在CUDA中并行化，为每列分配线程 [英] Parallelization in CUDA, assigning threads to each column

问题描述

假设我有一个从MxN 2D矩阵转换的1D数组，我想并行化每个列，并做一些操作。

Say I have a 1D array converted from a MxN 2D matrix, and I want to parallelize each column and do some operations. How do I assign a thread to each column?

例如，如果我有一个3x3的矩阵：

For example, if I have a 3x3 matrix:

1  2  3

4  5  6

7  8  9

而且我想根据列＃添加列中的每个数字（因此第一列将添加1，第二列将添加2 ....），然后变为：

And I want to add each number in the column depending on the column # (so 1st column will add 1, 2nd will add 2....), it then becomes:

1+1   2+1   3+1

4+2   5+2   6+2

7+3   8+3   9+3

这在CUDA？我知道如何分配线程到数组中的所有元素，但我不知道如何分配线程到每一列。所以，我想要的是发送每一列（1，2，3）（4,5,6）（7,8,9）并执行操作。

How do I do this in CUDA? I know how to assign threads to all the elements in the array but I don't know how to assign thread to each column. So, what I want is to send each column (1 , 2 ,3 ) ( 4 , 5 ,6 ) (7 , 8 ,9) and do the operation.

推荐答案

在您的示例中，您将添加基于行的数字。不过，你知道矩阵的行/列长度（你知道它是MxN）。你可以做的是：

In your example you are adding numbers based on the row. Still, you know the row/column length of the matrix (you know it's MxN). What you could do is something like:

__global__ void MyAddingKernel(int* matrix, int M, int N)
{

    int gid = threadIdx.x + blockDim.x*blockIdx.x;
    //Let's add the row number to each element
    matrix[ gid ] += gid % M;
    //Let's add the column number to each element
    matrix[ gid ] += gid % N;

}

如果您想添加其他号码，例如：

If you wanted to add a different number, you could do something like:

matrix[ gid ] += my_col_number_function(gid%N);

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