在 MATLAB Cuda 中获取随机值以进行二次输出

Question

问题：我得到两个计算的数组和两个预期的输出

右计算输出
随机数，旧数，其他数组中的数

我正在使用 MATLAB R2016B 和这个 Coda 版本 + GPU：

 CUDADevice with properties:

                  Name: 'GeForce GT 525M'
                 Index: 1
     ComputeCapability: '2.1'
        SupportsDouble: 1
         DriverVersion: 8
        ToolkitVersion: 7.5000
    MaxThreadsPerBlock: 1024
      MaxShmemPerBlock: 49152
    MaxThreadBlockSize: [1024 1024 64]
           MaxGridSize: [65535 65535 65535]
             SIMDWidth: 32
           TotalMemory: 1.0737e+09
       AvailableMemory: 947929088
   MultiprocessorCount: 2
          ClockRateKHz: 1200000
           ComputeMode: 'Default'
  GPUOverlapsTransfers: 1
KernelExecutionTimeout: 1
      CanMapHostMemory: 1
       DeviceSupported: 1
        DeviceSelected: 1

我现在将尝试使用 GPU 对两个不同的数组进行加减运算，并将其返回给 MATLAB。

MATLAB代码：

n = 10;
as = [1,1,1];
bs = [10,10,10];

for i = 2:n+1
  as(end+1,:) = [i,i,i];
  bs(end+1,:) = [10,10,10];
end
as = as *1;

% Load the kernel
cudaFilename = 'add2.cu';
ptxFilename = ['add2.ptx'];

% Check if the files are awareable
if((exist(cudaFilename, 'file') || exist(ptxFilename, 'file')) == 2)
  error('CUDA FILES ARE NOT HERE');
end
kernel = parallel.gpu.CUDAKernel( ptxFilename, cudaFilename );

% Make sure we have sufficient blocks to cover all of the locations
kernel.ThreadBlockSize = [kernel.MaxThreadsPerBlock,1,1];
kernel.GridSize = [ceil(n/kernel.MaxThreadsPerBlock),1];

% Call the kernel
outadd = zeros(n,1, 'single' );
outminus = zeros(n,1, 'single' );
[outadd, outminus] = feval( kernel, outadd,outminus, as, bs );

Cuda 片段

#include "cuda_runtime.h"
#include "add_wrapper.hpp"
#include <stdio.h>

__device__ size_t calculateGlobalIndex() {
    // Which block are we?
    size_t const globalBlockIndex = blockIdx.x + blockIdx.y * gridDim.x;
    // Which thread are we within the block?
    size_t const localThreadIdx = threadIdx.x + blockDim.x * threadIdx.y;
    // How big is each block?
    size_t const threadsPerBlock = blockDim.x*blockDim.y;
    // Which thread are we overall?
    return localThreadIdx + globalBlockIndex*threadsPerBlock;
}

__global__ void addKernel(float *c, float *d, const float *a, const  float *b)
{
    int i = calculateGlobalIndex();
    c[i] = a[i] + b[i];
    d[i] = a[i] - b[i];
}

// C = A + B
// D = A - B
void addWithCUDA(float *cpuC,float *cpuD, const float *cpuA, const float *cpuB, const size_t sz)
{   
//TODO: add error checking

// choose which GPU to run on
cudaSetDevice(0);

// allocate GPU buffers
float *gpuA, *gpuB, *gpuC, *gpuD;
cudaMalloc((void**)&gpuA, sz*sizeof(float));
cudaMalloc((void**)&gpuB, sz*sizeof(float));
cudaMalloc((void**)&gpuC, sz*sizeof(float));
cudaMalloc((void**)&gpuD, sz*sizeof(float));
cudaCheckErrors("cudaMalloc fail");

// copy input vectors from host memory to GPU buffers
cudaMemcpy(gpuA, cpuA, sz*sizeof(float), cudaMemcpyHostToDevice);
cudaMemcpy(gpuB, cpuB, sz*sizeof(float), cudaMemcpyHostToDevice);

// launch kernel on the GPU with one thread per element
addKernel<<<1,sz>>>(gpuC, gpuD, gpuA, gpuB);

// wait for the kernel to finish
cudaDeviceSynchronize();

// copy output vector from GPU buffer to host memory
cudaMemcpy(cpuC, gpuC, sz*sizeof(float), cudaMemcpyDeviceToHost);
cudaMemcpy(cpuD, gpuD, sz*sizeof(float), cudaMemcpyDeviceToHost);


// cleanup
cudaFree(gpuA);
cudaFree(gpuB);
cudaFree(gpuC);
cudaFree(gpuD);
}

void resetDevice()
{
    cudaDeviceReset();
}

[outadd, outminus]是MATLAB中运行代码后的两个GPU数组对象。

Outadd 总是正确计算，outminus 很少正确，主要包含随机整数或浮点数、零，有时甚至 outadd 的值。

如果我将算术运算的顺序换成另一个算术运算，那么 'outminus' 是不是应该计算正确？

Answer 1

使用@Robert Crovella 提示不必要的线程可能会导致访问错误，我只是为线程添加了一个限制。

MATLAB

[outadd, outminus] = feval( kernel, outadd,outminus, as, bs, n);

CUDA 内核方法

__global__ void addKernel(float *c, float *d, const float *a, const float *b, const float n)
{  
    int i = calculateGlobalIndex();
    if ( i < n ){
        c[i] = a[i] + b[i];
        d[i] = a[i] - b[i];
   }
}

我认为这仍然不是最佳解决方案，因为 GPU 仍然会启动所有线程，即使大多数线程不应该使用那么多资源。

修改妥当后上传到这里

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