参考文献：
http://blog.csdn.net/neoxmu/article/details/8866928
我安装的是CUDA5.5,代码如下：
//#include "stdafx.h"
#include "CLcl.h"
#include <stdlib.h>
#include <stdio.h>
#pragma comment(lib,"OpenCL.lib")
#define CL_VERBOSE
void openclRetTackle(cl_int retValue, char* processInfo){
if(retValue!=CL_SUCCESS){
#if (defined CL_DEBUG) || (defined CL_VERBOSE)
printf("%s Error!
",processInfo);
#endif
exit(-1);
}else{
#ifdef CL_VERBOSE
printf("%s Success!
",processInfo);
#endif
}
}
cl_platform_id cpPlatform;
cl_device_id cdDevice;
cl_context cxGPUContext;
cl_command_queue cqCommandQueue;
int openclInit()
{
cl_int ret;
//得到平台ID
openclRetTackle( clGetPlatformIDs(1, &cpPlatform, NULL), "clGetPlatFormIDs");
//得到GPU设备ID
openclRetTackle( clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU,1,&cdDevice,NULL), "clGetDeviceIDs");
//获取GPU设备上下文
cxGPUContext = clCreateContext(0, 1, &cdDevice, NULL, NULL, &ret);
openclRetTackle( ret , "clCreateContext" );
//开辟任务队列
cqCommandQueue = clCreateCommandQueue(cxGPUContext, cdDevice, 0, &ret);
openclRetTackle( ret , "clCreateCommandQueue");
return CL_SUCCESS;
}
int run()
{
openclInit();
system("pause");
return 0;
}
<span style="font-family:Microsoft YaHei;font-size:18px;">//#include "stdafx.h"
#include <stdio.h>
#include <vector>
#include <CL/cl.h>
#include <iostream>
#include <fstream>
#include <string>
#pragma comment(lib,"OpenCL.lib")
int print_device()
{
cl_int err;
cl_uint num;
err = clGetPlatformIDs(0, 0, &num);
if(err != CL_SUCCESS)
{
std::cerr << "Unable to get platforms
";
return 0;
}
std::vector<cl_platform_id> platforms(num);
err = clGetPlatformIDs(num, &platforms[0], &num);
if(err != CL_SUCCESS)
{
std::cerr << "Unable to get platform ID
";
return 0;
}
cl_context_properties prop[] = { CL_CONTEXT_PLATFORM, reinterpret_cast<cl_context_properties>(platforms[0]), 0 };
cl_context context = clCreateContextFromType(prop, CL_DEVICE_TYPE_DEFAULT, NULL, NULL, NULL);
if(context == 0)
{
std::cerr << "Can't create OpenCL context
";
return 0;
}
size_t cb;
clGetContextInfo(context, CL_CONTEXT_DEVICES, 0, NULL, &cb);
std::vector<cl_device_id> devices(cb / sizeof(cl_device_id));
clGetContextInfo(context, CL_CONTEXT_DEVICES, cb, &devices[0], 0);
clGetDeviceInfo(devices[0], CL_DEVICE_NAME, 0, NULL, &cb);
std::string devname;
devname.resize(cb);
clGetDeviceInfo(devices[0], CL_DEVICE_NAME, cb, &devname[0], 0);
std::cout << "Device: " << devname.c_str() << "
";
clReleaseContext(context);
return 0;
}
cl_program load_program(cl_context context, const char* filename)
{
std::ifstream in(filename, std::ios_base::binary);
if(!in.good())
{
return 0;
}// get file length
in.seekg(0, std::ios_base::end);
size_t length = in.tellg();
in.seekg(0, std::ios_base::beg);
// read program source
std::vector<char> data(length + 1);
in.read(&data[0], length);
data[length] = 0;
// create and build program
const char* source = &data[0];
cl_program program = clCreateProgramWithSource(context, 1, &source, 0, 0);
if(program == 0)
{
return 0;
}
if(clBuildProgram(program, 0, 0, 0, 0, 0) != CL_SUCCESS)
{
return 0;
}
return program;
}
int main()
{
print_device();
cl_int err;
cl_uint num;
err = clGetPlatformIDs(0, 0, &num);
if(err != CL_SUCCESS)
{
std::cerr << "Unable to get platforms
";
return 0;
}
std::vector<cl_platform_id> platforms(num);
err = clGetPlatformIDs(num, &platforms[0], &num);
if(err != CL_SUCCESS)
{
std::cerr << "Unable to get platform ID
";
return 0;
}
cl_context_properties prop[] = { CL_CONTEXT_PLATFORM, reinterpret_cast<cl_context_properties>(platforms[0]), 0 };
cl_context context = clCreateContextFromType(prop, CL_DEVICE_TYPE_DEFAULT, NULL, NULL, NULL);
if(context == 0)
{
std::cerr << "Can't create OpenCL context
";
return 0;
}
size_t cb;
clGetContextInfo(context, CL_CONTEXT_DEVICES, 0, NULL, &cb);
std::vector<cl_device_id> devices(cb / sizeof(cl_device_id));
clGetContextInfo(context, CL_CONTEXT_DEVICES, cb, &devices[0], 0);
clGetDeviceInfo(devices[0], CL_DEVICE_NAME, 0, NULL, &cb);
std::string devname;
devname.resize(cb);
clGetDeviceInfo(devices[0], CL_DEVICE_NAME, cb, &devname[0], 0);
std::cout << "Device: " << devname.c_str() << "
";
cl_command_queue queue = clCreateCommandQueue(context, devices[0], 0, 0);
if(queue == 0)
{
std::cerr << "Can't create command queue
";
clReleaseContext(context);
return 0;
}
const int DATA_SIZE = 1048576;
std::vector<float> a(DATA_SIZE), b(DATA_SIZE), res(DATA_SIZE);
for(int i = 0; i < DATA_SIZE; i++)
{
a[i] = std::rand();
b[i] = std::rand();
}
cl_mem cl_a = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, sizeof(cl_float) * DATA_SIZE, &a[0], NULL);
cl_mem cl_b = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, sizeof(cl_float) * DATA_SIZE, &b[0], NULL);
cl_mem cl_res = clCreateBuffer(context, CL_MEM_WRITE_ONLY, sizeof(cl_float) * DATA_SIZE, NULL, NULL);
if(cl_a == 0 || cl_b == 0 || cl_res == 0)
{
std::cerr << "Can't create OpenCL buffer
";
clReleaseMemObject(cl_a);
clReleaseMemObject(cl_b);
clReleaseMemObject(cl_res);
clReleaseCommandQueue(queue);
clReleaseContext(context);
return 0;
}
cl_program program = load_program(context, "..\shader.txt");
if(program == 0)
{
std::cerr << "Can't load or build program
";
clReleaseMemObject(cl_a);
clReleaseMemObject(cl_b);
clReleaseMemObject(cl_res);
clReleaseCommandQueue(queue);
clReleaseContext(context);
return 0;
}
cl_kernel adder = clCreateKernel(program, "adder", 0);
if(adder == 0)
{
std::cerr << "Can't load kernel
";
clReleaseProgram(program);
clReleaseMemObject(cl_a);
clReleaseMemObject(cl_b);
clReleaseMemObject(cl_res);
clReleaseCommandQueue(queue);
clReleaseContext(context);
return 0;
}
clSetKernelArg(adder, 0, sizeof(cl_mem), &cl_a);
clSetKernelArg(adder, 1, sizeof(cl_mem), &cl_b);
clSetKernelArg(adder, 2, sizeof(cl_mem), &cl_res);
size_t work_size = DATA_SIZE;
err = clEnqueueNDRangeKernel(queue, adder, 1, 0, &work_size, 0, 0, 0, 0);
if(err == CL_SUCCESS)
{
err = clEnqueueReadBuffer(queue, cl_res, CL_TRUE, 0, sizeof(float) * DATA_SIZE, &res[0], 0, 0, 0);
}
if(err == CL_SUCCESS)
{
bool correct = true;
for(int i = 0; i < DATA_SIZE; i++)
{
if(a[i] + b[i] != res[i])
{
correct = false;
break;
}
}
if(correct)
{
std::cout << "Data is correct
";
}
else
{
std::cout << "Data is incorrect
";
}
}
else
{
std::cerr << "Can't run kernel or read back data
";
}
clReleaseKernel(adder);
clReleaseProgram(program);
clReleaseMemObject(cl_a);
clReleaseMemObject(cl_b);
clReleaseMemObject(cl_res);
clReleaseCommandQueue(queue);
clReleaseContext(context);
return 0;
}</span>
需要使用的数据：
shader.txt
<span style="font-family:Microsoft YaHei;font-size:18px;">__kernel void adder(__global const float* a, __global const float* b, __global float* result)
{
int idx = get_global_id(0);
result[idx] = a[idx] + b[idx];
}</span>