配置VS invida OpenCL环境

 

1. 安装CUDA安装包

 

由于目前的CUDA安装包自带显卡驱动、CUAD工具、OpenCL的SDK；其中OpenCL的相关内容的默认目录有：

• CL文件夹的目录：C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.0\include

• OpenCL.lib文件目录：C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.0\lib

• OpenCL.dll文件目录：C:\Program Files\NVIDIA Corporation\OpenCL

 

2. 新建空项目

 

可以通过VS2013的VC++模板新建一个空项目；

3. 添加文件

为了验证配置的正确性，所以为项目添加两个文件：cl_kernel.cl和main.cpp。

1) 添加cl_kernel.cl文件

    其中在项目所在的目录下新建一个cl_kernel.cl文件，其内容为附录1所示，目录结构如图 1所示。同时在VS2013的项目中将cl_kernel.cl文件添加到项目的"源文件"筛选器中，如图 2所示。

2) 添加main.cpp文件

类似cl_kernel.cl文件操作，同样将main.cpp文件添加到项目中。

4. 配置CL目录

需要将OpenCL的SDK的头文件包含到项目中，具体操作方法为：

在项目->属性->配置属性->C/C++->常规->附加包含目录->配置，然后添加CL文件夹的目录：C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.0\include。如图 3所示。

5. 配置预处理器

项目->属性->配置属性->c/c++->预处理器定义->编辑，然后添加"_CRT_SECURE_NO_WARNINGS"，否则会报错。

6. 配置外部依赖OpenCL.lib目录

具体操作：项目->属性->配置属性->链接器->常规->附加库目录。然后将OpenCL.lib文件所在的目录添加进去，其中需要注意的是将程序Debug成32位和64位平台添加的Opencl.lib目录是不同的，如图 4所示，是Debug成Win32平台，所以只加"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.0\lib\Win32"路径；若是Debug成X64，则添加的路径为"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.0\lib\x64"。同时需要在"启用增量链接"选项中选否。

7. 配置OpenCL.lib文件

项目->属性->配置属性->连接器->输入->附件依赖库->编辑，接着添加OpenCL.lib

8. 运行结果图

附录2：main.cpp文件

#include <CL/cl.h> 

#include <stdio.h> 

#include <iostream> 

using namespace std; 

 

int main(void){ 

    cl_uint numPlatforms = 0; //the NO. of platforms 

    cl_platform_id platform = nullptr; //the chosen platform 

    cl_context context = nullptr; // OpenCL context 

    cl_command_queue commandQueue = nullptr; 

    cl_program program = nullptr; // OpenCL kernel program object that'll be running on the compute device 

    cl_mem input1MemObj = nullptr; // input1 memory object for input argument 1 

    cl_mem input2MemObj = nullptr; // input2 memory object for input argument 2 

    cl_mem outputMemObj = nullptr; // output memory object for output 

    cl_kernel kernel = nullptr; // kernel object 

 

    cl_int status = clGetPlatformIDs(0, NULL, &numPlatforms); 

    if (status != CL_SUCCESS) 

    { 

        cout << "Error: Getting platforms!" << endl; 

        return 0; 

    } 

 

    /*For clarity, choose the first available platform. */ 

    if (numPlatforms > 0) 

    { 

        cl_platform_id* platforms = (cl_platform_id*)malloc(numPlatforms* sizeof(cl_platform_id)); 

        status = clGetPlatformIDs(numPlatforms, platforms, NULL); 

        platform = platforms[0]; 

        free(platforms); 

    } 

    else 

    { 

        puts("Your system does not have any OpenCL platform!"); 

        return 0; 

    } 

 

    /*Step 2:Query the platform and choose the first GPU device if has one.Otherwise use the CPU as device.*/ 

    cl_uint numDevices = 0; 

    cl_device_id *devices; 

    status = clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, 0, NULL, &numDevices); 

    if (numDevices == 0) //no GPU available. 

    { 

        cout << "No GPU device available." << endl; 

        cout << "Choose CPU as default device." << endl; 

        status = clGetDeviceIDs(platform, CL_DEVICE_TYPE_CPU, 0, NULL, &numDevices); 

        devices = (cl_device_id*)malloc(numDevices * sizeof(cl_device_id)); 

 

        status = clGetDeviceIDs(platform, CL_DEVICE_TYPE_CPU, numDevices, devices, NULL); 

    } 

    else 

    { 

        devices = (cl_device_id*)malloc(numDevices * sizeof(cl_device_id)); 

        status = clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, numDevices, devices, NULL); 

        cout << "The number of devices: " << numDevices << endl; 

    } 

 

    /*Step 3: Create context.*/ 

    context = clCreateContext(NULL, 1, devices, NULL, NULL, NULL); 

 

    /*Step 4: Creating command queue associate with the context.*/ 

    commandQueue = clCreateCommandQueue(context, devices[0], 0, NULL); 

 

    /*Step 5: Create program object */ 

    // Read the kernel code to the buffer 

    FILE *fp = fopen("cl_kernel.cl", "rb"); 

 

    //错误    1    error C4996 : 'fopen' : This function or variable may be unsafe.Consider using fopen_s instead.To disable deprecation, use _CRT_SECURE_NO_WARNINGS.See online help for details.c : \users\zyj\documents\visual studio 2013\projects\project3\project3\main.cpp    67    1    Project3 

 

 

    if (fp == nullptr) 

    { 

        puts("The kernel file not found!"); 

        goto RELEASE_RESOURCES; 

    } 

    fseek(fp, 0, SEEK_END); 

    size_t kernelLength = ftell(fp); 

    fseek(fp, 0, SEEK_SET); 

    char *kernelCodeBuffer = (char*)malloc(kernelLength + 1); 

    fread(kernelCodeBuffer, 1, kernelLength, fp); 

    kernelCodeBuffer[kernelLength] = '\0'; 

    fclose(fp); 

 

    const char *aSource = kernelCodeBuffer; 

    program = clCreateProgramWithSource(context, 1, &aSource, &kernelLength, NULL); 

 

    /*Step 6: Build program. */ 

    status = clBuildProgram(program, 1, devices, NULL, NULL, NULL); 

 

    /*Step 7: Initial inputs and output for the host and create memory objects for the kernel*/ 

    int __declspec(align(32)) input1Buffer[128]; // 32 bytes alignment to improve data copy 

    int __declspec(align(32)) input2Buffer[128]; 

    int __declspec(align(32)) outputBuffer[128]; 

 

    // Do initialization 

    int i; 

    for (i = 0; i < 128; i++) 

        input1Buffer[i] = input2Buffer[i] = i + 1; 

    memset(outputBuffer, 0, sizeof(outputBuffer)); 

 

    // Create mmory object 

    input1MemObj = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, 128 * sizeof(int), input1Buffer, nullptr); 

    input2MemObj = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, 128 * sizeof(int), input2Buffer, nullptr); 

    outputMemObj = clCreateBuffer(context, CL_MEM_WRITE_ONLY, 128 * sizeof(int), NULL, NULL); 

 

    /*Step 8: Create kernel object */ 

    kernel = clCreateKernel(program, "MyCLAdd", NULL); 

 

    /*Step 9: Sets Kernel arguments.*/ 

    status = clSetKernelArg(kernel, 0, sizeof(cl_mem), (void *)&outputMemObj); 

    status = clSetKernelArg(kernel, 1, sizeof(cl_mem), (void *)&input1MemObj); 

    status = clSetKernelArg(kernel, 2, sizeof(cl_mem), (void *)&input2MemObj); 

 

    /*Step 10: Running the kernel.*/ 

    size_t global_work_size[1] = { 128 }; 

    status = clEnqueueNDRangeKernel(commandQueue, kernel, 1, NULL, global_work_size, NULL, 0, NULL, NULL); 

    clFinish(commandQueue); // Force wait until the OpenCL kernel is completed 

 

    /*Step 11: Read the cout put back to host memory.*/ 

    status = clEnqueueReadBuffer(commandQueue, outputMemObj, CL_TRUE, 0, global_work_size[0] * sizeof(int), outputBuffer, 0, NULL, NULL); 

 

    printf("Veryfy the rsults... "); 

    for (i = 0; i < 128; i++) 

    { 

        if (outputBuffer[i] != (i + 1) * 2) 

        { 

            puts("Results not correct!"); 

            break; 

        } 

    } 

    if (i == 128) 

        puts("Correct!"); 

RELEASE_RESOURCES: 

    /*Step 12: Clean the resources.*/ 

    status = clReleaseKernel(kernel);//*Release kernel. 

    status = clReleaseProgram(program); //Release the program object. 

    status = clReleaseMemObject(input1MemObj);//Release mem object. 

    status = clReleaseMemObject(input2MemObj); 

    status = clReleaseMemObject(outputMemObj); 

    status = clReleaseCommandQueue(commandQueue);//Release Command queue. 

    status = clReleaseContext(context);//Release context. 

 

    free(devices); 

}

 

附录1 cl_kernel.cl文件

__kernel void MyCLAdd(__global int *dst, __global int *src1, __global int *src2) 

{ 

int index = get_global_id(0); 

dst[index] = src1[index] + src2[index]; 

}