Application of the inverse fast multipole method as a preconditioner in a 3D Helmholtz boundary element method

JOURNAL OF COMPUTATIONAL PHYSICS

卷:341

Article

Takahashi, Toru¹  Coulier, Pieter^2,3  Darve, Eric³ 

[1] Nagoya Univ, Dept Mech Sci & Engn, Furo Cho, Nagoya, Aichi 4648603, Japan

[2] Katholieke Univ Leuven, Dept Civil Engn, Kasteelpk Arenberg 40, B-3001 Leuven, Belgium

[3] Stanford Univ, Dept Mech Engn, 496 Lomita Mall, Stanford, CA 94305 USA

关键词: Fast multipole method;    Boundary element method;    Inverse fast multipole method;    Iterative solver;    Preconditioning;    Low rank compression;   

DOI  :  10.1016/j.jcp.2017.04.016

来源: Elsevier

【 摘 要 】

We investigate an efficient preconditioning of iterative methods (such as GMRES) for solving dense linear systems Ax = b that follow from a boundary element method (BEM) for the 3D Helmholtz equation, focusing on the low-frequency regime. While matrix-vector products in GMRES can be accelerated through the low-frequency fast multipole method (LFFMM), the BEM often remains computationally expensive due to the large number of GMRES iterations. We propose the application of the inverse fast multipole method (IFMM) as a preconditioner to accelerate the convergence of GMRES. The IFMM is in essence an approximate direct solver that uses a multilevel hierarchical decomposition and low rank approximations. The proposed IFMM-based preconditioning has a tunable parameter epsilon that balances the cost to construct a preconditioner M, which is an approximation of A(-1), and the cost to perform the iterative process by means of M. Namely, using a small (respectively, large) value of s takes a long (respectively, short) time to construct M, while the number of iterations can be small (respectively, large). A comprehensive set of numerical examples involving various boundary value problems with complicated geometries and mixed boundary conditions is presented to validate the efficiency of the proposed method. We show that the IFMM preconditioner (with a nearly optimal s of 10(-2)) clearly outperforms some common preconditioners for the BEM, achieving 1.2-10.8 times speed-up of the computations, in particular when the scale of the underlying scatterer is about five wavelengths or more. In addition, the IFMM preconditioner is capable of solving complicated problems (in a reasonable amount of time) that BD preconditioner can not. (C) 2017 Elsevier Inc. All rights reserved.

【 授权许可】

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