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International Workshop on Applied Parallel Computing

PARA 1998: Applied Parallel Computing Large Scale Scientific and Industrial Problems pp 332–336Cite as

A parallel algorithm for computing the extremal eigenvalues of very large sparse matrices

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1541))

Abstract

Quantum mechanics often give rise to problems where one needs to find a few eigenvalues of very large sparse matrices. The size of the matrices is such that it is not possible to store them in main memory but instead they must be generated on the fly.

In this paper the method of coordinate relaxation is applied to one class of such problems. A parallel algorithm based on graph coloring is proposed. Experimental results on a Cray Origin 2000 super computer show that the algorithm converges fast and that it also scales well as more processors are applied.

For full paper, see http://www.ii.uib.no/~fredrikm

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References

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Author information

Authors and Affiliations

  1. Department of Informatics, University of Bergen, N-5020, Bergen, Norway

    Fredrik Manne

Authors
  1. Fredrik Manne
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Editor information

Bo Kågström Jack Dongarra Erik Elmroth Jerzy Waśniewski

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© 1998 Springer-Verlag Berlin Heidelberg

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Manne, F. (1998). A parallel algorithm for computing the extremal eigenvalues of very large sparse matrices. In: Kågström, B., Dongarra, J., Elmroth, E., Waśniewski, J. (eds) Applied Parallel Computing Large Scale Scientific and Industrial Problems. PARA 1998. Lecture Notes in Computer Science, vol 1541. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095354

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  • DOI: https://doi.org/10.1007/BFb0095354

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65414-8

  • Online ISBN: 978-3-540-49261-0

  • eBook Packages: Springer Book Archive

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