OpenCL 对循环大小的限制

OpenCL Limit on for loop size?

本文关键字:循环 OpenCL      更新时间:2023-10-16

>更新:clEnqueueReadBuffer(command_queue, c_mem_obj, CL_TRUE, 0, LIST_SIZE * sizeof(double), C, 0, NULL, NULL);返回 -5,CL_OUT_OF_RESOURCES 。此功能/调用永远不应该返回此函数!

我开始使用 OpenCL 并遇到了一个问题。如果我允许 for 循环(在内核中)运行 10000 次,如果我允许循环运行 8000 次,则所有 C 都是 0,结果都是正确的。

我在

内核周围添加了等待以确保它完成,认为我在完成之前提取了数据,并尝试了 Clwaitforevent 和 CLFinish。任何调用都不会发出任何错误信号。当我使用 ints 时,for 循环将以 4000000 的大小工作。浮点数和双精度有同样的问题,但是浮点数在 10000 时工作,但在 20000 时不工作,当我使用浮点数时,我#pragma OPENCL EXTENSION cl_khr_fp64 : enable删除以检查这不是问题。

这是不是一些奇怪的内存问题,我用错了 OpenCL?我意识到在大多数内核中,我都没有为这样的循环实现,但这似乎是一个问题。我还删除了__private,看看这是否是问题所在,没有变化。那么 OpenCL 内核中 for 循环的大小是否有限制?硬件是否特定于?还是这是一个错误?

内核是一个简单的内核,它将 2 个数组 (A+B) 加在一起并输出另一个 (C)。为了感受性能,我在每个计算周围放置了一个 for 循环,以减慢/增加每次运行的操作数。

内核的代码如下:

#pragma OPENCL EXTENSION cl_khr_fp64 : enable
__kernel void vector_add(__global double *A, __global double *B, __global double *C)
{
    // Get the index of the current element
    int i = get_global_id(0);
    // Do the operation
    for (__private unsigned int j = 0; j < 10000; j++)
    {
        C[i] = A[i] + B[i];
    }
}

正在运行的代码如下:(当我在浮点数和双精度之间切换时,我确保两段代码之间的变量是一致的)

#include <stdio.h>
#include <stdlib.h>
#include <iostream>
#ifdef __APPLE__
#include <OpenCL/opencl.h>
#else
#include <CL/cl.h>
#endif
#define MAX_SOURCE_SIZE (0x100000)
int main(void) {
    // Create the two input vectors
    int i;
    const int LIST_SIZE = 4000000;
    double *A = (double*)malloc(sizeof(double)*LIST_SIZE);
    double *B = (double*)malloc(sizeof(double)*LIST_SIZE);
    for(i = 0; i < LIST_SIZE; i++) {
        A[i] = static_cast<double>(i);
        B[i] = static_cast<double>(LIST_SIZE - i);
    }
    // Load the kernel source code into the array source_str
    FILE *fp;
    char *source_str;
    size_t source_size;
    fp = fopen("vector_add_kernel.cl", "r");
    if (!fp) {
        fprintf(stderr, "Failed to load kernel.n");
        exit(1);
    }
    source_str = (char*)malloc(MAX_SOURCE_SIZE);
    source_size = fread( source_str, 1, MAX_SOURCE_SIZE, fp);
    fclose( fp );
    // Get platform and device information
    cl_platform_id platform_id = NULL;
    cl_device_id device_id = NULL;
    cl_uint ret_num_devices;
    cl_uint ret_num_platforms;
//    clGetPlatformIDs(1, &platform_id, NULL);
//clGetDeviceIDs(platform_id, CL_DEVICE_TYPE_GPU, 1, &device_id, ret_num_devices);

    cl_int ret = clGetPlatformIDs(1, &platform_id, NULL);
                if (ret != CL_SUCCESS) {
printf("Error: Failed to get platforms! (%d) n", ret);
return EXIT_FAILURE;
}
    ret = clGetDeviceIDs(platform_id, CL_DEVICE_TYPE_GPU, 1, &device_id, &ret_num_devices);
            if (ret != CL_SUCCESS) {
printf("Error: Failed to query platforms to get devices! (%d) n", ret);
return EXIT_FAILURE;
}
/*
    cl_int ret = clGetPlatformIDs(1, &platform_id, NULL);
                if (ret != CL_SUCCESS) {
printf("Error: Failed to get platforms! (%d) n", ret);
return EXIT_FAILURE;
}
    ret = clGetDeviceIDs( platform_id, CL_DEVICE_TYPE_CPU, 1,
            &device_id, &ret_num_devices);
            if (ret != CL_SUCCESS) {
printf("Error: Failed to query platforms to get devices! (%d) n", ret);
return EXIT_FAILURE;
}
*/
    // Create an OpenCL context
    cl_context context = clCreateContext( NULL, 1, &device_id, NULL, NULL, &ret);
    // Create a command queue
    cl_command_queue command_queue = clCreateCommandQueue(context, device_id, 0, &ret);
    // Create memory buffers on the device for each vector
    cl_mem a_mem_obj = clCreateBuffer(context, CL_MEM_READ_ONLY,
            LIST_SIZE * sizeof(double), NULL, &ret);
    cl_mem b_mem_obj = clCreateBuffer(context, CL_MEM_READ_ONLY,
            LIST_SIZE * sizeof(double), NULL, &ret);
    cl_mem c_mem_obj = clCreateBuffer(context, CL_MEM_WRITE_ONLY,
            LIST_SIZE * sizeof(double), NULL, &ret);
            if (ret != CL_SUCCESS) {
printf("Error: Buffer Fail! (%d) n", ret);
return EXIT_FAILURE;
}
    // Copy the lists A and B to their respective memory buffers
    ret = clEnqueueWriteBuffer(command_queue, a_mem_obj, CL_TRUE, 0,
            LIST_SIZE * sizeof(double), A, 0, NULL, NULL);
    ret = clEnqueueWriteBuffer(command_queue, b_mem_obj, CL_TRUE, 0,
            LIST_SIZE * sizeof(double), B, 0, NULL, NULL);
    std::cout << "Begin Compile" << "n";
    // Create a program from the kernel source
    cl_program program = clCreateProgramWithSource(context, 1,
            (const char **)&source_str, (const size_t *)&source_size, &ret);
             if (ret != CL_SUCCESS) {
printf("Error: Program Fail! (%d) n", ret);
return EXIT_FAILURE;
}
    // Build the program
    ret = clBuildProgram(program, 1, &device_id, NULL, NULL, NULL);
    if (ret != CL_SUCCESS) {
printf("Error: ProgramBuild Fail! (%d) n", ret);
return EXIT_FAILURE;
}
    // Create the OpenCL kernel
    cl_kernel kernel = clCreateKernel(program, "vector_add", &ret);
    if (ret != CL_SUCCESS) {
printf("Error: Kernel Build Fail! (%d) n", ret);
return EXIT_FAILURE;
}
    std::cout << "End Compile" << "n";
    std::cout << "Begin Data Move" << "n";
    // Set the arguments of the kernel
    ret = clSetKernelArg(kernel, 0, sizeof(cl_mem), (void *)&a_mem_obj);
    ret = clSetKernelArg(kernel, 1, sizeof(cl_mem), (void *)&b_mem_obj);
    ret = clSetKernelArg(kernel, 2, sizeof(cl_mem), (void *)&c_mem_obj);
    std::cout << "End Data Move" << "n";
    // Execute the OpenCL kernel on the list
    size_t global_item_size = LIST_SIZE; // Process the entire lists
    size_t local_item_size = 64; // Process in groups of 64
    std::cout << "Begin Execute" << "n";
    cl_event event;
    ret = clEnqueueNDRangeKernel(command_queue, kernel, 1, NULL,
            &global_item_size, &local_item_size, 0, NULL, &event);
            clFinish(command_queue);
            //clWaitForEvents(1, &event);
    std::cout << "End Execute" << "n";
    if (ret != CL_SUCCESS) {
printf("Error: Execute Fail! (%d) n", ret);
return EXIT_FAILURE;
}
    // Read the memory buffer C on the device to the local variable C
    std::cout << "Begin Data Move" << "n";
    double *C = (double*)malloc(sizeof(double)*LIST_SIZE);
    ret = clEnqueueReadBuffer(command_queue, c_mem_obj, CL_TRUE, 0,
            LIST_SIZE * sizeof(double), C, 0, NULL, NULL);
            if (ret != CL_SUCCESS) {
            printf("Error: Read Fail! (%d) n", ret);
            return EXIT_FAILURE;
            }
            clFinish(command_queue);
    std::cout << "End Data Move" << "n";
    std::cout << "Done" << "n";
    std::cin.get();
    // Display the result to the screen
    for(i = 0; i < LIST_SIZE; i++)
        printf("%f + %f = %f n", A[i], B[i], C[i]);
    // Clean up
    ret = clFlush(command_queue);
    ret = clFinish(command_queue);
    ret = clReleaseKernel(kernel);
    ret = clReleaseProgram(program);
    ret = clReleaseMemObject(a_mem_obj);
    ret = clReleaseMemObject(b_mem_obj);
    ret = clReleaseMemObject(c_mem_obj);
    ret = clReleaseCommandQueue(command_queue);
    ret = clReleaseContext(context);
    free(A);
    free(B);
    free(C);
    std::cout << "Number of Devices: " << ret_num_devices << "n";
    std::cin.get();
    return 0;
}

我在互联网上看了一下,找不到有类似问题的人,这是一个问题,因为它可能会导致代码在扩展之前运行良好......

我正在运行 Ubuntu 14.04,并且有一个用于 RC520 的笔记本电脑显卡,我用大黄蜂/optirun 运行。如果此错误在其他循环大小不超过 4000000 的机器上不可重现,那么我将使用 bumblebee/optirun 记录一个错误。

干杯

我发现了这个问题,连接到显示器/活动 VGA/等的 GPU 有一个看门狗计时器,在 ~5 秒后超时。非特斯拉的卡就是这种情况,它们具有此功能要关闭。在辅助卡上运行是一种解决方法。这很糟糕,需要尽快修复。这绝对是一个NVidia问题,不确定AMD,无论哪种方式,这都很糟糕。

解决方法是在Windows中更改注册表,在Linux/Ubuntu中更改X conf并放置:

选项"交互式"0"

但是,在

与显卡的差距中,X conf 现在不会在更高版本中生成,可能需要手动创建。如果有人对此有复制和粘贴控制台代码修复程序,那将是很好且更好的答案。