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Using Clustering to Address Heterogeneity and Dynamism in Parallel Scientific Applications

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High Performance Computing – HiPC 2005 (HiPC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3769))

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Abstract

The dynamism and space-time heterogeneity exhibited by structured adaptive mesh refinement (SAMR) applications makes their scalable parallel implementation a significant challenge. This paper investigates an adaptive hierarchical multi-partitioner (AHMP) framework that dynamically applies multiple partitioners to different regions of the domain, in a hierarchical manner, to match the local requirements of these regions. Key components of the AHMP framework include a segmentation-based clustering algorithm (SBC) for identifying regions in the domain with relatively homogeneous partitioning requirements, mechanisms for characterizing the partitioning requirements, and a runtime system for selecting, configuring and applying the most appropriate partitioner to each region. The AHMP framework has been implemented and experimentally evaluated on up to 1280 processors of the IBM SP4 cluster at San Diego Supercomputer Center.

The research presented in this paper is supported in part by the National Science Foundation via grants numbers ACI 9984357, EIA 0103674, EIA 0120934, ANI 0335244, CNS 0305495, CNS 0426354 and IIS 0430826.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Oklahoma State University, OK, 74078, USA

    Xiaolin Li

  2. Department of Electrical & Computer Engineering, Rutgers University, NJ, 08854, USA

    Manish Parashar

Authors
  1. Xiaolin Li
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  2. Manish Parashar
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Editor information

Editors and Affiliations

  1. College of Computing, Georgia Institute of Technology, 30332, Atlanta, GA, USA

    David A. Bader

  2. Department of Electrical and Computer Engineering, Rutgers, the State University of New Jersey, 94 Brett Road, 08854, Piscataway, NJ, USA

    Manish Parashar

  3. Satyam Computer Services Ltd., Indian Institute of Science Campus, Entrepreneurship Centre, SID Block, 560 012, Bangalore, India

    Varadarajan Sridhar

  4. Department of Electrical Engineering, University of Southern California, 90089-2562, Los Angeles, CA, USA

    Viktor K. Prasanna

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© 2005 Springer-Verlag Berlin Heidelberg

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Li, X., Parashar, M. (2005). Using Clustering to Address Heterogeneity and Dynamism in Parallel Scientific Applications. In: Bader, D.A., Parashar, M., Sridhar, V., Prasanna, V.K. (eds) High Performance Computing – HiPC 2005. HiPC 2005. Lecture Notes in Computer Science, vol 3769. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11602569_28

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  • DOI: https://doi.org/10.1007/11602569_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30936-9

  • Online ISBN: 978-3-540-32427-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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