Abstract
Molecular dynamics (MD) is one of the most widely used techniques in computational materials science. By providing fully resolved trajectories, it allows for a natural description of static, thermodynamic, and kinetic properties. A major hurdle that has hampered the use of MD is the fact that the timescales that can be directly simulated are very limited, even when using massively parallel computers. In this study, we compare two time-parallelization approaches, parallel replica dynamics (ParRep) and parallel trajectory splicing (ParSplice), that were specifically designed to address this issue for rare event systems by leveraging parallel computing resources. Using simulations of the relaxation of small disordered platinum nanoparticles, a comparative performance analysis of the two methods is presented. The results show that ParSplice can significantly outperform ParRep in the common case where the trajectory remains trapped for a long time within a region of configuration space but makes rapid structural transitions within this region.
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ACKNOWLEDGMENTS
This work was supported by the United States Department of Energy (DOE), Office of Basic Energy Sciences, Materials Sciences and Engineering Division (D.P., A.F.V.) and by the China Scholarship Council (R.H.). The development and implementation of the ParSplice code were initially supported by LANL/LDRD Project No. 20150557ER and now by the DOE’s Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. 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. We gratefully acknowledge computing resources from the Los Alamos Institutional Computing program. Los Alamos National Laboratory is operated by Los Alamos National Security, LLC, for the National Nuclear Security administration of the US DOE under Contract No. DE-AC52-06NA25396.
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Perez, D., Huang, R. & Voter, A.F. Long-time molecular dynamics simulations on massively parallel platforms: A comparison of parallel replica dynamics and parallel trajectory splicing. Journal of Materials Research 33, 813–822 (2018). https://doi.org/10.1557/jmr.2017.456
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DOI: https://doi.org/10.1557/jmr.2017.456