Literature DB >> 24659253

Midpoint cell method for hybrid (MPI+OpenMP) parallelization of molecular dynamics simulations.

Jaewoon Jung1, Takaharu Mori, Yuji Sugita.   

Abstract

We have developed a new hybrid (MPI+OpenMP) parallelization scheme for molecular dynamics (MD) simulations by combining a cell-wise version of the midpoint method with pair-wise Verlet lists. In this scheme, which we call the midpoint cell method, simulation space is divided into subdomains, each of which is assigned to a MPI processor. Each subdomain is further divided into small cells. The interaction between two particles existing in different cells is computed in the subdomain containing the midpoint cell of the two cells where the particles reside. In each MPI processor, cell pairs are distributed over OpenMP threads for shared memory parallelization. The midpoint cell method keeps the advantages of the original midpoint method, while filtering out unnecessary calculations of midpoint checking for all the particle pairs by single midpoint cell determination prior to MD simulations. Distributing cell pairs over OpenMP threads allows for more efficient shared memory parallelization compared with distributing atom indices over threads. Furthermore, cell grouping of particle data makes better memory access, reducing the number of cache misses. The parallel performance of the midpoint cell method on the K computer showed scalability up to 512 and 32,768 cores for systems of 20,000 and 1 million atoms, respectively. One MD time step for long-range interactions could be calculated within 4.5 ms even for a 1 million atoms system with particle-mesh Ewald electrostatics.
Copyright © 2014 Wiley Periodicals, Inc.

Keywords:  domain decomposition; hybrid parallelization; midpoint cell method; molecular dynamics

Mesh:

Year:  2014        PMID: 24659253     DOI: 10.1002/jcc.23591

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  5 in total

1.  Scaling molecular dynamics beyond 100,000 processor cores for large-scale biophysical simulations.

Authors:  Jaewoon Jung; Wataru Nishima; Marcus Daniels; Gavin Bascom; Chigusa Kobayashi; Adetokunbo Adedoyin; Michael Wall; Anna Lappala; Dominic Phillips; William Fischer; Chang-Shung Tung; Tamar Schlick; Yuji Sugita; Karissa Y Sanbonmatsu
Journal:  J Comput Chem       Date:  2019-04-17       Impact factor: 3.376

2.  New parallel computing algorithm of molecular dynamics for extremely huge scale biological systems.

Authors:  Jaewoon Jung; Chigusa Kobayashi; Kento Kasahara; Cheng Tan; Akiyoshi Kuroda; Kazuo Minami; Shigeru Ishiduki; Tatsuo Nishiki; Hikaru Inoue; Yutaka Ishikawa; Michael Feig; Yuji Sugita
Journal:  J Comput Chem       Date:  2020-11-16       Impact factor: 3.376

3.  GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations.

Authors:  Jaewoon Jung; Takaharu Mori; Chigusa Kobayashi; Yasuhiro Matsunaga; Takao Yoda; Michael Feig; Yuji Sugita
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2015-05-07

4.  myPresto/omegagene: a GPU-accelerated molecular dynamics simulator tailored for enhanced conformational sampling methods with a non-Ewald electrostatic scheme.

Authors:  Kota Kasahara; Benson Ma; Kota Goto; Bhaskar Dasgupta; Junichi Higo; Ikuo Fukuda; Tadaaki Mashimo; Yutaka Akiyama; Haruki Nakamura
Journal:  Biophys Physicobiol       Date:  2016-09-07

5.  Implementation of residue-level coarse-grained models in GENESIS for large-scale molecular dynamics simulations.

Authors:  Cheng Tan; Jaewoon Jung; Chigusa Kobayashi; Diego Ugarte La Torre; Shoji Takada; Yuji Sugita
Journal:  PLoS Comput Biol       Date:  2022-04-05       Impact factor: 4.779

  5 in total

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