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European Conference on Parallel Processing

Euro-Par 2011: Euro-Par 2011: Parallel Processing Workshops pp 334–344Cite as

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On Partitioning Problems with Complex Objectives

On Partitioning Problems with Complex Objectives

  • Kamer Kaya30,
  • François-Henry Rouet31 &
  • Bora Uçar32 
  • Conference paper
  • 1339 Accesses

  • 2 Citations

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7155)

Abstract

Hypergraph and graph partitioning tools are used to partition work for efficient parallelization of many sparse matrix computations. Most of the time, the objective function that is reduced by these tools relates to reducing the communication requirements, and the balancing constraints satisfied by these tools relate to balancing the work or memory requirements. Sometimes, the objective sought for having balance is a complex function of a partition. We mention some important class of parallel sparse matrix computations that have such balance objectives. For these cases, the current state of the art partitioning tools fall short of being adequate. To the best of our knowledge, there is only a single algorithmic framework in the literature to address such balance objectives. We propose another algorithmic framework to tackle complex objectives and experimentally investigate the proposed framework.

Keywords

  • Hypergraph partitioning
  • graph partitioning
  • sparse matrix partitioning
  • parallel sparse matrix computations

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Author information

Authors and Affiliations

  1. CERFACS, Toulouse, France

    Kamer Kaya

  2. Université de Toulouse, INPT (ENSEEIHT)-IRIT, France

    François-Henry Rouet

  3. CNRS and ENS Lyon, France

    Bora Uçar

Authors
  1. Kamer Kaya
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  2. François-Henry Rouet
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  3. Bora Uçar
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Editor information

Editors and Affiliations

  1. Scilytics, Koellnerhofgasse 3/15A, 1010, Vienna, Austria

    Michael Alexander

  2. ICAR-CNR, Via P. Castellino, 111, 80131, Napoli, Italy

    Pasqua D’Ambra

  3. University of Amsterdam, 1090, Amsterdam, Netherlands

    Adam Belloum

  4. Innovative Computing Laboratory, The University of Tennessee, USA

    George Bosilca

  5. Department of Experimental Medicine and Clinic, University Magna Græcia, 88100, Catanzaro, Italy

    Mario Cannataro

  6. Computer Science Department, University of Pisa, Italy

    Marco Danelutto

  7. Second University of Naples, Italy

    Beniamino Di Martino

  8. TU München, Boltzmannstr. 3, 85748, Garching, Germany

    Michael Gerndt

  9. Equipe Runtime, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Emmanuel Jeannot & Raymond Namyst & 

  10. Equipe HIEPACS, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Jean Roman

  11. Oak Ridge National Laboratory, Computer Science and Mathematics Division, 37831-6164, Oak Ridge, TN, USA

    Stephen L. Scott

  12. Department of Scientific Computing, University of Vienna, Nordbergstr. 15/3C, 1090, Vienna, Austrial

    Jesper Larsson Traff

  13. Computer Science and Mathematics Division, Oak Ridge National Laboratory, 37831, Oak Ridge, TN, USA

    Geoffroy Vallée

  14. Technische Universität München, Germany

    Josef Weidendorfer

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© 2012 Springer-Verlag Berlin Heidelberg

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Kaya, K., Rouet, FH., Uçar, B. (2012). On Partitioning Problems with Complex Objectives. In: Alexander, M., et al. Euro-Par 2011: Parallel Processing Workshops. Euro-Par 2011. Lecture Notes in Computer Science, vol 7155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29737-3_38

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  • DOI: https://doi.org/10.1007/978-3-642-29737-3_38

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  • Print ISBN: 978-3-642-29736-6

  • Online ISBN: 978-3-642-29737-3

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