用于有限元分析的三种直接线性求解器的注意事项

IF 2.7 3区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY International Journal for Numerical Methods in Engineering Pub Date : 2024-05-30 DOI:10.1002/nme.7545

Dorival M. Pedroso

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摘要

稀疏矩阵大型线性方程组的求解是有限元分析的一个重要组成部分。本文研究了三种线性求解器：MUMPS、UMFPACK 和 Intel DSS (PARDISO)。这些求解器通常作为 "黑盒 "使用。但是，在实施过程中必须注意一些注意事项。例如，求解器可能会产生不正确的结果，或者在多线程环境中表现极差。我们对这些问题进行了演示，并提出了解决建议。此外，还介绍了一些性能基准，重点关注多线程行为。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Caveats of three direct linear solvers for finite element analyses

The solution of large linear systems of equations with sparse matrices is a critical component of finite element analyses. Three linear solvers are investigated here: MUMPS, UMFPACK, and Intel DSS (PARDISO). Often, these solvers are employed as “black boxes.” However, some caveats in their implementation must be observed. For instance, the solvers may yield incorrect results or perform extremely poorly in a multithread environment. These issues are demonstrated, and suggestions to fix them are provided. Some performance benchmarks are also presented with a focus on the multithreaded behavior.

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来源期刊

International Journal for Numerical Methods in Engineering 工程技术-工程：综合

CiteScore

5.70

自引率

6.90%

发文量

276

审稿时长

5.3 months

期刊介绍： The International Journal for Numerical Methods in Engineering publishes original papers describing significant, novel developments in numerical methods that are applicable to engineering problems. The Journal is known for welcoming contributions in a wide range of areas in computational engineering, including computational issues in model reduction, uncertainty quantification, verification and validation, inverse analysis and stochastic methods, optimisation, element technology, solution techniques and parallel computing, damage and fracture, mechanics at micro and nano-scales, low-speed fluid dynamics, fluid-structure interaction, electromagnetics, coupled diffusion phenomena, and error estimation and mesh generation. It is emphasized that this is by no means an exhaustive list, and particularly papers on multi-scale, multi-physics or multi-disciplinary problems, and on new, emerging topics are welcome.

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