|Parallel Symbolic Cholesky Factorization
|Year of Publication
|Ribizel, T., and H. Anzt
|SC-W 2023: Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis
We present a hybrid sequential/parallel symbolic Cholesky factorization algorithm that computes the sparsity pattern of the symbolic factors in parallel. We evaluate the performance on a large subset of the SuiteSparse matrix collection and multicore CPUs as well as flagship GPUs by AMD and NVIDIA, achieving speedups of an order of magnitude compared to a state-of-the-art sequential symbolic Cholesky factorization.
Parallel Symbolic Cholesky Factorization
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