host多线程下OpenCL平台等单例

/* * PrepareOpenCL.cpp * * Created on: 2017年8月10日 * Author: root */ #include "PrepareOpenCL.hpp" prepareing::prepareing():rgbarray(new uchar[256*256*256]),rgbsize(256*256*256), imgheight(1456),imgwidth(1936),mysize(cvSize(1936,1456)), srcdatasize(1456*1936*3*sizeof(uchar)),dstdatasize(1456*1936*sizeof(uchar)), rgbArray_buffer(NULL),kernel_imgProc(NULL),device(NULL), context(NULL),program(NULL) { boost::mutex::scoped_lock lock(initMutex); memset(rgbarray, 0, rgbsize * sizeof(uchar)); Ptr<ml::TrainData> mlData2=cv::ml::TrainData::loadFromCSV("/home/jumper/Ore_projects/multiThreadsFluoreOpenCL/fluore_0728pm.csv",0,-2,0); cv::Mat csvimg2=mlData2->getSamples(); int csvrows2 = csvimg2.rows; for (int j = 0; j < csvrows2; j++){ float* pixeldata = csvimg2.ptr<float>(j); float x = pixeldata[0]; float y = pixeldata[1]; float z = pixeldata[2]; int newindex = x + y * 256 + z * 256 * 256; rgbarray[newindex] = 255; } //"prepare for running the OpenCL partion..."; cl_uint platformNum; cl_int status; status=clGetPlatformIDs(0,NULL,&platformNum); if(status!=CL_SUCCESS){ printf("Error:cannot get platforms number.\n"); } cl_platform_id platforms[1]; status=clGetPlatformIDs(platformNum,platforms,NULL); if(status!=CL_SUCCESS){ printf("Error:cannot get platforms addresses.\n"); } cl_platform_id platformInUse=platforms[0]; clGetDeviceIDs(platformInUse,CL_DEVICE_TYPE_GPU,1,&device,NULL); context=clCreateContext(NULL,1,&device,NULL,NULL,NULL); std::ifstream srcFile("/home/jumper/Ore_projects/multiThreadsFluoreOpenCL/forFluore.cl"); std::string srcProg(std::istreambuf_iterator<char>(srcFile),(std::istreambuf_iterator<char>())); const char * src = srcProg.c_str(); size_t length = srcProg.length(); program=clCreateProgramWithSource(context,1,&src,&length,&status); status=clBuildProgram(program,1,&device,NULL,NULL,NULL); if (status != CL_SUCCESS) { printf("Error:clBuildProgram()...\n"); shrLogEx(LOGBOTH | ERRORMSG, status, STDERROR); oclLogBuildInfo(program, oclGetFirstDev(context)); oclLogPtx(program, oclGetFirstDev(context), "oclfluore.ptx"); } rgbArray_buffer=clCreateBuffer(context,CL_MEM_READ_ONLY,rgbsize*sizeof(uchar),rgbarray,&status); //cout<<"srcdatasize in PrepareOpenCL..."<<srcdatasize<<endl; for(int i=0;i<threadsnum;i++) //number of threads { queue[i]=clCreateCommandQueue(context,device,CL_QUEUE_PROFILING_ENABLE,NULL); status=clEnqueueWriteBuffer(queue[i], rgbArray_buffer, CL_FALSE, 0, rgbsize* sizeof(uchar),rgbarray, 0, NULL, NULL); srcdata_buffer[i] = clCreateBuffer(context, CL_MEM_READ_ONLY, srcdatasize, NULL,NULL); dstdata_buffer[i] = clCreateBuffer(context, CL_MEM_WRITE_ONLY| CL_MEM_ALLOC_HOST_PTR, dstdatasize, NULL,NULL); } kernel_imgProc=clCreateKernel(program,"imgProcess",&status); status = clSetKernelArg(kernel_imgProc, 0, sizeof(cl_mem), (void*)&rgbArray_buffer); status = clSetKernelArg(kernel_imgProc, 3, sizeof(cl_int), &imgwidth); status = clSetKernelArg(kernel_imgProc, 4, sizeof(cl_int), &imgheight); if(status!=CL_SUCCESS) { cout<<"common resources failed..."<<status<<endl; } } void prepareing::initCommonResource() { } prepareing& prepareing::operator=(const prepareing &rhs) { imgwidth=rhs.imgwidth; imgheight=rhs.imgheight; mysize=rhs.mysize; rgbsize=rhs.rgbsize; device=rhs.device; program=rhs.program; context=rhs.context; kernel_imgProc=rhs.kernel_imgProc; rgbArray_buffer=rhs.rgbArray_buffer; srcdatasize=rhs.srcdatasize; dstdatasize=rhs.dstdatasize; if(rgbarray==NULL) rgbarray=new uchar[rgbsize]; for(int j=0;j<rgbsize;j++) rgbarray[j]=rhs.rgbarray[j]; for(int i=0;i<5;i++) { queue[i]=rhs.queue[i]; srcdata_buffer[i]=rhs.srcdata_buffer[i]; dstdata_buffer[i]=rhs.dstdata_buffer[i]; } return *this; } //int prepareing::getimgwidth() //{ // return imgwidth; //} //int prepareing::getimgheight() //{ // return imgheight; //} //CvSize prepareing::getmysize() //{ // return mysize; //} //int prepareing::getrgbsize() //{ // return rgbsize; //} // //cl_device_id prepareing::getdevice() //{ // return device; //} //cl_program prepareing::getprogram() //{ // return program; //} //cl_context prepareing::getcontext() //{ // return context; //} //int prepareing::getsrcdatasize() //{ // return srcdatasize; //} //int prepareing::getdstdatasize() //{ // return dstdatasize; //} //cl_kernel prepareing::getkernel_imgProc() //{ // return kernel_imgProc; //} //cl_mem prepareing::getrgbArray_buffer() //{ // return rgbArray_buffer; //} //uchar* prepareing::getrgbarray() //{ // uchar *rgbreturn=new uchar[rgbsize]; //??????? // for(int j=0;j<rgbsize;j++) // rgbreturn[j]=rgbarray[j]; // return rgbreturn; //} //cl_command_queue* prepareing::getqueue() //{ // // cl_command_queue queuereturn[threadsnum]; // for(int j=0;j<threadsnum;j++) // queuereturn[j]=queue[j]; // return queuereturn; //} //cl_mem* prepareing::getsrcdata_buffer() //{ // cl_mem srcdata_bufferreturn[threadsnum]; // for(int j=0;j<threadsnum;j++) // srcdata_bufferreturn[j]=srcdata_buffer[j]; // return srcdata_bufferreturn; //} // //cl_mem* prepareing::getdstdata_buffer() //{ // cl_mem dstdata_bufferreturn[threadsnum]; // for(int j=0;j<threadsnum;j++) // dstdata_bufferreturn[j]=dstdata_buffer[j]; // return dstdata_bufferreturn; //} prepareing::~prepareing() { if(rgbarray) delete [] rgbarray; clReleaseContext(context); clReleaseProgram(program); clReleaseKernel(kernel_imgProc); for(int i=0;i<threadsnum;i++) { clReleaseCommandQueue(queue[i]); clReleaseMemObject(dstdata_buffer[i]); clReleaseMemObject(srcdata_buffer[i]); } clReleaseMemObject(rgbArray_buffer); } //void prepareing::init() //{ // public_resource common_obj; // common_obj.rgbsize=256*256*256; // common_obj.imgheight=1456; // common_obj.imgwidth=1936; // common_obj.mysize = cvSize(common_obj.imgwidth, common_obj.imgheight); // common_obj.rgbarray = new uchar[256*256*256]; // // memset(common_obj.rgbarray, 0, common_obj.rgbsize * sizeof(uchar)); // Ptr<ml::TrainData> mlData2=cv::ml::TrainData::loadFromCSV("/home/jumper/Ore_projects/multiThreadsFluoreOpenCL/fluore_0728pm.csv",0,-2,0); // cv::Mat csvimg2=mlData2->getSamples(); // int csvrows2 = csvimg2.rows; // for (int j = 0; j < csvrows2; j++){ // float* pixeldata = csvimg2.ptr<float>(j); // float x = pixeldata[0]; // float y = pixeldata[1]; // float z = pixeldata[2]; // int newindex = x + y * 256 + z * 256 * 256; // common_obj.rgbarray[newindex] = 255; // } // // //"prepare for running the OpenCL partion..."; // cl_uint platformNum; // cl_int status; // status=clGetPlatformIDs(0,NULL,&platformNum); // if(status!=CL_SUCCESS){ // printf("Error:cannot get platforms number.\n"); // } // cl_platform_id platforms[1]; // status=clGetPlatformIDs(platformNum,platforms,NULL); // if(status!=CL_SUCCESS){ // printf("Error:cannot get platforms addresses.\n"); // } // cl_platform_id platformInUse=platforms[0]; // // clGetDeviceIDs(platformInUse,CL_DEVICE_TYPE_GPU,1,&(common_obj.device),NULL); // common_obj.context=clCreateContext(NULL,1,&(common_obj.device),NULL,NULL,NULL); // // // std::ifstream srcFile("/home/jumper/Ore_projects/multiThreadsFluoreOpenCL/forFluore.cl"); // std::string srcProg(std::istreambuf_iterator<char>(srcFile),(std::istreambuf_iterator<char>())); // const char * src = srcProg.c_str(); // size_t length = srcProg.length(); // common_obj.program=clCreateProgramWithSource(common_obj.context,1,&src,&length,&status); // status=clBuildProgram(common_obj.program,1,&(common_obj.device),NULL,NULL,NULL); // if (status != CL_SUCCESS) // { // printf("Error:clBuildProgram()...\n"); // shrLogEx(LOGBOTH | ERRORMSG, status, STDERROR); // oclLogBuildInfo(common_obj.program, oclGetFirstDev(common_obj.context)); // oclLogPtx(common_obj.program, oclGetFirstDev(common_obj.context), "oclfluore.ptx"); // } // // int pixels=(common_obj.imgheight)*(common_obj.imgwidth); // common_obj.srcdatasize=pixels*3*sizeof(uchar