如何在cuSparse中使用cusparseXcoo2csr从coo转换为csc

在cuSparse的文档中，它指出函数cusparseXcoo2csr

还可以用于转换包含未压缩的列索引(对应COO格式(到列数组中指针(对应CSC格式(

然而，我找不到复制它的方法。请参阅下面的最小代码：

CMakeLists.txt

cmake_minimum_required(VERSION 3.11)
project(sample)
find_package(CUDA REQUIRED)
add_executable(${PROJECT_NAME} main.cpp)
target_compile_features(${PROJECT_NAME} PUBLIC cxx_std_14)
target_include_directories(${PROJECT_NAME} SYSTEM PUBLIC ${CUDA_INCLUDE_DIRS})
target_link_libraries(${PROJECT_NAME} ${CUDA_LIBRARIES} ${CUDA_cusparse_LIBRARY})

main.cpp

#include <iostream>
#include <vector>
#include <cuda_runtime_api.h>
#include <cusparse_v2.h>
int main(){
// using the matrix as shown in https://docs.nvidia.com/cuda/cusparse/index.html#coo-format
// 1 4 0 0 0
// 0 2 3 0 0
// 5 0 0 7 8
// 0 0 9 0 6
std::vector<int> row;
std::vector<int> col;
std::vector<double> val;
row.emplace_back(0);
row.emplace_back(0);
row.emplace_back(1);
row.emplace_back(1);
row.emplace_back(2);
row.emplace_back(2);
row.emplace_back(2);
row.emplace_back(3);
row.emplace_back(3);
col.emplace_back(0);
col.emplace_back(1);
col.emplace_back(1);
col.emplace_back(2);
col.emplace_back(0);
col.emplace_back(3);
col.emplace_back(4);
col.emplace_back(2);
col.emplace_back(4);
val.emplace_back(1);
val.emplace_back(4);
val.emplace_back(2);
val.emplace_back(3);
val.emplace_back(5);
val.emplace_back(7);
val.emplace_back(8);
val.emplace_back(9);
val.emplace_back(6);
int *d_row;
int *d_col;
double *d_val;
cudaMalloc(reinterpret_cast<void **>(&d_row), row.size() * sizeof(int));
cudaMalloc(reinterpret_cast<void **>(&d_col), col.size() * sizeof(int));
cudaMalloc(reinterpret_cast<void **>(&d_val), val.size() * sizeof(double));
cudaMemcpy(d_row, row.data(), sizeof(int) * row.size(), cudaMemcpyHostToDevice);
cudaMemcpy(d_col, col.data(), sizeof(int) * col.size(), cudaMemcpyHostToDevice);
cudaMemcpy(d_val, val.data(), sizeof(double) * val.size(), cudaMemcpyHostToDevice);
cusparseHandle_t handle;
cusparseCreate(&handle);
cusparseMatDescr_t descr;
cusparseCreateMatDescr(&descr);
cusparseSetMatType(descr, CUSPARSE_MATRIX_TYPE_GENERAL);
cusparseSetMatIndexBase(descr, CUSPARSE_INDEX_BASE_ZERO);
cusparseMatDescr_t descr_out;
cusparseCreateMatDescr(&descr_out);
cusparseSetMatType(descr_out, CUSPARSE_MATRIX_TYPE_GENERAL);
cusparseSetMatIndexBase(descr_out, CUSPARSE_INDEX_BASE_ZERO);
int *d_row_csr;
cudaMalloc(reinterpret_cast<void **>(&d_row_csr), (4 + 1) * sizeof(int));
cusparseXcoo2csr(handle, d_row, 9, 4, d_row_csr, CUSPARSE_INDEX_BASE_ZERO);
std::vector<int> row_csr(4 + 1);
cudaMemcpy(row_csr.data(), d_row_csr, sizeof(int) * (4 + 1), cudaMemcpyDeviceToHost);
std::cout << "row" << std::endl;
for (int i : row_csr){
std::cout << i << std::endl; // prints 0 2 4 7 9 as expected
}
// however when I try to compress the column the same way...
int *d_col_csc;
cudaMalloc(reinterpret_cast<void **>(&d_col_csc), (5 + 1) * sizeof(int));
cusparseXcoo2csr(handle, d_col, 9, 5, d_col_csc, CUSPARSE_INDEX_BASE_ZERO);
std::vector<int> col_csc(5 + 1);
cudaMemcpy(col_csc.data(), d_col_csc, sizeof(int) * (5 + 1), cudaMemcpyDeviceToHost);
std::cout << "col" << std::endl;
for (int i : col_csc){
std::cout << i << std::endl; // prints 0 5 3 8 6 9, shouldn't it be 0 2 4 6 7 9?
}
return 0;
}

正如您所看到的，出于某种原因，从coo到csc的转换是不正确的。我暂时解决了这个问题，调用cusparseXcoo2csr进行coo到csr的转换，然后调用另一个cusparseDcsr2csc将csr中间结果转换为csc。这是额外的计算，所以我想知道如何使用cusparseXcoo2csr直接将coo转换为csc，如文档中所示。