SlabLU: A Two-Level Sparse Direct Solver for Elliptic PDEs

Fuente: arXiv
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Autori principali: Yesypenko, Anna, Martinsson, Per-Gunnar
Natura: Preprint
Pubblicazione: 2022
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author Yesypenko, Anna
Martinsson, Per-Gunnar
author_facet Yesypenko, Anna
Martinsson, Per-Gunnar
contents The paper describes a sparse direct solver for the linear systems that arise from the discretization of an elliptic PDE on a two dimensional domain. The scheme decomposes the domain into thin subdomains, or ``slabs'' and uses a two-level approach that is designed with parallelization in mind. The scheme takes advantage of $\mathcal H^2$-matrix structure emerging during factorization and utilizes randomized algorithms to efficiently recover this structure. As opposed to multi-level nested dissection schemes that incorporate the use of $\mathcal H$ or $\mathcal H^2$ matrices for a hierarchy of front sizes, SlabLU is a two-level scheme which only uses $\mathcal H^2$-matrix algebra for fronts of roughly the same size. The simplicity allows the scheme to be easily tuned for performance on modern architectures and GPUs. The solver described is compatible with a range of different local discretizations, and numerical experiments demonstrate its performance for regular discretizations of rectangular and curved geometries. The technique becomes particularly efficient when combined with very high-order accurate multi-domain spectral collocation schemes. With this discretization, a Helmholtz problem on a domain of size $1000 λ\times 1000 λ$ (for which $N=100 \rm{M}$) is solved in 15 minutes to 6 correct digits on a high-powered desktop with GPU acceleration.
format Preprint
id arxiv_https___arxiv_org_abs_2211_07572
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle SlabLU: A Two-Level Sparse Direct Solver for Elliptic PDEs
Yesypenko, Anna
Martinsson, Per-Gunnar
Numerical Analysis
The paper describes a sparse direct solver for the linear systems that arise from the discretization of an elliptic PDE on a two dimensional domain. The scheme decomposes the domain into thin subdomains, or ``slabs'' and uses a two-level approach that is designed with parallelization in mind. The scheme takes advantage of $\mathcal H^2$-matrix structure emerging during factorization and utilizes randomized algorithms to efficiently recover this structure. As opposed to multi-level nested dissection schemes that incorporate the use of $\mathcal H$ or $\mathcal H^2$ matrices for a hierarchy of front sizes, SlabLU is a two-level scheme which only uses $\mathcal H^2$-matrix algebra for fronts of roughly the same size. The simplicity allows the scheme to be easily tuned for performance on modern architectures and GPUs. The solver described is compatible with a range of different local discretizations, and numerical experiments demonstrate its performance for regular discretizations of rectangular and curved geometries. The technique becomes particularly efficient when combined with very high-order accurate multi-domain spectral collocation schemes. With this discretization, a Helmholtz problem on a domain of size $1000 λ\times 1000 λ$ (for which $N=100 \rm{M}$) is solved in 15 minutes to 6 correct digits on a high-powered desktop with GPU acceleration.
title SlabLU: A Two-Level Sparse Direct Solver for Elliptic PDEs
topic Numerical Analysis
url https://arxiv.org/abs/2211.07572