• DocumentCode
    3591149
  • Title

    Coupling-aware graph partitioning algorithms: Preliminary study

  • Author

    Predari, Maria ; Esnard, Aurelien

  • Author_Institution
    LaBRI, Univ. Bordeaux, Talence, France
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    10
  • Abstract
    In the field of scientific computing, load balancing is a major issue that determines the performance of parallel applications. Nowadays, simulations of real-life problems are becoming more and more complex, involving numerous coupled codes, representing different models. In this context, reaching high performance can be a great challenge. In this paper, we present graph partitioning techniques, called co-partitioning, that address the problem of load balancing for two coupled codes: the key idea is to perform a “coupling-aware” partitioning, instead of partitioning these codes independently, as it is usually done. Finally, we present a preliminary experimental study which compares our methods against the usual approach.
  • Keywords
    graph theory; parallel processing; resource allocation; co-partitioning; coupling-aware graph partitioning algorithm; load balancing; parallel application; scientific computing; Atmospheric modeling; Computational modeling; Couplings; Load management; Load modeling; Partitioning algorithms; Program processors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing (HiPC), 2014 21st International Conference on
  • Print_ISBN
    978-1-4799-5975-4
  • Type

    conf

  • DOI
    10.1109/HiPC.2014.7116879
  • Filename
    7116879