Hi, my name is Ana.
I have been used function in the NVIDIA library: Cusparse and Cublas. I have been implemented in my program the conjugate gradient method using these functions. Thus, it´s worked very well!
However, when I used Cholesky preconditioned and CG iterative methods, in another case, one problem occurred with cusparseScsric0 function. I am using matrix from The University of Florida in my algorithms with symmetric positive definite linear systems.
Thus, I have two questions:
1 – Incomplete Cholesky factorization could be: op(A)aproximately R R^T? I read from Matrix Computation´s book (Golub & Van Loan, 2rd Ed., section 10.3.2, pg. 530) about this function.
2 - In the manual “Cuda_cusparse” there is an information about the cusparseScsric0. The function is defined Hermitian/symmetric positive definite sparse matrix (CSR storage format by the three arrays csrValM, csrRowPtrA and csrColIndA). I didn’t understand the supported matrix type: CUSPARSE_MATRIX_TYPE_GENERAL, because only a lower or upper Hermitian/symmetric part of the matrix is actually stored. I used lower or upper or general matrix and I did none result. The results in all the simulations were: CUSPARSE_STATUS_MATRIX_TYPE_NOT_SUPPORTED.
Please, I need your help!