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New subclasses of block H-matrices with applications to parallel decomposition-type relaxation methods

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Abstract

The parallel decomposition-type relaxation methods for solving large sparse systems of linear equations on SIMD multiprocessor systems have been proposed in [3] and [2]. In case when the coefficient matrix of the linear system is a block \(H\)-matrix, sufficient conditions for the convergence of methods given in [2], [3] have been further improved in [5] and [4]. From the practical point of view, the convergence area obtained there is not always suitable for computation, so we propose new, easily computable ones, for some special subclasses of block \(H\)-matrices. Furthermore, this approach improves the already known convergence area for the class of block strictly diagonally dominant (SDD) matrices.

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Authors and Affiliations

  1. Department of Mathematics and Informatics, Faculty of Science, University of Novi Sad, Trg D. Obradovica 4, Novi Sad, 21000, Serbia and Montenegro

    Ljiljana Cvetković & Vladimir Kostić

Authors
  1. Ljiljana Cvetković
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  2. Vladimir Kostić
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Correspondence to Vladimir Kostić.

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Cvetković, L., Kostić, V. New subclasses of block H-matrices with applications to parallel decomposition-type relaxation methods. Numer Algor 42, 325–334 (2006). https://doi.org/10.1007/s11075-006-9031-9

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  • DOI: https://doi.org/10.1007/s11075-006-9031-9

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