我正在尝试将一个线性问题移植到CUDA,以加快解决时间。我已经成功地使用cusolverDn来处理GPU上的密集问题。然而,当我试图使用cusolverSpScsrlsvchol将其应用于稀疏问题时,我总是得到一个分段错误。
为了调试这个问题,我使用了CUDA计算消毒器,并收到了以下输出:
$ /c/Programme/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v11.7/bin/compute-sanitizer.bat --tool memcheck bin/FEMaster_gpu.exe
========= COMPUTE-SANITIZER
========= Error: process didn't terminate successfully
========= Target application returned an error
========= ERROR SUMMARY: 0 errors
Segmentation fault
我将问题缩小到以下最小代码片段:
cusolverSpHandle_t handle_cusolver_sp;
cusparseHandle_t handle_cusparse;
// loading handles
cusolverSpCreate(&handle_cusolver_sp);
cusparseCreate (&handle_cusparse);
// get properties
cudaSetDevice(0);
// create csr arrays on cpu
float host_csr_values[4]{1,1,1,1};
int host_csr_col_id[4]{0,1,2,3};
int host_csr_row_pt[5]{0,1,2,3,4};
float host_rhs [4]{0,3,7,1};
int host_singular [1]{0};
// allocate arrays on the gpu
float* dev_csr_values;
int * dev_csr_col_id;
int * dev_csr_row_pt;
float* dev_rhs;
int * dev_singular;
runtime_assert_cuda(cudaMalloc((void**) &dev_csr_values,4 * sizeof(float)));
runtime_assert_cuda(cudaMalloc((void**) &dev_csr_col_id,4 * sizeof(int )));
runtime_assert_cuda(cudaMalloc((void**) &dev_csr_row_pt,5 * sizeof(int )));
runtime_assert_cuda(cudaMalloc((void**) &dev_rhs ,4 * sizeof(float)));
runtime_assert_cuda(cudaMalloc((void**) &dev_singular ,1 * sizeof(int )));
// move data to gpu
runtime_assert_cuda(cudaMemcpy(dev_csr_values, host_csr_values, 4 * sizeof(float), cudaMemcpyHostToDevice));
runtime_assert_cuda(cudaMemcpy(dev_csr_col_id, host_csr_col_id, 4 * sizeof(int ), cudaMemcpyHostToDevice));
runtime_assert_cuda(cudaMemcpy(dev_csr_row_pt, host_csr_row_pt, 5 * sizeof(int ), cudaMemcpyHostToDevice));
runtime_assert_cuda(cudaMemcpy(dev_rhs , host_rhs , 4 * sizeof(float), cudaMemcpyHostToDevice));
// create matrix descriptor
cusparseMatDescr_t descr;
runtime_assert_cuda(cusparseCreateMatDescr(&descr));
runtime_assert_cuda(cusparseSetMatType (descr, CUSPARSE_MATRIX_TYPE_GENERAL));
runtime_assert_cuda(cusparseSetMatIndexBase(descr, CUSPARSE_INDEX_BASE_ZERO ));
runtime_assert_cuda(cusolverSpScsrlsvchol(handle_cusolver_sp,
4,
4,
descr,
dev_csr_values,
dev_csr_row_pt,
dev_csr_col_id,
dev_rhs,
0, // tolerance
0, // reorder
dev_rhs,
dev_singular));
稀疏矩阵的值就是对角矩阵的值。
为了简单起见,我删除了内存释放、输出检索和其他类似的调用。这段代码看起来很简单,但它会导致一个分段错误。此问题特别是在调用cusolverSpScsrlsvchol期间发生。
我在这个问题上被困了一天多,我不知道为什么它不起作用。任何帮助将不胜感激!
1条答案
按热度按时间uurity8g1#
API声明奇异性参数应该在主机存储器空间中,而不是设备中。