In cuSPARSE, you can solve a sparse triangular linear system by calling
cusparse<t>csrsv2_solve(). However, you need to call
From what I read in the doc, it seems:
csrsv2might need additional memory, and
csrsv2_bufferSize()tells you how much that should be.
csrsv2_analysis()analyze the sparsity pattern of the coefficient matrix. It may or may not improve the performance of
The documentation says:
csrsv2_analysis()reports a structural zero and computes level information.
- The level information may not improve the performance. For example, a tridiagonal matrix has no parallelism.
csrsv2_solve()reports the first numerical zero, including a structural zero.
So here is what I don't understand:
- What are those things: structural zero, numerical zero, level information?
- And why tridiagonal matrices have no parallellism? What does parallelism mean here?
I guess structural zero and numerical zero have something to do with the singularity of the matrix, but I need clarification on that.