学步园

自从Apple从08年正式将自己的OpenCL提交到Khronos Group开放标准组织后，先后获得AMD、nVidia、Intel等大公司的支持。OpenCL能充分发挥GPU数据密集型大规模计算的能力，从而使得很多多媒体应用乃至科学计算能获得大幅度的性能提升。

这里将主要介绍如何在Windows 7中使用AMD APP SDK中的OpenCL。

首先，我们可以先去AMD开发者官网——development.amd.com，到这个网页http://developer.amd.com/tools-and-sdks/heterogeneous-computing/amd-accelerated-parallel-processing-app-sdk/，根据你的系统来选择下载AMD APP SDK。如果你使用的是Windows 7操作系统，那么在你安装完毕后，安装包会自动在系统环境变量中添加AMDAPPSDKROOT，我们后面将会利用这个环境变量来找包含的头文件路径以及连接库的路径。

然后，我们得有Visual Stduio 2012 Express Edition或Professional Edition。我们可以先创建一个Win32 Console项目或Win32 Application项目，然后在菜单栏Project中的<项目名> Properties中找到C/C++，然后再选到Genral，在Additional Include Directories中输入$(AMDAPPSDKROOT)\include。

然后我们再找到Preprocessor，在Preprocessor Definitions中添加宏_CRT_SECURE_NO_WARNINGS，这个宏将会对稍候代码中使用读文件有用。

我们再来，找到Linker，点击后找到Additional Library Directories，添加$(AMDAPPSDKROOT)\lib\x86。

然后我们再点击Input，在Additional Dependencies中添加OpenCL.lib。

这样，我们就把所有的准备工作做好了。

接下来，我们可以先写这个例子所需要的OpenCL Kernel代码：

__kernel void MyCLAdd(__global int *dst, __global int *src1, __global int *src2)
{
    int index = get_global_id(0);
    dst[index] = src1[index] + src2[index];
}

我们将上述代码保存为cl_kernel.cl，放在这个工程放资源文件和源代码的文件夹下。在VC++工程中，我们可以将这个文件添加到Resource筛选器下。

接下来，我们可以写main函数，或其它什么函数来创建并运行这段OpenCL内核代码。

#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");
        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);
}

我们直接编译运行即可。

在校验函数中，我们可以发现，输出结果完全正确。

这里需要注意的是，这个源文件必须保存为.cpp后缀，并且得用支持C++11标准的VC编译器，比如VS2012 。当然如果用VS2010应该也能通过编译，尽管我还没试过。