Algebraic multigrid methods based on element preconditioning
This paper presents a new algebraic multigrid (AMG) solution strategy for large linear systems with a sparse matrix arising from a finite element discretization of some self-adjoint, second order, scalar, elliptic partial differential equation. The AMG solver is based on Ruge/Stübens method. Ruge/St...
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Published in | International journal of computer mathematics Vol. 78; no. 4; pp. 575 - 598 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Gordon and Breach Science Publishers
01.01.2001
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Subjects | |
Online Access | Get full text |
ISSN | 0020-7160 1029-0265 |
DOI | 10.1080/00207160108805133 |
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Summary: | This paper presents a new algebraic multigrid (AMG) solution strategy for large linear systems with a sparse matrix arising from a finite element discretization of some self-adjoint, second order, scalar, elliptic partial differential equation. The AMG solver is based on Ruge/Stübens method. Ruge/Stübens algorithm is robust for M-matrices, but unfortunately the "region of robustness" between symmetric positive definite M-matrices and general symmetric positive definite matrices is very fuzzy.
For this reason the so-called element preconditioning technique is introduced in this paper. This technique aims at the construction of an M-matrix that is spectrally equivalent to the original stiffness matrix. This is done by solving small restricted optimization problems. AMG applied to the spectrally equivalent M-matrix instead of the original stiffness matrix is then used as a preconditioner in the conjugate gradient method for solving the original problem.
The numerical experiments show the efficiency and the robustness of the new preconditioning method for a wide class of problems including problems with anisotropic elements. |
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ISSN: | 0020-7160 1029-0265 |
DOI: | 10.1080/00207160108805133 |