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A Framework for Efficient Sparse LU Factorization in a Cluster Based Platform

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Advanced Environments, Tools, and Applications for Cluster Computing (IWCC 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2326))

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Abstract

In this paper we address necessary issues in developing an efficient parallel sparse LU factorization without pivoting in a cluster technology. The algorithm we propose reduces the communications between processors by using an adequate mapping algorithm. The volume of communications during parallel symbolic factorization is decreased by using the notion of symmetric pruning of the directed graph of L.

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Author information

Authors and Affiliations

  1. INRIA Lorraine, Université Henri Poincaré, Nancy, France

    Laura Grigori

Authors
  1. Laura Grigori
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Editor information

Editors and Affiliations

  1. Computer Science Department, University College Cork, College Road, Cork, Ireland

    Dan Grigoras

  2. Information and Computer Science Department, University of California, 444 Computer Science Building, Irvine, CA, 92697-3425, USA

    Alex Nicolau

  3. Laboratoire d’Informatique Fondamentale de Lille (LIFL), University Lille 1, 59655, Villeneuve d’Ascq, France

    Bernard Toursel

  4. LIP, University Paris 6, 8, rue du Capitaine Scott, 75015, Paris, France

    Bertil Folliot

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© 2002 Springer-Verlag Berlin Heidelberg

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Grigori, L. (2002). A Framework for Efficient Sparse LU Factorization in a Cluster Based Platform. In: Grigoras, D., Nicolau, A., Toursel, B., Folliot, B. (eds) Advanced Environments, Tools, and Applications for Cluster Computing. IWCC 2001. Lecture Notes in Computer Science, vol 2326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47840-X_11

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  • DOI: https://doi.org/10.1007/3-540-47840-X_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43672-0

  • Online ISBN: 978-3-540-47840-9

  • eBook Packages: Springer Book Archive

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