C++ 多个类的DLL封装以及隐式链接和显式链接2种方法调用

//#define CREATEOPENCLDLL_EXPORTS #include <iostream> #include <fstream> #include <string> #include <vector> #include <sstream> #include <time.h> #include "createopencldll.h" using namespace std; const int KArraySize = 1000; CreateOpenCLDLL::CreateOpenCLDLL() { m_context = 0; m_commandQueue = 0; m_program = 0; m_device = 0; m_kernel = 0; m_memObjects[0] = 0; m_memObjects[1] = 0; m_memObjects[2] = 0; m_errNum = 0; } CreateOpenCLDLL::~CreateOpenCLDLL() { } // 选择平台并创建上下文 cl_context CreateOpenCLDLL::CreateContext() { cl_int errNum; cl_uint numPlatforms; cl_platform_id firstPlatformId; cl_context context = NULL; //选择第一个可用的平台 errNum = clGetPlatformIDs(1, &firstPlatformId, &numPlatforms); if (errNum != CL_SUCCESS || numPlatforms <= 0) { std::cerr << "Failed to find any OpenCL platforms." << std::endl; return NULL; } // 创建一个opencl上下文，成功则使用GUP上下文，否则使用cpu cl_context_properties contextProperties[] = { CL_CONTEXT_PLATFORM, (cl_context_properties)firstPlatformId, 0 }; context = clCreateContextFromType(contextProperties, CL_DEVICE_TYPE_GPU, NULL, NULL, &errNum); if (errNum != CL_SUCCESS) { std::cout << "Could not create GPU context, trying CPU..." << std::endl; context = clCreateContextFromType(contextProperties, CL_DEVICE_TYPE_CPU, NULL, NULL, &errNum); if (errNum != CL_SUCCESS) { std::cerr << "Failed to create an OpenCL GPU or CPU context." << std::endl; return NULL; } } return context; } //选择第一个可用的设备并创建一个命令队列 cl_command_queue CreateOpenCLDLL::CreateCommandQueue(cl_context context, cl_device_id *device) { cl_int errNum; cl_device_id *devices; cl_command_queue commandQueue = NULL; size_t deviceBufferSize = -1; //这个clGetContextInfo获得设备缓冲区的大小 errNum = clGetContextInfo(context, CL_CONTEXT_DEVICES, 0, NULL, &deviceBufferSize); if (errNum != CL_SUCCESS) { std::cerr << "Failed call to clGetContextInfo(...,GL_CONTEXT_DEVICES,...)"; return NULL; } if (deviceBufferSize <= 0) { std::cerr << "No devices available."; return NULL; } //为设备缓冲区分配内存，这个clGetContextInfo用来获得上下文中所有可用的设备 devices = new cl_device_id[deviceBufferSize / sizeof(cl_device_id)]; errNum = clGetContextInfo(context, CL_CONTEXT_DEVICES, deviceBufferSize, devices, NULL); if (errNum != CL_SUCCESS) { delete[] devices; std::cerr << "Failed to get device IDs"; return NULL; } char deviceName[512]; char deviceVendor[512]; char deviceVersion[512]; errNum = clGetDeviceInfo(devices[0], CL_DEVICE_VENDOR, sizeof(deviceVendor), deviceVendor, NULL); errNum |= clGetDeviceInfo(devices[0], CL_DEVICE_NAME, sizeof(deviceName), deviceName, NULL); errNum |= clGetDeviceInfo(devices[0], CL_DEVICE_VERSION, sizeof(deviceVersion), deviceVersion, NULL); printf("OpenCL Device Vendor = %s, OpenCL Device Name = %s, OpenCL Device Version = %s\n", deviceVendor, deviceName, deviceVersion); // 在这个例子中，我们只选择第一个可用的设备。在实际的程序，你可能会使用所有可用的设备或基于OpenCL设备查询选择性能最高的设备 commandQueue = clCreateCommandQueue(context, devices[0], 0, NULL); if (commandQueue == NULL) { delete[] devices; std::cerr << "Failed to create commandQueue for device 0"; return NULL; } *device = devices[0]; delete[] devices; return commandQueue; } //从磁盘加载内核源文件并创建一个程序对象 cl_program CreateOpenCLDLL::CreateProgram(cl_context context, cl_device_id device, const char* fileName) { cl_int errNum; cl_program program; std::ifstream kernelFile(fileName, std::ios::in); if (!kernelFile.is_open()) { std::cerr << "Failed to open file for reading: " << fileName << std::endl; return NULL; } std::ostringstream oss; oss << kernelFile.rdbuf(); std::string srcStdStr = oss.str(); const char *srcStr = srcStdStr.c_str(); //创建程序对象 program = clCreateProgramWithSource(context, 1, (const char**)&srcStr, NULL, NULL); if (program == NULL) { std::cerr << "Failed to create CL program from source." << std::endl; return NULL; } //编译内核源代码 errNum = clBuildProgram(program, 0, NULL, NULL, NULL, NULL); if (errNum != CL_SUCCESS) { // 编译失败可以通过clGetProgramBuildInfo获取日志 char buildLog[16384]; clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG, sizeof(buildLog), buildLog, NULL); std::cerr << "Error in kernel: " << std::endl; std::cerr << buildLog; clReleaseProgram(program); return NULL; } return program; } //创建内存对象 bool CreateOpenCLDLL::CreateMemObjects(cl_context context, cl_mem memObjects[3], float *a, float *b) { //创建内存对象 memObjects[0] = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, sizeof(float)* KArraySize, a, NULL); memObjects[1] = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, sizeof(float)* KArraySize, b, NULL); memObjects[2] = clCreateBuffer(context, CL_MEM_READ_WRITE, sizeof(float)* KArraySize, NULL, NULL); if (memObjects[0] == NULL || memObjects[1] == NULL || memObjects[2] == NULL) { std::cerr << "Error creating memory objects." << std::endl; return false; } return true; } //清理任何创建OpenCL的资源 void CreateOpenCLDLL::Cleanup(cl_context context, cl_command_queue commandQueue, cl_program program, cl_kernel kernel, cl_mem memObjects[3]) { for (int i = 0; i < 3; i++) { if (memObjects[i] != 0) clReleaseMemObject(memObjects[i]); } if (commandQueue != 0) clReleaseCommandQueue(commandQueue); if (kernel != 0) clReleaseKernel(kernel); if (program != 0) clReleaseProgram(program); if (context != 0) clReleaseContext(context); } void CreateOpenCLDLL::Calcaute() { // 创建opencl上下文和第一个可用平台 m_context = CreateContext(); if (m_context == NULL) { std::cerr << "Failed to create OpenCL context." << std::endl; } // 在创建的一个上下文中选择第一个可用的设备并创建一个命令队列 m_commandQueue = CreateCommandQueue(m_context, &m_device); if (m_commandQueue == NULL) { Cleanup(m_context, m_commandQueue, m_program, m_kernel, m_memObjects); } // 创建一个程序对象 HelloWorld.cl kernel source m_program = CreateProgram(m_context, m_device, "HelloWorld.cl"); if (m_program == NULL) { Cleanup(m_context, m_commandQueue, m_program, m_kernel, m_memObjects); } // 创建内核 m_kernel = clCreateKernel(m_program, "hello_kernel", NULL); if (m_kernel == NULL) { std::cerr << "Failed to create kernel" << std::endl; Cleanup(m_context, m_commandQueue, m_program, m_kernel, m_memObjects); } // 创建一个将用作参数内核内存中的对象。首先创建将被用来将参数存储到内核主机存储器阵列 float result[KArraySize]; float a[KArraySize]; float b[KArraySize]; for (int i = 0; i < KArraySize; i++) { a[i] = (float)i; b[i] = (float)(i * 2); } if (!CreateMemObjects(m_context, m_memObjects, a, b)) { Cleanup(m_context, m_commandQueue, m_program, m_kernel, m_memObjects); } // 设置内核参数、执行内核并读回结果 m_errNum = clSetKernelArg(m_kernel, 0, sizeof(cl_mem), &m_memObjects[0]); m_errNum |= clSetKernelArg(m_kernel, 1, sizeof(cl_mem), &m_memObjects[1]); m_errNum |= clSetKernelArg(m_kernel, 2, sizeof(cl_mem), &m_memObjects[2]); if (m_errNum != CL_SUCCESS) { std::cerr << "Error setting kernel arguments." << std::endl; Cleanup(m_context, m_commandQueue, m_program, m_kernel, m_memObjects); } size_t globalWorkSize[1] = { KArraySize };//让之等于数组的大小 size_t localWorkSize[1] = { 1 }; //让之等于1 // 利用命令队列使将在设备执行的内核排队 m_errNum = clEnqueueNDRangeKernel(m_commandQueue, m_kernel, 1, NULL, globalWorkSize, localWorkSize, 0, NULL, NULL); if (