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Parallel Solution of Large Sparse SPD Linear Systems Based on Overlapping Domain Decomposition

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Parallel Computing Technologies (PaCT 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1662))

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Abstract

We present a parallel iterative solver for large sparse sym- metric positive definite (SPD) linear systems based on a new theory describing the convergence ofthe Preconditioned Conjugate Gradient (PCG) method and a proper combination ofa dvanced preconditioning strategies. Formally, the preconditioning can be interpreted as a special (nearly optimum from the viewpoint of the new PCG theory) version of overlapping domain decomposition with incomplete Cholesky solutions over subdomains. The estimates ofpa rallel efficiency are given as well as the results ofn umerical experiments for the serial and parallel versions oft he solver.

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Author information

Authors and Affiliations

  1. Computing Center RAS, Vavilov str. 40, 117967, Moscow, Russia

    Igor E. Kaporin & Igor N. Konshin

Authors
  1. Igor E. Kaporin
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  2. Igor N. Konshin
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Editor information

Editors and Affiliations

  1. Computing Center, 6 Lavrentiev Avenue, Novosibirsk, 630090, Russia

    Victor Malyshkin

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Kaporin, I.E., Konshin, I.N. (1999). Parallel Solution of Large Sparse SPD Linear Systems Based on Overlapping Domain Decomposition. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 1999. Lecture Notes in Computer Science, vol 1662. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48387-X_45

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  • DOI: https://doi.org/10.1007/3-540-48387-X_45

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66363-8

  • Online ISBN: 978-3-540-48387-8

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