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Title: Long-time dynamics through parallel trajectory splicing

Abstract

Simulating the atomistic evolution of materials over long time scales is a longstanding challenge, especially for complex systems where the distribution of barrier heights is very heterogeneous. Such systems are difficult to investigate using conventional long-time scale techniques, and the fact that they tend to remain trapped in small regions of configuration space for extended periods of time strongly limits the physical insights gained from short simulations. We introduce a novel simulation technique, Parallel Trajectory Splicing (ParSplice), that aims at addressing this problem through the timewise parallelization of long trajectories. The computational efficiency of ParSplice stems from a speculation strategy whereby predictions of the future evolution of the system are leveraged to increase the amount of work that can be concurrently performed at any one time, hence improving the scalability of the method. ParSplice is also able to accurately account for, and potentially reuse, a substantial fraction of the computational work invested in the simulation. We validate the method on a simple Ag surface system and demonstrate substantial increases in efficiency compared to previous methods. As a result, we then demonstrate the power of ParSplice through the study of topology changes in Ag42Cu13 core–shell nanoparticles.

Authors:
 [1];  [2];  [2];  [2];  [1]
+ Show Author Affiliations
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Harvard Univ., Cambridge, MA (United States)
Publication Date:
Research Org.:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1239568
Report Number(s):
LA-UR-15-27573
Journal ID: ISSN 1549-9618
Grant/Contract Number:  
CCF-1438983; 2012116808; AC52-06NA25396
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Chemical Theory and Computation
Additional Journal Information:
Journal Volume: 12; Journal Issue: 1; Journal ID: ISSN 1549-9618
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE

Citation Formats

Perez, Danny, Cubuk, Ekin D., Waterland, Amos, Kaxiras, Efthimios, and Voter, Arthur F. Long-time dynamics through parallel trajectory splicing. United States: N. p., 2015. Web. doi:10.1021/acs.jctc.5b00916.
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Perez, Danny, Cubuk, Ekin D., Waterland, Amos, Kaxiras, Efthimios, & Voter, Arthur F. Long-time dynamics through parallel trajectory splicing. United States. https://doi.org/10.1021/acs.jctc.5b00916
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Perez, Danny, Cubuk, Ekin D., Waterland, Amos, Kaxiras, Efthimios, and Voter, Arthur F. Tue . "Long-time dynamics through parallel trajectory splicing". United States. https://doi.org/10.1021/acs.jctc.5b00916. https://www.osti.gov/servlets/purl/1239568.
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@article{osti_1239568,
title = {Long-time dynamics through parallel trajectory splicing},
author = {Perez, Danny and Cubuk, Ekin D. and Waterland, Amos and Kaxiras, Efthimios and Voter, Arthur F.},
abstractNote = {Simulating the atomistic evolution of materials over long time scales is a longstanding challenge, especially for complex systems where the distribution of barrier heights is very heterogeneous. Such systems are difficult to investigate using conventional long-time scale techniques, and the fact that they tend to remain trapped in small regions of configuration space for extended periods of time strongly limits the physical insights gained from short simulations. We introduce a novel simulation technique, Parallel Trajectory Splicing (ParSplice), that aims at addressing this problem through the timewise parallelization of long trajectories. The computational efficiency of ParSplice stems from a speculation strategy whereby predictions of the future evolution of the system are leveraged to increase the amount of work that can be concurrently performed at any one time, hence improving the scalability of the method. ParSplice is also able to accurately account for, and potentially reuse, a substantial fraction of the computational work invested in the simulation. We validate the method on a simple Ag surface system and demonstrate substantial increases in efficiency compared to previous methods. As a result, we then demonstrate the power of ParSplice through the study of topology changes in Ag42Cu13 core–shell nanoparticles.},
doi = {10.1021/acs.jctc.5b00916},
journal = {Journal of Chemical Theory and Computation},
number = 1,
volume = 12,
place = {United States},
year = {Tue Nov 24 00:00:00 EST 2015},
month = {Tue Nov 24 00:00:00 EST 2015}
}
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https://doi.org/10.1021/acs.jctc.5b00916
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