A fast solver for FEM analyses using the parallelized algebraic multigrid method

The algebraic multigrid (AMG) method is an efficient solver for linear systems arising in finite element analyses. The AMG method is applicable at a matrix level, different from the geometric multigrid solvers. This paper proposes a combination of the parallel processing technique and the AMG method...

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Bibliographic Details
Published inIEEE transactions on magnetics Vol. 38; no. 2; pp. 369 - 372
Main Authors Mifune, T., Iwashita, T., Shimasaki, M.
Format Journal Article Conference Proceeding
LanguageEnglish
Published New York, NY IEEE 01.03.2002
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algebra
Applied classical electromagnetism
Computation
Electromagnetic analysis
Electromagnetic fields
Electromagnetism; electron and ion optics
Exact sciences and technology
Finite element method
Finite element methods
Fundamental areas of phenomenology (including applications)
Interpolation
Linear systems
Magnetic analysis
Magnetism
Magnetostatics
Magnetostatics; magnetic shielding, magnetic induction, boundary-value problems
Mathematical models
Parallel processing
Performance analysis
Physics
Scalability
Solvers
Finite element method
Linear systems
Electromagnetism
Digital simulation
Theoretical study
Algebraic method
Parallel computation
Maxwell equations
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Summary:The algebraic multigrid (AMG) method is an efficient solver for linear systems arising in finite element analyses. The AMG method is applicable at a matrix level, different from the geometric multigrid solvers. This paper proposes a combination of the parallel processing technique and the AMG method as a fast solver for electromagnetic field analyses. While the AMG method consists of a setup phase and a solution phase, parallel processing of the former phase is difficult. We present the use of long-range interpolation instead of the conventional direct interpolation for improvement of the parallel efficiency of the AMG setup phase. A magnetostatic analysis and an eddy-current analysis show the solver performance. The numerical results show that parallelized AMG is a fast solver and has sufficient scalability, as compared with the conventional solver.
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ISSN:0018-9464
1941-0069
DOI:10.1109/20.996099