對于Ubuntu或其近親（Lubuntu、Kubuntu、Mint等）編寫OpenCL程序也不會太難。由于本例用的是AMD APP SDK，因此需要AMD的GPU以及相關驅動。首先，去AMD官網下載GPU驅動——AMD Catalyst。如果你用的是APU并且還有一塊獨立顯卡的話，通過AMD Catalyst Control Center可以選擇使用哪個GPU。像我現在用的聯想Z475筆記本，搭載了AMD APU A6-3420M以及一塊AMD Radeon HD 7400M，但是相比較而言，還是APU自帶的6620G的GPU性能更強一些，因此我這邊設置的是采用AMD Radeon HD 6620G。

在Linux下，AMD官方的GPU驅動是.run文件，只需使用sudo sh xxx.run即可安裝。安裝時采用默認安裝即可。

然后去developer.amd.com開發者網站下載AMD APP SDK。下載完成之后，將lib里面的動態庫文件（xxx.so）取出來，并且把include里的頭文件取出來。在你的OpenCL工程中把頭文件的路徑以及動態加載庫都設置好。在你用-l的時候，如果動態庫文件后綴名為.so.1，那么得把文件名后綴.1去掉。因為-l只能連接.a、.lib、.so等這些后綴的庫文件。

下面我們將舉一個最簡單的例子，首先看主機端代碼：

/*============================================================================Name : OpenCLTest.cAuthor : Zenny ChenVersion :Copyright : Your copyright noticeDescription : Hello World in C, Ansi-style============================================================================*/#include <stdio.h> #include <string.h> #include <stdlib.h> #include <unistd.h> #include <CL/cl.h>static int GetCurrentLocationFilePath(char pDst[512], const char *filename) {if(pDst == NULL || filename == NULL)return 0;int size = readlink("/proc/self/exe", pDst, 512);while(pDst[size - 1] != '/')size--;strcpy(&pDst[size], filename);int retSize = strlen(filename) + size;pDst[retSize] = '\0';return retSize; }int main(void) {/*Step1: Getting platforms and choose an available one.*/cl_uint numPlatforms; //the NO. of platformscl_int status = clGetPlatformIDs(0, NULL, &numPlatforms);if (status != CL_SUCCESS){puts("Error: Getting platforms!");return 0;}cl_platform_id platforms[16];/*For clarity, choose the first available platform. */if(numPlatforms > 0){status = clGetPlatformIDs(numPlatforms, platforms, NULL);if(status != CL_SUCCESS){puts("Failed to get platform IDs");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[16];clGetDeviceIDs(platforms[0], CL_DEVICE_TYPE_GPU, 0, NULL, &numDevices);if(numDevices == 0) //no GPU available. {puts("No devices available!");return 0;}else{printf("The number of available devices is: %u\n", numDevices);clGetDeviceIDs(platforms[0], CL_DEVICE_TYPE_GPU, numDevices, devices, NULL);}/*Step 3: Create context.*/cl_context context = clCreateContext(NULL,1, devices,NULL,NULL,NULL);/*Step 4: Creating command queue associate with the context.*/cl_command_queue commandQueue = clCreateCommandQueue(context, devices[0], 0, NULL);/*Step 5: Create program object */char filePath[512];GetCurrentLocationFilePath(filePath, "test.cl");FILE *fp = fopen(filePath, "r");if(fp == NULL){puts("OpenCL kernel source file open failed!");return 0;}fseek(fp, 0, SEEK_END);long fileLength = ftell(fp);fseek(fp, 0, SEEK_SET);char *source = (char*)malloc(fileLength + 1);fread(source, 1, fileLength, fp);fclose(fp);size_t sourceSize[] = {fileLength};cl_program program = clCreateProgramWithSource(context, 1, (const char**)&source, sourceSize, NULL);free(source);if(program == NULL){puts("Failed to create the program!");return 0;}/*Step 6: Build program. */status = clBuildProgram(program, 1,devices,NULL,NULL,NULL);if(status != CL_SUCCESS){puts("Failed to build the program!");return 0;}/*Step 7: Initial input,output for the host and create memory objects for the kernel*/int input[128];for(int i = 0; i < 128; i++)input[i] = i + 1;cl_mem inputBuffer = clCreateBuffer(context, CL_MEM_READ_ONLY|CL_MEM_COPY_HOST_PTR, sizeof(input), input, NULL);cl_mem outputBuffer = clCreateBuffer(context, CL_MEM_WRITE_ONLY , sizeof(input), NULL, NULL);/*Step 8: Create kernel object */cl_kernel kernel = clCreateKernel(program, "test", NULL);/*Step 9: Sets Kernel arguments.*/status = clSetKernelArg(kernel, 0, sizeof(cl_mem), &inputBuffer);status = clSetKernelArg(kernel, 1, sizeof(cl_mem), &outputBuffer);/*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);/*Step 11: Read the cout put back to host memory.*/int output[128];status = clEnqueueReadBuffer(commandQueue, outputBuffer, CL_TRUE, 0, sizeof(input), output, 0, NULL, NULL);/*Step 12: Clean the resources.*/status = clReleaseKernel(kernel); //Release kernel.status = clReleaseProgram(program); //Release the program object.status = clReleaseMemObject(inputBuffer); //Release mem object.status = clReleaseMemObject(outputBuffer);status = clReleaseCommandQueue(commandQueue); //Release Command queue.status = clReleaseContext(context); //Release context.for(int i = 0; i < 128; i++){if(output[i] != i + 2){printf("Error occurred @%d!", i);return 0;}}puts("Pass!");return 1; }

在編譯選項中，使用-std=gnu99或-std=gnu11。上述代碼為純C語言，因此即便你沒有安裝g++也完全沒關系。

下面看看內核源代碼：

/*============================================================================Name : OpenCLTest.cAuthor : Zenny ChenVersion :Copyright : Your copyright noticeDescription : Simple OpenCL kernel source============================================================================*/__kernel void test(__global int* in, __global int* out) {int index = get_global_id(0);out[index] = in[index] + 1; }

將此文件放在可執行文件相同路徑下，然后我們就能正常運行了。

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