ParAC parallelizes randomized approximate Cholesky factorization for Laplacian matrices using dynamic dependency tracking and no nested-dissection preprocessing, with CPU and GPU implementations that beat several standard preconditioners on many test problems.
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Parallel GPU-Accelerated Randomized Construction of Approximate Cholesky Preconditioners
ParAC parallelizes randomized approximate Cholesky factorization for Laplacian matrices using dynamic dependency tracking and no nested-dissection preprocessing, with CPU and GPU implementations that beat several standard preconditioners on many test problems.