如何从尖峰库矩阵格式获取原始指针 [英] How to get raw pointer from cusp library matrix format

问题描述

我需要从尖峰库矩阵格式获取原始指针.例如:

I need to get raw pointer from cusp library matrix format. For example:

cusp::coo_matrix<int,double,cusp::device_memory> A(3,3,4);

A.values[0] = 1;
A.row_indices[0] = 0;
A.column_indices[0]= 1;

A.values[1] = 2;
A.row_indices[1] = 1;
A.column_indices[1]= 0;

A.values[2] = 3;
A.row_indices[2] = 1;
A.column_indices[2]= 1;

A.values[3] = 4;
A.row_indices[3] = 2;
A.column_indices[3]= 2;

如何获取指向row_indices，column_indices和values数组的原始指针?我需要将它们传递给我的内核，如果可能的话，我希望避免不必要的数据复制.

How can I get the raw pointer to row_indices, column_indices and values arrays? I need to pass them to my kernels and I'd like to avoid unnecesary data copying if possible.

推荐答案

有多种方法可以实现此目的.例如，如果您希望以原始设备数据表示形式而不是cusp数据表示形式开始，则可以使用cusp

There are multiple ways to accomplish this. For example, if the you wish to start with the raw device data representation instead of the cusp data representation, you could use the methodology in the cusp views functionality.

如果您已经拥有尖峰数据，并且想要转换为原始数据表示形式，那么我们可以使用尖峰建立在

If you have cusp data already, and you want to convert to raw data representation, we can use the fact that cusp is built on top of thrust. Here's a fully worked example:

$ cat t346.cu
#include <cusp/coo_matrix.h>
#include <cusp/print.h>

template <typename T>
__global__ void my_swap_kernel(T *a, T *b, unsigned size){
  int idx = threadIdx.x+blockDim.x*blockIdx.x;
  if (idx < size){
    T temp = b[idx];
    b[idx] = a[idx];
    a[idx] = temp;}
}



int main(void)
{
    // allocate storage for (4,3) matrix with 6 nonzeros
    cusp::coo_matrix<int,float,cusp::device_memory> A(4,3,6);

    // initialize matrix entries on host
    A.row_indices[0] = 0; A.column_indices[0] = 0; A.values[0] = 10;
    A.row_indices[1] = 0; A.column_indices[1] = 2; A.values[1] = 20;
    A.row_indices[2] = 2; A.column_indices[2] = 2; A.values[2] = 30;
    A.row_indices[3] = 3; A.column_indices[3] = 0; A.values[3] = 40;
    A.row_indices[4] = 3; A.column_indices[4] = 1; A.values[4] = 50;
    A.row_indices[5] = 3; A.column_indices[5] = 2; A.values[5] = 60;
    float *val0 = thrust::raw_pointer_cast(&A.values[0]);
    float *val3 = thrust::raw_pointer_cast(&A.values[3]);

    // A now represents the following matrix
    //    [10  0 20]
    //    [ 0  0  0]
    //    [ 0  0 30]
    //    [40 50 60]

    // print matrix entries
    cusp::print(A);
    my_swap_kernel<<<1,3>>>(val0, val3, 3);
    cusp::print(A);

    return 0;
}

$ nvcc -arch=sm_20 -o t346 t346.cu
$ cuda-memcheck ./t346
========= CUDA-MEMCHECK
sparse matrix <4, 3> with 6 entries
              0              0             10
              0              2             20
              2              2             30
              3              0             40
              3              1             50
              3              2             60
sparse matrix <4, 3> with 6 entries
              0              0             40
              0              2             50
              2              2             60
              3              0             10
              3              1             20
              3              2             30
========= ERROR SUMMARY: 0 errors
$

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