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A Framework for Integrating Network Information into Distributed Iterative Solution of Sparse Linear Systems

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High Performance Computing for Computational Science — VECPAR 2002 (VECPAR 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2565))

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Abstract

Recently, we have proposed a design of an easy-to-use network information discovery tool that can interface with a distributed application non-intrusively and without incurring much overhead. The application is notified of the network changes in a timely manner and may react to the changes by invoking the adaptation mechanisms encapsulated in notification handlers. Here we describe possible adaptations of a commonly used scientific computing kernel, distributed sparse largescale linear system solution code.

This work was supported in part by NSF under grants NSF/ACI-0000443 and NSF/INT-0003274, and in part by the Minnesota Supercomputing Institute

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Minnesota, 55414, Minneapolis, MN, USA

    Devdatta Kulkarni

  2. Department of Computer Science, University of Minnesota, 55812, Duluth, MN, USA

    Masha Sosonkina

Authors
  1. Devdatta Kulkarni
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  2. Masha Sosonkina
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Editor information

Editors and Affiliations

  1. Faculdade de Engenharia da, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    José M. L. M. Palma  & A. Augusto Sousa  & 

  2. Department of Computer Science, University of Tennessee, 37996-1301, Knoxville, TN, USA

    Jack Dongarra

  3. Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Camino de Vera, s/n, Apartado 22012, 46020, Valencia, Spain

    Vicente Hernández

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© 2003 Springer-Verlag Berlin Heidelberg

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Kulkarni, D., Sosonkina, M. (2003). A Framework for Integrating Network Information into Distributed Iterative Solution of Sparse Linear Systems. In: Palma, J.M.L.M., Sousa, A.A., Dongarra, J., Hernández, V. (eds) High Performance Computing for Computational Science — VECPAR 2002. VECPAR 2002. Lecture Notes in Computer Science, vol 2565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36569-9_29

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  • DOI: https://doi.org/10.1007/3-540-36569-9_29

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  • Print ISBN: 978-3-540-00852-1

  • Online ISBN: 978-3-540-36569-3

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