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European Parallel Virtual Machine / Message Passing Interface Users’ Group Meeting

EuroPVM/MPI 1998: Recent Advances in Parallel Virtual Machine and Message Passing Interface pp 323–330Cite as

Coarse grained parallel Monte Carlo algorithms for solving SLAE using PVM

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1497))

Abstract

The problem of solving System of Linear Algebraic Equations (SLAE) by parallel Monte Carlo numerical methods is considered. Three Monte Carlo algorithms are presented. In case when copy of the matrix is sent to each processor the execution time for solving SLAE by Monte Carlo on p processors is bounded by O(nNT/p) (excluding the initial loading of the data) where N is the number of chains and T is the length of the chain in the stochastic process, which are independent of matrix size n.

Numerical tests are performed for a number of dense and sparse test matrices using PVM on a cluster of workstations.

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Authors and Affiliations

  1. Department of Computer Science, University of Liverpool, Chadwick Building, Peach Street, L69 7ZP, Liverpool, UK

    V. Alexandrov & K. Taft

  2. School of Computer Science, Carleton University, K1S 5B6, Ottawa, Canada

    F. Dehne

  3. Faculty of Computer Science, DalTech, Dalhousie University, P.O. Box 1000, B3J 2X4, Halifax, NS, Canada

    A. Rau-Chaplin

Authors
  1. V. Alexandrov
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  2. F. Dehne
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  3. A. Rau-Chaplin
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  4. K. Taft
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Editor information

Vassil Alexandrov Jack Dongarra

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© 1998 Springer-Verlag Berlin Heidelberg

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Alexandrov, V., Dehne, F., Rau-Chaplin, A., Taft, K. (1998). Coarse grained parallel Monte Carlo algorithms for solving SLAE using PVM. In: Alexandrov, V., Dongarra, J. (eds) Recent Advances in Parallel Virtual Machine and Message Passing Interface. EuroPVM/MPI 1998. Lecture Notes in Computer Science, vol 1497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056591

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  • DOI: https://doi.org/10.1007/BFb0056591

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65041-6

  • Online ISBN: 978-3-540-49705-9

  • eBook Packages: Springer Book Archive

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