Parallel iterative solvers for sparse linear systems in circuit simulation

For the solution of sparse linear systems from circuit simulation whose coefficient matrices include a few dense rows and columns, a parallel iterative algorithm with distributed Schur complement preconditioning is presented. The parallel efficiency of the solver is increased by transforming the equ...

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Bibliographic Details
Published inFuture generation computer systems Vol. 21; no. 8; pp. 1275 - 1284
Main Authors Basermann, A., Jaekel, U., Nordhausen, M., Hachiya, K.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.10.2005
Subjects
Circuit simulation
Parallel iterative solver
Partitioning
Preconditioning
Reordering
System reduction
Parallel iterative solver
Circuit simulation
Partitioning
Preconditioning
System reduction
Reordering
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Summary:For the solution of sparse linear systems from circuit simulation whose coefficient matrices include a few dense rows and columns, a parallel iterative algorithm with distributed Schur complement preconditioning is presented. The parallel efficiency of the solver is increased by transforming the equation system into a problem without dense rows and columns as well as by exploitation of parallel graph partitioning methods. The costs of local, incomplete LU decompositions are decreased by fill-in reducing reordering methods of the matrix and a threshold strategy for the factorization. The efficiency of the parallel solver is demonstrated with real circuit simulation problems on PC clusters.
ISSN:0167-739X
1872-7115
DOI:10.1016/j.future.2004.09.007