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Hybrid Parallelization of a Large-Scale Heart Model

  • Dorian Krause
  • Mark Potse
  • Thomas Dickopf
  • Rolf Krause
  • Angelo Auricchio
  • Frits Prinzen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7174)

Abstract

The simulation of the electrophysiology of the heart is challenging due to its multiscale nature requiring the use of high spatial resolutions. Hence, it is important to efficiently utilize large parallel machines. In this article, we present a code designed to meet these scalability challenges on contemporary multicore-based massively parallel architectures. It is based on a well-established model originally designed for shared-memory systems. To improve scalability and extend support to distributed-memory architectures, we developed a hybrid OpenMP-MPI code. The new code shows excellent scalability up to 8448 cores with both explicit and implicit time discretizations. We present an in-depth analysis of the advantages of hybrid parallelization for this type of application.

Keywords

Communication Time Multiple Thread Strong Scaling Bidomain Model Implicit Time Discretizations 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dorian Krause
    • 1
  • Mark Potse
    • 2
  • Thomas Dickopf
    • 1
  • Rolf Krause
    • 1
  • Angelo Auricchio
    • 3
  • Frits Prinzen
    • 2
  1. 1.Institute of Computational ScienceUniversity of LuganoSwitzerland
  2. 2.Cardiovascular Research InstituteMaastricht UniversityThe Netherlands
  3. 3.Fondazione Cardiocentro TicinoLuganoSwitzerland

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