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Accelerated Molecular Dynamics Methods in a Massively Parallel World

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Abstract

As high-performance computing systems now rely on hardware parallelism for continuous improvements in performance, the timescales accessible to direct molecular dynamics (MD) remain limited by the relatively stagnant performance of a single processor. While spatial decomposition allows extremely large systems to be simulated for short periods of time, alternative methods are needed to extend these simulations to significantly longer timescales. Although parallel means to produce long-timescale trajectories have been known since the late nineteen-nineties, several newer methodologies falling under the umbrella of accelerated molecular dynamics (AMD) have recently been developed with parallelism in mind. In this chapter, we review the current state-of-the-art in replica-based AMD and review several additional means of parallel scaling. Following a brief introduction to the serial AMD procedures, the chapter is organized into three general categories of parallel extensions: replication, speculation, and localization.

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Acknowledgements

This work was supported in part by the Department of Energy (DOE), Office of Basic Energy Sciences, Materials Sciences and Engineering Division. This work was also supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two US Department of Energy organizations (Office of Science and the National Nuclear Security Administration), responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering, and early testbed platforms, in support of the nation’s exascale computing imperative. Los Alamos National Laboratory is operated by Los Alamos National Security, LLC, for the National Nuclear Security Administration of the DOE, under contract DE-AC52-O6NA25396.

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Authors and Affiliations

  1. Leadership Computing Facility, Argonne National Laboratory, Lemont, IL, USA

    R. J. Zamora

  2. Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA

    D. Perez & A. F. Voter

  3. Materials Science and Technology Division, Los Alamos National Laboratory, Los Alamos, NM, USA

    E. Martinez & B. P. Uberuaga

Authors
  1. R. J. Zamora
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  2. D. Perez
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  3. E. Martinez
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  4. B. P. Uberuaga
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  5. A. F. Voter
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Corresponding author

Correspondence to R. J. Zamora .

Editor information

Editors and Affiliations

  1. Institute of Physics, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Wanda Andreoni

  2. Department of Nuclear Science & Engineering , Massachusetts Institute of Technology , Cambridge, MA, USA

    Sidney Yip

Section Editor information

  1. Theoretical Division T-1, Los Alamos National Laboratory, Los Alamos, NM, USA

    Danny Perez

  2. Materials Science and Technology Division, Los Alamos National Laboratory, Los Alamos, NM, USA

    B. P. Uberuaga

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Zamora, R., Perez, D., Martinez, E., Uberuaga, B., Voter, A. (2020). Accelerated Molecular Dynamics Methods in a Massively Parallel World. In: Andreoni, W., Yip, S. (eds) Handbook of Materials Modeling . Springer, Cham. https://doi.org/10.1007/978-3-319-42913-7_25-2

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  • DOI: https://doi.org/10.1007/978-3-319-42913-7_25-2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42913-7

  • Online ISBN: 978-3-319-42913-7

  • eBook Packages: Springer Reference Physics and AstronomyReference Module Physical and Materials ScienceReference Module Chemistry, Materials and Physics

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Chapter history

  1. Latest

    Accelerated Molecular Dynamics Methods in a Massively Parallel World
    Published:
    10 October 2019

    DOI: https://doi.org/10.1007/978-3-319-42913-7_25-2

  2. Original

    Accelerated Molecular Dynamics Methods in a Massively Parallel World
    Published:
    05 July 2018

    DOI: https://doi.org/10.1007/978-3-319-42913-7_25-1

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