(), dim, clLengthsIn ) );
openCLSafeCall( clAmdFftSetResultLocation( plHandle, CLFFT_OUTOFPLACE ) );
openCLSafeCall( clAmdFftSetLayout( plHandle, inLayout, outLayout ) );
@ -220,7 +220,7 @@ cv::ocl::FftPlan::FftPlan(Size _dft_size, int _src_step, int _dst_step, int _fla
openCLSafeCall( clAmdFftSetPlanScale ( plHandle, is_inverse ? CLFFT_BACKWARD : CLFFT_FORWARD, scale_ ) );
//ready to bake
openCLSafeCall( clAmdFftBakePlan( plHandle, 1, (cl_command_queue*)getoclCommandQueue(), NULL, NULL ) );
openCLSafeCall( clAmdFftBakePlan( plHandle, 1, (cl_command_queue*)getClCommandQueuePtr(), NULL, NULL ) );
}
cv::ocl::FftPlan::~FftPlan()
{
@ -296,12 +296,12 @@ void cv::ocl::dft(const oclMat &src, oclMat &dst, Size dft_size, int flags)
// similar assertions with cuda module
CV_Assert(src.type() == CV_32F || src.type() == CV_32FC2);
//bool is_1d_input = (src.rows == 1);
//int is_row_dft = flags & DFT_ROWS;
//int is_scaled_dft = flags & DFT_SCALE;
int is_inverse = flags & DFT_INVERSE;
bool is_complex_input = src.channels() == 2;
bool is_complex_output = !(flags & DFT_REAL_OUTPUT);
//bool is_1d_input = (src.rows == 1);
//int is_row_dft = flags & DFT_ROWS;
//int is_scaled_dft = flags & DFT_SCALE;
int is_inverse = flags & DFT_INVERSE;
bool is_complex_input = src.channels() == 2;
bool is_complex_output = !(flags & DFT_REAL_OUTPUT);
// We don't support real-to-real transform
@ -338,10 +338,10 @@ void cv::ocl::dft(const oclMat &src, oclMat &dst, Size dft_size, int flags)
if (buffersize)
{
cl_int medstatus;
clMedBuffer = clCreateBuffer ( (cl_context)src.clCxt->oclContext(), CL_MEM_READ_WRITE, buffersize, 0, &medstatus);
clMedBuffer = clCreateBuffer ( *(cl_context*)(src.clCxt->getOpenCLContextPtr()), CL_MEM_READ_WRITE, buffersize, 0, &medstatus);
openCLSafeCall( medstatus );
}
cl_command_queue clq = (cl_command_queue)src.clCxt->oclCommandQueue();
cl_command_queue clq = *(cl_command_queue*)(src.clCxt->getOpenCLCommandQueuePtr());
openCLSafeCall( clAmdFftEnqueueTransform( plHandle,
is_inverse ? CLFFT_BACKWARD : CLFFT_FORWARD,
1,

2
modules/ocl/src/filtering.cpp
View File

@ -1430,7 +1430,7 @@ void cv::ocl::Scharr(const oclMat &src, oclMat &dst, int ddepth, int dx, int dy,
void cv::ocl::Laplacian(const oclMat &src, oclMat &dst, int ddepth, int ksize, double scale)
{
if (!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.type() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.type() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device don't support double\r\n");
return;

2
modules/ocl/src/gemm.cpp
View File

@ -134,7 +134,7 @@ void cv::ocl::gemm(const oclMat &src1, const oclMat &src2, double alpha,
int offb = src2.offset;
int offc = dst.offset;
cl_command_queue clq = (cl_command_queue)src1.clCxt->oclCommandQueue();
cl_command_queue clq = *(cl_command_queue*)src1.clCxt->getOpenCLCommandQueuePtr();
switch(src1.type())
{
case CV_32FC1:

2
modules/ocl/src/gftt.cpp
View File

@ -338,7 +338,7 @@ void cv::ocl::GoodFeaturesToTrackDetector_OCL::downloadPoints(const oclMat &poin
CV_DbgAssert(points.type() == CV_32FC2);
points_v.resize(points.cols);
openCLSafeCall(clEnqueueReadBuffer(
*reinterpret_cast<cl_command_queue*>(getoclCommandQueue()),
*(cl_command_queue*)getClCommandQueuePtr(),
reinterpret_cast<cl_mem>(points.data),
CL_TRUE,
0,

14
modules/ocl/src/haar.cpp
View File

@ -745,7 +745,7 @@ CvSeq *cv::ocl::OclCascadeClassifier::oclHaarDetectObjects( oclMat &gimg, CvMemS
if( gimg.cols < minSize.width || gimg.rows < minSize.height )
CV_Error(CV_StsError, "Image too small");
cl_command_queue qu = reinterpret_cast<cl_command_queue>(Context::getContext()->oclCommandQueue());
cl_command_queue qu = getClCommandQueue(Context::getContext());
if( (flags & CV_HAAR_SCALE_IMAGE) )
{
CvSize winSize0 = cascade->orig_window_size;
@ -788,7 +788,7 @@ CvSeq *cv::ocl::OclCascadeClassifier::oclHaarDetectObjects( oclMat &gimg, CvMemS
size_t blocksize = 8;
size_t localThreads[3] = { blocksize, blocksize , 1 };
size_t globalThreads[3] = { grp_per_CU *(gsum.clCxt->computeUnits()) *localThreads[0],
size_t globalThreads[3] = { grp_per_CU *(gsum.clCxt->getDeviceInfo().maxComputeUnits) *localThreads[0],
localThreads[1], 1
};
int outputsz = 256 * globalThreads[0] / localThreads[0];
@ -949,7 +949,7 @@ CvSeq *cv::ocl::OclCascadeClassifier::oclHaarDetectObjects( oclMat &gimg, CvMemS
int grp_per_CU = 12;
size_t blocksize = 8;
size_t localThreads[3] = { blocksize, blocksize , 1 };
size_t globalThreads[3] = { grp_per_CU *gsum.clCxt->computeUnits() *localThreads[0],
size_t globalThreads[3] = { grp_per_CU *gsum.clCxt->getDeviceInfo().maxComputeUnits *localThreads[0],
localThreads[1], 1 };
int outputsz = 256 * globalThreads[0] / localThreads[0];
int nodenum = (datasize - sizeof(GpuHidHaarClassifierCascade) -
@ -1120,7 +1120,7 @@ void cv::ocl::OclCascadeClassifierBuf::detectMultiScale(oclMat &gimg, CV_OUT std
int blocksize = 8;
int grp_per_CU = 12;
size_t localThreads[3] = { blocksize, blocksize, 1 };
size_t globalThreads[3] = { grp_per_CU * cv::ocl::Context::getContext()->computeUnits() *localThreads[0],
size_t globalThreads[3] = { grp_per_CU * cv::ocl::Context::getContext()->getDeviceInfo().maxComputeUnits *localThreads[0],
localThreads[1],
1 };
int outputsz = 256 * globalThreads[0] / localThreads[0];
@ -1148,7 +1148,7 @@ void cv::ocl::OclCascadeClassifierBuf::detectMultiScale(oclMat &gimg, CV_OUT std
}
int *candidate;
cl_command_queue qu = reinterpret_cast<cl_command_queue>(Context::getContext()->oclCommandQueue());
cl_command_queue qu = getClCommandQueue(Context::getContext());
if( (flags & CV_HAAR_SCALE_IMAGE) )
{
int indexy = 0;
@ -1340,7 +1340,7 @@ void cv::ocl::OclCascadeClassifierBuf::Init(const int rows, const int cols,
GpuHidHaarStageClassifier *stage;
GpuHidHaarClassifier *classifier;
GpuHidHaarTreeNode *node;
cl_command_queue qu = reinterpret_cast<cl_command_queue>(Context::getContext()->oclCommandQueue());
cl_command_queue qu = getClCommandQueue(Context::getContext());
if( (flags & CV_HAAR_SCALE_IMAGE) )
{
gcascade = (GpuHidHaarClassifierCascade *)(cascade->hid_cascade);
@ -1505,7 +1505,7 @@ void cv::ocl::OclCascadeClassifierBuf::CreateFactorRelatedBufs(
CvSize sz;
CvSize winSize0 = oldCascade->orig_window_size;
detect_piramid_info *scaleinfo;
cl_command_queue qu = reinterpret_cast<cl_command_queue>(Context::getContext()->oclCommandQueue());
cl_command_queue qu = getClCommandQueue(Context::getContext());
if (flags & CV_HAAR_SCALE_IMAGE)
{
for(factor = 1.f;; factor *= scaleFactor)

14
modules/ocl/src/hog.cpp
View File

@ -157,7 +157,7 @@ cv::ocl::HOGDescriptor::HOGDescriptor(Size win_size_, Size block_size_, Size blo
effect_size = Size(0, 0);
if (queryDeviceInfo<IS_CPU_DEVICE, bool>())
if (isCpuDevice())
hog_device_cpu = true;
else
hog_device_cpu = false;
@ -1670,9 +1670,9 @@ void cv::ocl::device::hog::compute_hists(int nbins,
else
{
cl_kernel kernel = openCLGetKernelFromSource(clCxt, &objdetect_hog, kernelName);
int wave_size = queryDeviceInfo<WAVEFRONT_SIZE, int>(kernel);
size_t wave_size = queryWaveFrontSize(kernel);
char opt[32] = {0};
sprintf(opt, "-D WAVE_SIZE=%d", wave_size);
sprintf(opt, "-D WAVE_SIZE=%d", (int)wave_size);
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads,
localThreads, args, -1, -1, opt);
}
@ -1734,9 +1734,9 @@ void cv::ocl::device::hog::normalize_hists(int nbins,
else
{
cl_kernel kernel = openCLGetKernelFromSource(clCxt, &objdetect_hog, kernelName);
int wave_size = queryDeviceInfo<WAVEFRONT_SIZE, int>(kernel);
size_t wave_size = queryWaveFrontSize(kernel);
char opt[32] = {0};
sprintf(opt, "-D WAVE_SIZE=%d", wave_size);
sprintf(opt, "-D WAVE_SIZE=%d", (int)wave_size);
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads,
localThreads, args, -1, -1, opt);
}
@ -1803,9 +1803,9 @@ void cv::ocl::device::hog::classify_hists(int win_height, int win_width,
else
{
cl_kernel kernel = openCLGetKernelFromSource(clCxt, &objdetect_hog, kernelName);
int wave_size = queryDeviceInfo<WAVEFRONT_SIZE, int>(kernel);
size_t wave_size = queryWaveFrontSize(kernel);
char opt[32] = {0};
sprintf(opt, "-D WAVE_SIZE=%d", wave_size);
sprintf(opt, "-D WAVE_SIZE=%d", (int)wave_size);
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads,
localThreads, args, -1, -1, opt);
}

38
modules/ocl/src/imgproc.cpp
View File

@ -289,7 +289,7 @@ namespace cv
args.push_back( make_pair(sizeof(cl_int), (void *)&map1.rows));
args.push_back( make_pair(sizeof(cl_int), (void *)&cols));
if(src.clCxt->supportsFeature(Context::CL_DOUBLE))
if(src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
{
args.push_back( make_pair(sizeof(cl_double4), (void *)&borderValue));
}
@ -317,7 +317,7 @@ namespace cv
args.push_back( make_pair(sizeof(cl_int), (void *)&map1.cols));
args.push_back( make_pair(sizeof(cl_int), (void *)&map1.rows));
args.push_back( make_pair(sizeof(cl_int), (void *)&cols));
if(src.clCxt->supportsFeature(Context::CL_DOUBLE))
if(src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
{
args.push_back( make_pair(sizeof(cl_double4), (void *)&borderValue));
}
@ -380,7 +380,7 @@ namespace cv
args.push_back( make_pair(sizeof(cl_int), (void *)&src.rows));
args.push_back( make_pair(sizeof(cl_int), (void *)&dst.cols));
args.push_back( make_pair(sizeof(cl_int), (void *)&dst.rows));
if(src.clCxt->supportsFeature(Context::CL_DOUBLE))
if(src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
{
args.push_back( make_pair(sizeof(cl_double), (void *)&ifx_d));
args.push_back( make_pair(sizeof(cl_double), (void *)&ify_d));
@ -802,12 +802,12 @@ namespace cv
string kernelName = "warpAffine" + s[interpolation];
if(src.clCxt->supportsFeature(Context::CL_DOUBLE))
if(src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
{
cl_int st;
coeffs_cm = clCreateBuffer( (cl_context)clCxt->oclContext(), CL_MEM_READ_WRITE, sizeof(F) * 2 * 3, NULL, &st );
coeffs_cm = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE, sizeof(F) * 2 * 3, NULL, &st );
openCLVerifyCall(st);
openCLSafeCall(clEnqueueWriteBuffer((cl_command_queue)clCxt->oclCommandQueue(), (cl_mem)coeffs_cm, 1, 0, sizeof(F) * 2 * 3, coeffs, 0, 0, 0));
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm, 1, 0, sizeof(F) * 2 * 3, coeffs, 0, 0, 0));
}
else
{
@ -817,8 +817,8 @@ namespace cv
{
float_coeffs[m][n] = coeffs[m][n];
}
coeffs_cm = clCreateBuffer( (cl_context)clCxt->oclContext(), CL_MEM_READ_WRITE, sizeof(float) * 2 * 3, NULL, &st );
openCLSafeCall(clEnqueueWriteBuffer((cl_command_queue)clCxt->oclCommandQueue(), (cl_mem)coeffs_cm, 1, 0, sizeof(float) * 2 * 3, float_coeffs, 0, 0, 0));
coeffs_cm = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE, sizeof(float) * 2 * 3, NULL, &st );
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm, 1, 0, sizeof(float) * 2 * 3, float_coeffs, 0, 0, 0));
}
//TODO: improve this kernel
@ -872,12 +872,12 @@ namespace cv
string s[3] = {"NN", "Linear", "Cubic"};
string kernelName = "warpPerspective" + s[interpolation];
if(src.clCxt->supportsFeature(Context::CL_DOUBLE))
if(src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
{
cl_int st;
coeffs_cm = clCreateBuffer((cl_context) clCxt->oclContext(), CL_MEM_READ_WRITE, sizeof(double) * 3 * 3, NULL, &st );
coeffs_cm = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE, sizeof(double) * 3 * 3, NULL, &st );
openCLVerifyCall(st);
openCLSafeCall(clEnqueueWriteBuffer((cl_command_queue)clCxt->oclCommandQueue(), (cl_mem)coeffs_cm, 1, 0, sizeof(double) * 3 * 3, coeffs, 0, 0, 0));
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm, 1, 0, sizeof(double) * 3 * 3, coeffs, 0, 0, 0));
}
else
{
@ -886,9 +886,9 @@ namespace cv
for(int n = 0; n < 3; n++)
float_coeffs[m][n] = coeffs[m][n];
coeffs_cm = clCreateBuffer((cl_context) clCxt->oclContext(), CL_MEM_READ_WRITE, sizeof(float) * 3 * 3, NULL, &st );
coeffs_cm = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE, sizeof(float) * 3 * 3, NULL, &st );
openCLVerifyCall(st);
openCLSafeCall(clEnqueueWriteBuffer((cl_command_queue)clCxt->oclCommandQueue(), (cl_mem)coeffs_cm, 1, 0, sizeof(float) * 3 * 3, float_coeffs, 0, 0, 0));
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm, 1, 0, sizeof(float) * 3 * 3, float_coeffs, 0, 0, 0));
}
//TODO: improve this kernel
size_t blkSizeX = 16, blkSizeY = 16;
@ -994,7 +994,7 @@ namespace cv
void integral(const oclMat &src, oclMat &sum, oclMat &sqsum)
{
CV_Assert(src.type() == CV_8UC1);
if(!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.depth() == CV_64F)
if(!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "select device don't support double");
}
@ -1192,7 +1192,7 @@ namespace cv
void cornerHarris_dxdy(const oclMat &src, oclMat &dst, oclMat &dx, oclMat &dy, int blockSize, int ksize,
double k, int borderType)
{
if(!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.depth() == CV_64F)
if(!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "select device don't support double");
}
@ -1211,7 +1211,7 @@ namespace cv
void cornerMinEigenVal_dxdy(const oclMat &src, oclMat &dst, oclMat &dx, oclMat &dy, int blockSize, int ksize, int borderType)
{
if(!src.clCxt->supportsFeature(Context::CL_DOUBLE) && src.depth() == CV_64F)
if(!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "select device don't support double");
}
@ -1512,17 +1512,17 @@ namespace cv
String kernelName = "calcLut";
size_t localThreads[3] = { 32, 8, 1 };
size_t globalThreads[3] = { tilesX * localThreads[0], tilesY * localThreads[1], 1 };
bool is_cpu = queryDeviceInfo<IS_CPU_DEVICE, bool>();
bool is_cpu = isCpuDevice();
if (is_cpu)
openCLExecuteKernel(Context::getContext(), &imgproc_clahe, kernelName, globalThreads, localThreads, args, -1, -1, (char*)" -D CPU");
else
{
cl_kernel kernel = openCLGetKernelFromSource(Context::getContext(), &imgproc_clahe, kernelName);
int wave_size = queryDeviceInfo<WAVEFRONT_SIZE, int>(kernel);
size_t wave_size = queryWaveFrontSize(kernel);
openCLSafeCall(clReleaseKernel(kernel));
static char opt[20] = {0};
sprintf(opt, " -D WAVE_SIZE=%d", wave_size);
sprintf(opt, " -D WAVE_SIZE=%d", (int)wave_size);
openCLExecuteKernel(Context::getContext(), &imgproc_clahe, kernelName, globalThreads, localThreads, args, -1, -1, opt);
}
}

1090
modules/ocl/src/initialization.cpp
View File

File diff suppressed because it is too large Load Diff

14
modules/ocl/src/knearest.cpp
View File

@ -44,17 +44,11 @@
//M*/
#include "precomp.hpp"
#include "opencl_kernels.hpp"
using namespace cv;
using namespace cv::ocl;
namespace cv
{
namespace ocl
{
extern const char* knearest;//knearest
}
}
KNearestNeighbour::KNearestNeighbour()
{
clear();
@ -112,7 +106,7 @@ void KNearestNeighbour::find_nearest(const oclMat& samples, int k, oclMat& lable
k1 = MIN( k1, k );
String kernel_name = "knn_find_nearest";
cl_ulong local_memory_size = queryLocalMemInfo();
cl_ulong local_memory_size = (cl_ulong)Context::getContext()->getDeviceInfo().localMemorySize;
int nThreads = local_memory_size / (2 * k * 4);
if(nThreads >= 256)
nThreads = 256;
@ -122,7 +116,7 @@ void KNearestNeighbour::find_nearest(const oclMat& samples, int k, oclMat& lable
size_t global_thread[] = {1, samples.rows, 1};
char build_option[50];
if(!Context::getContext()->supportsFeature(Context::CL_DOUBLE))
if(!Context::getContext()->supportsFeature(FEATURE_CL_DOUBLE))
{
sprintf(build_option, " ");
}else

13
modules/ocl/src/matrix_operations.cpp
View File

@ -134,7 +134,6 @@ void cv::ocl::oclMat::upload(const Mat &m)
Size wholeSize;
Point ofs;
m.locateROI(wholeSize, ofs);
create(wholeSize, m.type());
if (m.channels() == 3)
@ -142,13 +141,12 @@ void cv::ocl::oclMat::upload(const Mat &m)
int pitch = wholeSize.width * 3 * m.elemSize1();
int tail_padding = m.elemSize1() * 3072;
int err;
cl_mem temp = clCreateBuffer((cl_context)clCxt->oclContext(), CL_MEM_READ_WRITE,
cl_mem temp = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE,
(pitch * wholeSize.height + tail_padding - 1) / tail_padding * tail_padding, 0, &err);
openCLVerifyCall(err);
openCLMemcpy2D(clCxt, temp, pitch, m.datastart, m.step, wholeSize.width * m.elemSize(), wholeSize.height, clMemcpyHostToDevice, 3);
convert_C3C4(temp, *this);
openCLSafeCall(clReleaseMemObject(temp));
}
else
@ -197,13 +195,12 @@ void cv::ocl::oclMat::download(cv::Mat &m) const
int pitch = wholecols * 3 * m.elemSize1();
int tail_padding = m.elemSize1() * 3072;
int err;
cl_mem temp = clCreateBuffer((cl_context)clCxt->oclContext(), CL_MEM_READ_WRITE,
cl_mem temp = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE,
(pitch * wholerows + tail_padding - 1) / tail_padding * tail_padding, 0, &err);
openCLVerifyCall(err);
convert_C4C3(*this, temp);
openCLMemcpy2D(clCxt, m.data, m.step, temp, pitch, wholecols * m.elemSize(), wholerows, clMemcpyDeviceToHost, 3);
openCLSafeCall(clReleaseMemObject(temp));
}
else
@ -319,7 +316,7 @@ static void convert_run(const oclMat &src, oclMat &dst, double alpha, double bet
void cv::ocl::oclMat::convertTo( oclMat &dst, int rtype, double alpha, double beta ) const
{
if (!clCxt->supportsFeature(Context::CL_DOUBLE) &&
if (!clCxt->supportsFeature(FEATURE_CL_DOUBLE) &&
(depth() == CV_64F || dst.depth() == CV_64F))
{
CV_Error(CV_GpuNotSupported, "Selected device don't support double\r\n");
@ -380,7 +377,7 @@ static void set_to_withoutmask_run(const oclMat &dst, const Scalar &scalar, stri
#ifdef CL_VERSION_1_2
// this enables backwards portability to
// run on OpenCL 1.1 platform if library binaries are compiled with OpenCL 1.2 support
if (Context::getContext()->supportsFeature(Context::CL_VER_1_2) &&
if (Context::getContext()->supportsFeature(FEATURE_CL_VER_1_2) &&
dst.offset == 0 && dst.cols == dst.wholecols)
{
const int sizeofMap[][7] =
@ -392,7 +389,7 @@ static void set_to_withoutmask_run(const oclMat &dst, const Scalar &scalar, stri
};
int sizeofGeneric = sizeofMap[dst.oclchannels() - 1][dst.depth()];
clEnqueueFillBuffer((cl_command_queue)dst.clCxt->oclCommandQueue(),
clEnqueueFillBuffer(getClCommandQueue(dst.clCxt),
(cl_mem)dst.data, (void*)mat.data, sizeofGeneric,
0, dst.step * dst.rows, 0, NULL, NULL);
}

24
modules/ocl/src/mcwutil.cpp
View File

@ -101,15 +101,15 @@ namespace cv
for(size_t i = 0; i < args.size(); i ++)
openCLSafeCall(clSetKernelArg(kernel, i, args[i].first, args[i].second));
openCLSafeCall(clEnqueueNDRangeKernel((cl_command_queue)clCxt->oclCommandQueue(), kernel, 3, NULL, globalThreads,
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), kernel, 3, NULL, globalThreads,
localThreads, 0, NULL, NULL));
switch(finish_mode)
{
case CLFINISH:
clFinish((cl_command_queue)clCxt->oclCommandQueue());
clFinish(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr());
case CLFLUSH:
clFlush((cl_command_queue)clCxt->oclCommandQueue());
clFlush(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr());
break;
case DISABLE:
default:
@ -178,7 +178,7 @@ namespace cv
#ifdef CL_VERSION_1_2
//this enables backwards portability to
//run on OpenCL 1.1 platform if library binaries are compiled with OpenCL 1.2 support
if(Context::getContext()->supportsFeature(Context::CL_VER_1_2))
if(Context::getContext()->supportsFeature(FEATURE_CL_VER_1_2))
{
cl_image_desc desc;
desc.image_type = CL_MEM_OBJECT_IMAGE2D;
@ -191,13 +191,13 @@ namespace cv
desc.buffer = NULL;
desc.num_mip_levels = 0;
desc.num_samples = 0;
texture = clCreateImage((cl_context)mat.clCxt->oclContext(), CL_MEM_READ_WRITE, &format, &desc, NULL, &err);
texture = clCreateImage(*(cl_context*)mat.clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE, &format, &desc, NULL, &err);
}
else
#endif
{
texture = clCreateImage2D(
(cl_context)mat.clCxt->oclContext(),
*(cl_context*)mat.clCxt->getOpenCLContextPtr(),
CL_MEM_READ_WRITE,
&format,
mat.cols,
@ -212,22 +212,22 @@ namespace cv
cl_mem devData;
if (mat.cols * mat.elemSize() != mat.step)
{
devData = clCreateBuffer((cl_context)mat.clCxt->oclContext(), CL_MEM_READ_ONLY, mat.cols * mat.rows
devData = clCreateBuffer(*(cl_context*)mat.clCxt->getOpenCLContextPtr(), CL_MEM_READ_ONLY, mat.cols * mat.rows
* mat.elemSize(), NULL, NULL);
const size_t regin[3] = {mat.cols * mat.elemSize(), mat.rows, 1};
clEnqueueCopyBufferRect((cl_command_queue)mat.clCxt->oclCommandQueue(), (cl_mem)mat.data, devData, origin, origin,
clEnqueueCopyBufferRect(*(cl_command_queue*)mat.clCxt->getOpenCLCommandQueuePtr(), (cl_mem)mat.data, devData, origin, origin,
regin, mat.step, 0, mat.cols * mat.elemSize(), 0, 0, NULL, NULL);
clFlush((cl_command_queue)mat.clCxt->oclCommandQueue());
clFlush(*(cl_command_queue*)mat.clCxt->getOpenCLCommandQueuePtr());
}
else
{
devData = (cl_mem)mat.data;
}
clEnqueueCopyBufferToImage((cl_command_queue)mat.clCxt->oclCommandQueue(), devData, texture, 0, origin, region, 0, NULL, 0);
clEnqueueCopyBufferToImage(*(cl_command_queue*)mat.clCxt->getOpenCLCommandQueuePtr(), devData, texture, 0, origin, region, 0, NULL, 0);
if ((mat.cols * mat.elemSize() != mat.step))
{
clFlush((cl_command_queue)mat.clCxt->oclCommandQueue());
clFlush(*(cl_command_queue*)mat.clCxt->getOpenCLCommandQueuePtr());
clReleaseMemObject(devData);
}
@ -259,7 +259,7 @@ namespace cv
try
{
cv::ocl::openCLGetKernelFromSource(clCxt, &_kernel_string, "test_func");
finish();
cv::ocl::finish();
_support = true;
}
catch (const cv::Exception& e)

4
modules/ocl/src/moments.cpp
View File

@ -106,7 +106,7 @@ static void icvContourMoments( CvSeq* contour, CvMoments* mom )
bool is_float = CV_SEQ_ELTYPE(contour) == CV_32FC2;
if (!cv::ocl::Context::getContext()->supportsFeature(Context::CL_DOUBLE) && is_float)
if (!cv::ocl::Context::getContext()->supportsFeature(FEATURE_CL_DOUBLE) && is_float)
{
CV_Error(CV_StsUnsupportedFormat, "Moments - double is not supported by your GPU!");
}
@ -146,7 +146,7 @@ static void icvContourMoments( CvSeq* contour, CvMoments* mom )
cv::Mat dst(dst_a);
a00 = a10 = a01 = a20 = a11 = a02 = a30 = a21 = a12 = a03 = 0.0;
if (!cv::ocl::Context::getContext()->supportsFeature(Context::CL_DOUBLE))
if (!cv::ocl::Context::getContext()->supportsFeature(FEATURE_CL_DOUBLE))
{
for (int i = 0; i < contour->total; ++i)
{

4
modules/ocl/src/pyrdown.cpp
View File

@ -15,8 +15,8 @@
// Third party copyrights are property of their respective owners.
//
// @Authors
// Dachuan Zhao, dachuan@multicorewareinc.com
// Yao Wang, yao@multicorewareinc.com
// Dachuan Zhao, dachuan@multicorewareinc.com
// Yao Wang, yao@multicorewareinc.com
//
//
// Redistribution and use in source and binary forms, with or without modification,

4
modules/ocl/src/pyrlk.cpp
View File

@ -125,7 +125,7 @@ static void lkSparse_run(oclMat &I, oclMat &J,
args.push_back( make_pair( sizeof(cl_int), (void *)&iters ));
args.push_back( make_pair( sizeof(cl_char), (void *)&calcErr ));
bool is_cpu = queryDeviceInfo<IS_CPU_DEVICE, bool>();
bool is_cpu = isCpuDevice();
if (is_cpu)
{
openCLExecuteKernel(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), (char*)" -D CPU");
@ -139,7 +139,7 @@ static void lkSparse_run(oclMat &I, oclMat &J,
stringstream idxStr;
idxStr << kernelName << "_C" << I.oclchannels() << "_D" << I.depth();
cl_kernel kernel = openCLGetKernelFromSource(clCxt, &pyrlk, idxStr.str());
int wave_size = queryDeviceInfo<WAVEFRONT_SIZE, int>(kernel);
int wave_size = (int)queryWaveFrontSize(kernel);
openCLSafeCall(clReleaseKernel(kernel));
static char opt[32] = {0};

4
modules/ocl/src/pyrup.cpp
View File

@ -15,8 +15,8 @@
// Third party copyrights are property of their respective owners.
//
// @Authors
// Zhang Chunpeng chunpeng@multicorewareinc.com
// Yao Wang, yao@multicorewareinc.com
// Zhang Chunpeng chunpeng@multicorewareinc.com
// Yao Wang, yao@multicorewareinc.com
//
//
// Redistribution and use in source and binary forms, with or without modification,

4
modules/ocl/src/split_merge.cpp
View File

@ -75,7 +75,7 @@ namespace cv
{
static void merge_vector_run(const oclMat *mat_src, size_t n, oclMat &mat_dst)
{
if(!mat_dst.clCxt->supportsFeature(Context::CL_DOUBLE) && mat_dst.type() == CV_64F)
if(!mat_dst.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && mat_dst.type() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device don't support double\r\n");
return;
@ -170,7 +170,7 @@ namespace cv
static void split_vector_run(const oclMat &mat_src, oclMat *mat_dst)
{
if(!mat_src.clCxt->supportsFeature(Context::CL_DOUBLE) && mat_src.type() == CV_64F)
if(!mat_src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && mat_src.type() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device don't support double\r\n");
return;

36
modules/ocl/src/stereo_csbp.cpp
View File

@ -150,10 +150,10 @@ namespace cv
openCLSafeCall(clSetKernelArg(kernel, 11, sizeof(cl_int), (void *)&rthis.min_disp_th));
openCLSafeCall(clSetKernelArg(kernel, 12, sizeof(cl_int), (void *)&left.step));
openCLSafeCall(clSetKernelArg(kernel, 13, sizeof(cl_int), (void *)&rthis.ndisp));
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getoclCommandQueue(), kernel, 2, NULL,
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getClCommandQueuePtr(), kernel, 2, NULL,
globalThreads, localThreads, 0, NULL, NULL));
clFinish(*(cl_command_queue*)getoclCommandQueue());
clFinish(*(cl_command_queue*)getClCommandQueuePtr());
openCLSafeCall(clReleaseKernel(kernel));
}
@ -200,9 +200,9 @@ namespace cv
openCLSafeCall(clSetKernelArg(kernel, 14, sizeof(cl_int), (void *)&rthis.min_disp_th));
openCLSafeCall(clSetKernelArg(kernel, 15, sizeof(cl_int), (void *)&cdisp_step1));
openCLSafeCall(clSetKernelArg(kernel, 16, sizeof(cl_int), (void *)&msg_step));
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getoclCommandQueue(), kernel, 3, NULL,
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getClCommandQueuePtr(), kernel, 3, NULL,
globalThreads, localThreads, 0, NULL, NULL));
clFinish(*(cl_command_queue*)getoclCommandQueue());
clFinish(*(cl_command_queue*)getClCommandQueuePtr());
openCLSafeCall(clReleaseKernel(kernel));
}
@ -235,10 +235,10 @@ namespace cv
openCLSafeCall(clSetKernelArg(kernel, 6, sizeof(cl_int), (void *)&msg_step));
openCLSafeCall(clSetKernelArg(kernel, 7, sizeof(cl_int), (void *)&disp_step));
openCLSafeCall(clSetKernelArg(kernel, 8, sizeof(cl_int), (void *)&rthis.ndisp));
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getoclCommandQueue(), kernel, 2, NULL,
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getClCommandQueuePtr(), kernel, 2, NULL,
globalThreads, localThreads, 0, NULL, NULL));
clFinish(*(cl_command_queue*)getoclCommandQueue());
clFinish(*(cl_command_queue*)getClCommandQueuePtr());
openCLSafeCall(clReleaseKernel(kernel));
}
static void get_first_initial_global_caller(uchar *data_cost_selected, uchar *disp_selected_pyr,
@ -270,10 +270,10 @@ namespace cv
openCLSafeCall(clSetKernelArg(kernel, 6, sizeof(cl_int), (void *)&msg_step));
openCLSafeCall(clSetKernelArg(kernel, 7, sizeof(cl_int), (void *)&disp_step));
openCLSafeCall(clSetKernelArg(kernel, 8, sizeof(cl_int), (void *)&rthis.ndisp));
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getoclCommandQueue(), kernel, 2, NULL,
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getClCommandQueuePtr(), kernel, 2, NULL,
globalThreads, localThreads, 0, NULL, NULL));
clFinish(*(cl_command_queue*)getoclCommandQueue());
clFinish(*(cl_command_queue*)getClCommandQueuePtr());
openCLSafeCall(clReleaseKernel(kernel));
}
@ -340,10 +340,10 @@ namespace cv
openCLSafeCall(clSetKernelArg(kernel, 14, sizeof(cl_float), (void *)&rthis.max_data_term));
openCLSafeCall(clSetKernelArg(kernel, 15, sizeof(cl_int), (void *)&left.step));
openCLSafeCall(clSetKernelArg(kernel, 16, sizeof(cl_int), (void *)&rthis.min_disp_th));
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getoclCommandQueue(), kernel, 2, NULL,
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getClCommandQueuePtr(), kernel, 2, NULL,
globalThreads, localThreads, 0, NULL, NULL));
clFinish(*(cl_command_queue*)getoclCommandQueue());
clFinish(*(cl_command_queue*)getClCommandQueuePtr());
openCLSafeCall(clReleaseKernel(kernel));
}
static void compute_data_cost_reduce_caller(uchar *disp_selected_pyr, uchar *data_cost,
@ -391,10 +391,10 @@ namespace cv
openCLSafeCall(clSetKernelArg(kernel, 17, sizeof(cl_float), (void *)&rthis.max_data_term));
openCLSafeCall(clSetKernelArg(kernel, 18, sizeof(cl_int), (void *)&left.step));
openCLSafeCall(clSetKernelArg(kernel, 19, sizeof(cl_int), (void *)&rthis.min_disp_th));
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getoclCommandQueue(), kernel, 3, NULL,
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getClCommandQueuePtr(), kernel, 3, NULL,
globalThreads, localThreads, 0, NULL, NULL));
clFinish(*(cl_command_queue*)getoclCommandQueue());
clFinish(*(cl_command_queue*)getClCommandQueuePtr());
openCLSafeCall(clReleaseKernel(kernel));
}
static void compute_data_cost(uchar *disp_selected_pyr, uchar *data_cost, StereoConstantSpaceBP &rthis,
@ -458,10 +458,10 @@ namespace cv
openCLSafeCall(clSetKernelArg(kernel, 20, sizeof(cl_int), (void *)&disp_step2));
openCLSafeCall(clSetKernelArg(kernel, 21, sizeof(cl_int), (void *)&msg_step1));
openCLSafeCall(clSetKernelArg(kernel, 22, sizeof(cl_int), (void *)&msg_step2));
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getoclCommandQueue(), kernel, 2, NULL,
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getClCommandQueuePtr(), kernel, 2, NULL,
globalThreads, localThreads, 0, NULL, NULL));
clFinish(*(cl_command_queue*)getoclCommandQueue());
clFinish(*(cl_command_queue*)getClCommandQueuePtr());
openCLSafeCall(clReleaseKernel(kernel));
}
////////////////////////////////////////////////////////////////////////////////////////////////
@ -500,10 +500,10 @@ namespace cv
openCLSafeCall(clSetKernelArg(kernel, 12, sizeof(cl_int), (void *)&disp_step));
openCLSafeCall(clSetKernelArg(kernel, 13, sizeof(cl_int), (void *)&msg_step));
openCLSafeCall(clSetKernelArg(kernel, 14, sizeof(cl_float), (void *)&rthis.disc_single_jump));
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getoclCommandQueue(), kernel, 2, NULL,
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getClCommandQueuePtr(), kernel, 2, NULL,
globalThreads, localThreads, 0, NULL, NULL));
clFinish(*(cl_command_queue*)getoclCommandQueue());
clFinish(*(cl_command_queue*)getClCommandQueuePtr());
openCLSafeCall(clReleaseKernel(kernel));
}
static void calc_all_iterations(uchar *u, uchar *d, uchar *l, uchar *r, uchar *data_cost_selected,
@ -552,10 +552,10 @@ namespace cv
openCLSafeCall(clSetKernelArg(kernel, 10, sizeof(cl_int), (void *)&nr_plane));
openCLSafeCall(clSetKernelArg(kernel, 11, sizeof(cl_int), (void *)&msg_step));
openCLSafeCall(clSetKernelArg(kernel, 12, sizeof(cl_int), (void *)&disp_step));
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getoclCommandQueue(), kernel, 2, NULL,
openCLSafeCall(clEnqueueNDRangeKernel(*(cl_command_queue*)getClCommandQueuePtr(), kernel, 2, NULL,
globalThreads, localThreads, 0, NULL, NULL));
clFinish(*(cl_command_queue*)getoclCommandQueue());
clFinish(*(cl_command_queue*)getClCommandQueuePtr());
openCLSafeCall(clReleaseKernel(kernel));
}
}

5
modules/ocl/src/stereobp.cpp
View File

@ -95,7 +95,10 @@ namespace cv
con_struct -> cmax_disc_term = max_disc_term;
con_struct -> cdisc_single_jump = disc_single_jump;
cl_con_struct = load_constant(*((cl_context*)getoclContext()), *((cl_command_queue*)getoclCommandQueue()), (void *)con_struct,
Context* clCtx = Context::getContext();
cl_context clContext = *(cl_context*)(clCtx->getOpenCLContextPtr());
cl_command_queue clCmdQueue = *(cl_command_queue*)(clCtx->getOpenCLCommandQueuePtr());
cl_con_struct = load_constant(clContext, clCmdQueue, (void *)con_struct,
sizeof(con_struct_t));
delete con_struct;

2
modules/ocl/src/tvl1flow.cpp
View File

@ -15,7 +15,7 @@
// Third party copyrights are property of their respective owners.
//
// @Authors
// Jin Ma, jin@multicorewareinc.com
// Jin Ma, jin@multicorewareinc.com
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//

35
modules/ocl/test/main.cpp
View File

@ -80,18 +80,18 @@ int main(int argc, char **argv)
const char *keys =
"{ h | help | false | print help message }"
"{ t | type | gpu | set device type:cpu or gpu}"
"{ p | platform | 0 | set platform id }"
"{ p | platform | -1 | set platform id }"
"{ d | device | 0 | set device id }";
CommandLineParser cmd(argc, argv, keys);
if (cmd.get<bool>("help"))
{
cout << "Avaible options besides goole test option:" << endl;
cout << "Available options besides google test option:" << endl;
cmd.printParams();
return 0;
}
string type = cmd.get<string>("type");
unsigned int pid = cmd.get<unsigned int>("platform");
int pid = cmd.get<int>("platform");
int device = cmd.get<int>("device");
print_info();
@ -100,24 +100,29 @@ int main(int argc, char **argv)
{
flag = CVCL_DEVICE_TYPE_CPU;
}
std::vector<cv::ocl::Info> oclinfo;
int devnums = getDevice(oclinfo, flag);
if(devnums <= device || device < 0)
cv::ocl::PlatformsInfo platformsInfo;
cv::ocl::getOpenCLPlatforms(platformsInfo);
if (pid >= (int)platformsInfo.size())
{
std::cout << "device invalid\n";
return -1;
}
if(pid >= oclinfo.size())
{
std::cout << "platform invalid\n";
return -1;
std::cout << "platform is invalid\n";
return 1;
}
setDevice(oclinfo[pid], device);
cv::ocl::DevicesInfo devicesInfo;
int devnums = cv::ocl::getOpenCLDevices(devicesInfo, flag, (pid < 0) ? NULL : platformsInfo[pid]);
if (device < 0 || device >= devnums)
{
std::cout << "device/platform invalid\n";
return 1;
}
cv::ocl::setDevice(devicesInfo[device]);
setBinaryDiskCache(CACHE_UPDATE);
cout << "Device type:" << type << endl << "Device name:" << oclinfo[pid].DeviceName[device] << endl;
cout << "Device type: " << type << endl
<< "Platform name: " << devicesInfo[device]->platform->platformName << endl
<< "Device name: " << devicesInfo[device]->deviceName << endl;
return RUN_ALL_TESTS();
}

3
modules/superres/perf/perf_superres_ocl.cpp
View File

@ -107,9 +107,6 @@ PERF_TEST_P(Size_MatType, SuperResolution_BTVL1_OCL,
Combine(Values(szSmall64, szSmall128),
Values(MatType(CV_8UC1), MatType(CV_8UC3))))
{
std::vector<cv::ocl::Info>info;
cv::ocl::getDevice(info);
declare.time(5 * 60);
const Size size = std::tr1::get<0>(GetParam());

2
modules/superres/src/btv_l1_ocl.cpp
View File

@ -232,7 +232,7 @@ void btv_l1_device_ocl::calcBtvRegularization(const oclMat& src, oclMat& dst, in
cl_mem c_btvRegWeights;
size_t count = btvWeights_size * sizeof(float);
c_btvRegWeights = openCLCreateBuffer(clCxt, CL_MEM_READ_ONLY, count);
int cl_safe_check = clEnqueueWriteBuffer((cl_command_queue)clCxt->oclCommandQueue(), c_btvRegWeights, 1, 0, count, btvWeights_, 0, NULL, NULL);
int cl_safe_check = clEnqueueWriteBuffer(getClCommandQueue(clCxt), c_btvRegWeights, 1, 0, count, btvWeights_, 0, NULL, NULL);
CV_Assert(cl_safe_check == CL_SUCCESS);
args.push_back(make_pair(sizeof(cl_mem), (void*)&src_.data));

2
modules/superres/test/test_superres.cpp
View File

@ -278,8 +278,6 @@ TEST_F(SuperResolution, BTVL1_GPU)
#if defined(HAVE_OPENCV_OCL) && defined(HAVE_OPENCL)
TEST_F(SuperResolution, BTVL1_OCL)
{
std::vector<cv::ocl::Info> infos;
cv::ocl::getDevice(infos);
RunTest(cv::superres::createSuperResolution_BTVL1_OCL());
}
#endif