【发布时间】：2012-04-26 16:31:01
【问题描述】：
所以，在另一篇文章中，我对 C 时间测量提出了质疑。现在，我想知道如何比较 C“函数”与 OpenCL“函数”的结果
这是宿主OpenCL和C的代码
#define PROGRAM_FILE "sum.cl"
#define KERNEL_FUNC "float_sum"
#define ARRAY_SIZE 1000000
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <CL/cl.h>
int main()
{
/* OpenCL Data structures */
cl_platform_id platform;
cl_device_id device;
cl_context context;
cl_program program;
cl_kernel kernel;
cl_command_queue queue;
cl_mem vec_buffer, result_buffer;
cl_event prof_event;;
/* ********************* */
/* C Data Structures / Data types */
FILE *program_handle; //Kernel file handle
char *program_buffer; //Kernel buffer
float *vec, *non_parallel;
float result[ARRAY_SIZE];
size_t program_size; //Kernel file size
cl_ulong time_start, time_end, total_time;
int i;
/* ****************************** */
/* Errors */
cl_int err;
/* ****** */
non_parallel = (float*)malloc(ARRAY_SIZE * sizeof(float));
vec = (float*)malloc(ARRAY_SIZE * sizeof(float));
//Initialize the vector of floats
for(i = 0; i < ARRAY_SIZE; i++)
vec[i] = i + 1;
/************************* C Function **************************************/
clock_t start, end;
start = clock();
for( i = 0; i < ARRAY_SIZE; i++)
{
non_parallel[i] = vec[i] * vec[i];
}
end = clock();
printf( "Number of seconds: %f\n", (clock()-start)/(double)CLOCKS_PER_SEC );
free(non_parallel);
/***************************************************************************/
clGetPlatformIDs(1, &platform, NULL);//Just want NVIDIA platform
clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, 1, &device, NULL);
context = clCreateContext(NULL, 1, &device, NULL, NULL, &err);
// Context error?
if(err)
{
perror("Cannot create context");
return 1;
}
//Read the kernel file
program_handle = fopen(PROGRAM_FILE,"r");
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 the program
program = clCreateProgramWithSource(context, 1, (const char**)&program_buffer,
&program_size, &err);
if(err)
{
perror("Cannot create program");
return 1;
}
free(program_buffer);
clBuildProgram(program, 0, NULL, NULL, NULL, NULL);
kernel = clCreateKernel(program, KERNEL_FUNC, &err);
if(err)
{
perror("Cannot create kernel");
return 1;
}
queue = clCreateCommandQueue(context, device, CL_QUEU_PROFILING_ENABLE, &err);
if(err)
{
perror("Cannot create command queue");
return 1;
}
vec_buffer = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR,
sizeof(float) * ARRAY_SIZE, vec, &err);
result_buffer = clCreateBuffer(context, CL_MEM_WRITE_ONLY, sizeof(float)*ARRAY_SIZE, NULL, &err);
if(err)
{
perror("Cannot create the vector buffer");
return 1;
}
clSetKernelArg(kernel, 0, sizeof(cl_mem), &vec_buffer);
clSetKernelArg(kernel, 1, sizeof(cl_mem), &result_buffer);
size_t global_size = ARRAY_SIZE;
size_t local_size = 0;
clEnqueueNDRangeKernel(queue, kernel, 1, NULL, &global_size, NULL, 0, NULL, &prof_event);
clEnqueueReadBuffer(queue, result_buffer, CL_TRUE, 0, sizeof(float)*ARRAY_SIZE, &result, 0, NULL, NULL);
clFinish(queue);
clGetEventProfilingInfo(prof_event, CL_PROFILING_COMMAND_START,
sizeof(time_start), &time_start, NULL);
clGetEventProfilingInfo(prof_event, CL_PROFILING_COMMAND_END,
sizeof(time_end), &time_end, NULL);
total_time += time_end - time_start;
printf("\nAverage time in nanoseconds = %lu\n", total_time/ARRAY_SIZE);
clReleaseMemObject(vec_buffer);
clReleaseMemObject(result_buffer);
clReleaseKernel(kernel);
clReleaseCommandQueue(queue);
clReleaseProgram(program);
clReleaseContext(context);
free(vec);
return 0;
}
内核是：
__kernel void float_sum(__global float* vec,__global float* result){
int gid = get_global_id(0);
result[gid] = vec[gid] * vec[gid];
}
现在，结果是：
秒数：0.010000
以纳秒为单位的平均时间 = 140737284
0,1407秒是OpenCL时间内核执行的时间，比C函数还多，对吗？因为我认为 OpenCL 应该比 C 非并行算法最快...
【问题讨论】：
-
我对这些结果感到非常惊讶，尤其是因为您将 OpenCL 速度除以数组大小。你确定你正在正确地计时代码吗？您使用的是 Windows 还是 Linux？您使用的是什么 GPU？
-
你在试验这个具体的例子吗？如果您使用 float4 类型，您可以在一次操作中对 4 个值进行点积和求和。我已经在下面回答了，假设您不是在寻找这样的优化，而是在寻找 opencl 指针。您还可以使用平方和公式。
标签： c performance algorithm opencl measurement