Question

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。这个功能/调用应该永远不会返回！

我已经开始使用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，那么如果我允许循环运行8000，则所有C都为0，结果都是正确的。

我已经在内核周围添加了等待以确保完成，认为我在完成之前将数据拉出来并尝试了Clwaitforevent和CLFinish。任何呼叫都不会发出任何错误信号。当我使用int时，for循环将工作在4000000的大小。浮动和双打有相同的问题，但浮点数工作在10000，但不是在20000，当我使用浮动我移除#pragma OPENCL EXTENSION cl_khr_fp64 : enable来检查是不是这个问题。

这是一些奇怪的记忆事，我是否使用OpenCL错了？我意识到在大多数内核中我都不会像这样实现循环，但这似乎是一个问题。我还删除了__private，看看是不是问题，没有改变。那么OpenCL内核中for循环的大小是否有限制？硬件是否具体？或者这是一个错误吗？

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，我在每次计算周围都进行了一次循环，以减慢/增加每次运行的操作次数。

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];
    }
}

我正在运行的代码如下:(当我在float和double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;
}

我已经在互联网上看过，找不到有类似问题的人，这是一个值得关注的问题，因为它可能导致代码在扩展之前运行良好...

我正在运行Ubuntu 14.04，并为RC520配备了笔记本电脑显卡，我使用bumblebee / optirun运行。如果这个bug在其他机器上无法重现，最大循环大小为4000000，那么我将使用bumblebee / optirun记录一个bug。

干杯

Answer 1

我发现问题，连接到显示器/有源VGA /等的GPU有一个看门狗定时器，在约5秒后超时。这种情况适用于非teslas的卡，它可以关闭此功能。在二级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，无论如何都不确定AMD，这很糟糕。

变通办法是Windows中的注册表更改，在Linux / Ubuntu中，更改X conf并放置：

选项“互动”“0”

在与显卡的差距中，X Conf现在不会在以后的版本中生成，可能需要手动创建。如果有人复制并粘贴控制台代码，那么这将是一个很好的答案。

OpenCL限制为循环大小？

1 个答案: