初识opencl

以一个例子开头

在自己的笔记本电脑上(win10)安装intel的那个opencl包，安装后，记得将include与lib包拷贝出来，然后在以后的使用中只要链接这个库就ok了。

例子代码如下：（出自opencl in action）

#pragma once
#define _CRT_SECURE_NO_WARNINGS
#define PROGRAM_FILE "matvec.cl"
#define KERNEL_FUNC "matvec_mult"

#include 
#include 
#include 

#ifdef MAC
#include 
#else  
#include 
#endif

int test1() {

	/* Host/device data structures   主机、设备数据结构体*/
	cl_platform_id platform;
	cl_device_id device;
	cl_context context;
	cl_command_queue queue;
	cl_int i, err;

	/* Program/kernel data structures  程序、内核 数据结构体  */
	cl_program program;
	FILE *program_handle;
	char *program_buffer, *program_log;
	size_t program_size, log_size;
	cl_kernel kernel;

	/* Data and buffers  数据与缓存*/
	float mat[16], vec[4], result[4];
	float correct[4] = { 0.0f, 0.0f, 0.0f, 0.0f };
	cl_mem mat_buff, vec_buff, res_buff;
	size_t work_units_per_kernel;

	/* Initialize data to be processed by the kernel  初始化数据 */
	for (i = 0; i < 16; i++) {
		mat[i] = i * 2.0f;
	}
	//初始化数据并在cpu上计算结果
	for (i = 0; i < 4; i++) {
		vec[i] = i * 3.0f;
		correct[0] += mat[i] * vec[i];
		correct[1] += mat[i + 4] * vec[i];
		correct[2] += mat[i + 8] * vec[i];
		correct[3] += mat[i + 12] * vec[i];
	}

	/* Identify a platform    定义平台*/
	err = clGetPlatformIDs(1, &platform, NULL);
	if (err < 0) {
		perror("Couldn't find any platforms");
		exit(1);
	}

	/* Access a device   获取设备*/
	err = clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, 1, &device, NULL);
	if (err < 0) {
		perror("Couldn't find any devices");
		exit(1);
	}

	/* Create the context  创建上下文*/
	context = clCreateContext(NULL, 1, &device, NULL, NULL, &err);
	if (err < 0) {
		perror("Couldn't create a context");
		exit(1);
	}

	/* Read program file and place content into buffer   读取内核程序文件 */
	program_handle = fopen(PROGRAM_FILE, "r");
	if (program_handle == NULL) {
		perror("Couldn't find the program file");
		exit(1);
	}
	fseek(program_handle, 0, SEEK_END);
	program_size = ftell(program_handle);
	rewind(program_handle);
	program_buffer = (char*)malloc(program_size + 1);
	program_buffer[program_size] = '\0';
	fread(program_buffer, sizeof(char), program_size, program_handle);
	fclose(program_handle);

	/* Create program from file  从程序文件与上下文得到 program 程序 */
	program = clCreateProgramWithSource(context, 1,
		(const char**)&program_buffer, &program_size, &err);
	if (err < 0) {
		perror("Couldn't create the program");
		exit(1);
	}
	free(program_buffer);

	/* Build program    编译程序 */
	err = clBuildProgram(program, 0, NULL, NULL, NULL, NULL);
	if (err < 0) {

		/* Find size of log and print to std output */
		clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG,
			0, NULL, &log_size);
		program_log = (char*)malloc(log_size + 1);
		program_log[log_size] = '\0';
		clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG,
			log_size + 1, program_log, NULL);
		printf("%s\n", program_log);
		free(program_log);
		exit(1);
	}

	/* Create kernel for the mat_vec_mult function 创建内核 */
	kernel = clCreateKernel(program, KERNEL_FUNC, &err);
	if (err < 0) {
		perror("Couldn't create the kernel");
		exit(1);
	}

	/* Create CL buffers to hold input and output data    创建cl 内存去保存输入与输出数据 */
	mat_buff = clCreateBuffer(context, CL_MEM_READ_ONLY |
		CL_MEM_COPY_HOST_PTR, sizeof(float) * 16, mat, &err);
	if (err < 0) {
		perror("Couldn't create a buffer object");
		exit(1);
	}
	vec_buff = clCreateBuffer(context, CL_MEM_READ_ONLY |
		CL_MEM_COPY_HOST_PTR, sizeof(float) * 4, vec, NULL);
	res_buff = clCreateBuffer(context, CL_MEM_WRITE_ONLY,
		sizeof(float) * 4, NULL, NULL);

	/* Create kernel arguments from the CL buffers   由Cl内存数据设置内核参数*/
	err = clSetKernelArg(kernel, 0, sizeof(cl_mem), &mat_buff);
	if (err < 0) {
		perror("Couldn't set the kernel argument");
		exit(1);
	}
	clSetKernelArg(kernel, 1, sizeof(cl_mem), &vec_buff);
	clSetKernelArg(kernel, 2, sizeof(cl_mem), &res_buff);

	/* Create a CL command queue for the device   由Device,context创建命令队列 */
	//queue = clCreateCommandQueue(context, device, 0, &err);
	queue = clCreateCommandQueueWithProperties(context, device, 0, NULL);
	if (err < 0) {
		perror("Couldn't create the command queue");
		exit(1);
	}

	/* Enqueue the command queue to the device   执行内核，使用4 work-units per kernel */
	work_units_per_kernel = 4; /* 4 work-units per kernel */
	err = clEnqueueNDRangeKernel(queue, kernel, 1, NULL, &work_units_per_kernel,
		NULL, 0, NULL, NULL);
	if (err < 0) {
		perror("Couldn't enqueue the kernel execution command");
		exit(1);
	}

	/* Read the result  读结果 */
	err = clEnqueueReadBuffer(queue, res_buff, CL_TRUE, 0, sizeof(float) * 4,
		result, 0, NULL, NULL);
	if (err < 0) {
		perror("Couldn't enqueue the read buffer command");
		exit(1);
	}

	/* Test the result  核对结果 */
	if ((result[0] == correct[0]) && (result[1] == correct[1])
		&& (result[2] == correct[2]) && (result[3] == correct[3])) {
		printf("Matrix-vector multiplication successful.\n");
	}
	else {
		printf("Matrix-vector multiplication unsuccessful.\n");
	}

	/* Deallocate resources */
	clReleaseMemObject(mat_buff);
	clReleaseMemObject(vec_buff);
	clReleaseMemObject(res_buff);
	clReleaseKernel(kernel);
	clReleaseCommandQueue(queue);
	clReleaseProgram(program);
	clReleaseContext(context);

	return 0;
}

总结一下上面的流程：

运行结果：

Matrix-vector multiplication successful.