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Load Balancing and Auto-Tuning for Heterogeneous Particle Systems Using Ls1 Mardyn

In: High Performance Computing in Science and Engineering '19

Author

Listed:
  • Steffen Seckler

    (Technical University of Munich, Department of Informatics)

  • Fabio Gratl

    (Technical University of Munich, Department of Informatics)

  • Nikola Tchipev

    (Technical University of Munich, Department of Informatics)

  • Matthias Heinen

    (Technical University of Berlin, Thermodynamics and Process Engineering)

  • Jadran Vrabec

    (Technical University of Berlin, Thermodynamics and Process Engineering)

  • Hans-Joachim Bungartz

    (Technical University of Munich, Department of Informatics)

  • Philipp Neumann

    (Helmut-Schmidt-Universität Hamburg, Chair for High Performance Computing)

Abstract

ls1 mardyn is a molecular dynamics (MD) simulation framework that enables investigations of multicomponent and multiphase processes relevant to engineering applications, such as droplet coalescence or bubble formation. These scenarios require the simulation of ensembles containing a large number of molecules. We present recent advances in ls1 mardyn both from the software design and high-performance computing perspective. From the former we describe the recently introduced plugin framework, from the latter we will look at some recent load balancing improvements to ls1 mardyn. We further present preliminary results of the integration of AutoPas, a C++ node-level library employing auto-tuning to achieve optimal node-level performance for particle simulations, into ls1 mardyn.

Suggested Citation

  • Steffen Seckler & Fabio Gratl & Nikola Tchipev & Matthias Heinen & Jadran Vrabec & Hans-Joachim Bungartz & Philipp Neumann, 2021. "Load Balancing and Auto-Tuning for Heterogeneous Particle Systems Using Ls1 Mardyn," Springer Books, in: Wolfgang E. Nagel & Dietmar H. Kröner & Michael M. Resch (ed.), High Performance Computing in Science and Engineering '19, pages 523-536, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-66792-4_35
    DOI: 10.1007/978-3-030-66792-4_35
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