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Journal of Computational Chemistry
Article . 2020 . Peer-reviewed
License: CC BY
Data sources: Crossref
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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; +5 Authors

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

Abstract

AbstractIn this paper, we address high performance extreme‐scale molecular dynamics (MD) algorithm in the GENESIS software to perform cellular‐scale molecular dynamics (MD) simulations with more than 100,000 CPU cores. It includes (1) the new algorithm of real‐space nonbonded interactions maximizing the performance on ARM CPU architecture, (2) reciprocal‐space nonbonded interactions minimizing communicational cost, (3) accurate temperature/pressure evaluations that allows a large time step, and (4) effective parallel file inputs/outputs (I/O) for MD simulations of extremely huge systems. The largest system that contains 1.6 billion atoms was simulated using MD with a performance of 8.30 ns/day on Fugaku supercomputer. It extends the available size and time of MD simulations to answer unresolved questions of biomacromolecules in a living cell.

Keywords

Computational Biology, RNA, DNA, Molecular Dynamics Simulation, Algorithms

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
67
Top 1%
Top 10%
Top 1%
hybrid