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Nonstationary multisplittings with general weighting matrices

By Violeta Migallón, Jose Penadés and Daniel B. Szyld


In the convergence theory of multisplittings for symmetric positive definite (s.p.d.) matrices it is usually assumed that the weighting matrices are scalar matrices, i.e., multiples of the identity. In this paper, this restrictive condition is eliminated. In its place it is assumed that more than one (inner) iteration is performed in each processor (or block). The theory developed here is applied to nonstationary multisplittings for s.p.d. matrices, as well as to two-stage multisplittings for symmetric positive semidefinite matrices.This research was supported by Spanish DGESIC grant PB98-0977 and by National Science Foundation grants INT-9521226 and DMS-9973219

Topics: Iterative methods, Linear systems, Symmetric positive definite matrices, Block methods, Parallel algorithms, Multisplitting, Two-stage, Nonstationary, Ciencia de la Computación e Inteligencia Artificial
Publisher: Society for Industrial and Applied Mathematics
Year: 2001
DOI identifier: 10.1137/S0895479800367038
OAI identifier:

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