Algebraic sub-structuring for electromagnetic applications

Authors:
Chao Yang;Weiguo Gao;Zhaojun Bai;Xiaoye S. Li;Lie-Quan Lee;Parry Husbands;Esmond G. Ng
Affiliations:
Computational Research Division, Lawrence Berkeley National Lab, Berkeley, CA;Computational Research Division, Lawrence Berkeley National Lab, Berkeley, CA;Department of Computer Science, The University of California at Davis, Davis, CA;Computational Research Division, Lawrence Berkeley National Lab, Berkeley, CA;Stanford Linear Accelerator Center, Menlo Park, CA;Computational Research Division, Lawrence Berkeley National Lab, Berkeley, CA;Computational Research Division, Lawrence Berkeley National Lab, Berkeley, CA
Venue:
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
Year:
2004

Citing 4
Cited 1

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The symmetric eigenvalue problem

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Construction of Nearly Orthogonal Nedelec Bases for Rapid Convergence with Multilevel Preconditioned Solvers

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An Algebraic Substructuring Method for Large-Scale Eigenvalue Calculation

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Improving eigenpairs of automated multilevel substructuring with subspace iterations

Computers and Structures

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Abstract

Algebraic sub-structuring refers to the process of applying matrix reordering and partitioning algorithms to divide a large sparse matrix into smaller submatrices from which a subset of spectral components are extracted and combined to form approximate solutions to the original problem. In this paper, we show that algebraic sub-structuring can be effectively used to solve generalized eigenvalue problems arising from the finite element analysis of an accelerator structure.