Long-time dynamics through parallel trajectory splicing

Perez, Danny; Cubuk, Ekin D.; Waterland, Amos; Kaxiras, Efthimios; Voter, Arthur F.

doi:10.1021/acs.jctc.5b00916

Title: Long-time dynamics through parallel trajectory splicing

Journal Article · Tue Nov 24 00:00:00 EST 2015 · Journal of Chemical Theory and Computation

DOI:https://doi.org/10.1021/acs.jctc.5b00916· OSTI ID:1239568

Perez, Danny ^[1]; Cubuk, Ekin D. ^[2]; Waterland, Amos ^[2]; Kaxiras, Efthimios ^[2]; Voter, Arthur F. ^[1]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Harvard Univ., Cambridge, MA (United States)

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.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: CCF-1438983; 2012116808; AC52-06NA25396

OSTI ID:: 1239568

Report Number(s):: LA-UR-15-27573

Journal Information:: Journal of Chemical Theory and Computation, Vol. 12, Issue 1; ISSN 1549-9618

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 54 works

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References (22)

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Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification Swinburne, Thomas D.; Perez, Danny Physical Review Materials, Vol. 2, Issue 5 https://doi.org/10.1103/physrevmaterials.2.053802	journal	May 2018
Path-accelerated stochastic molecular dynamics: Parallel-in-time integration using path integrals Rosa-Raíces, Jorge L.; Zhang, Bin; Miller, Thomas F. The Journal of Chemical Physics, Vol. 151, Issue 16 https://doi.org/10.1063/1.5125455	journal	October 2019
Reaction pathways in atomistic models of thin film growth Lloyd, Adam L.; Zhou, Ying; Yu, Miao The Journal of Chemical Physics, Vol. 147, Issue 15 https://doi.org/10.1063/1.4986402	journal	October 2017
Combining Machine Learning and Physics to Understand Glassy Systems Schoenholz, Samuel S. Journal of Physics: Conference Series, Vol. 1036 https://doi.org/10.1088/1742-6596/1036/1/012021	journal	June 2018
Cluster analysis of accelerated molecular dynamics simulations: A case study of the decahedron to icosahedron transition in Pt nanoparticles Huang, Rao; Lo, Li-Ta; Wen, Yuhua The Journal of Chemical Physics, Vol. 147, Issue 15 https://doi.org/10.1063/1.4996922	journal	October 2017
Long-time molecular dynamics simulations on massively parallel platforms: A comparison of parallel replica dynamics and parallel trajectory splicing Perez, Danny; Huang, Rao; Voter, Arthur F. Journal of Materials Research, Vol. 33, Issue 7 https://doi.org/10.1557/jmr.2017.456	journal	December 2017
Speculation and replication in temperature accelerated dynamics Zamora, Richard J.; Perez, Danny; Voter, Arthur F. Journal of Materials Research, Vol. 33, Issue 7 https://doi.org/10.1557/jmr.2018.17	journal	February 2018
The mobility of small vacancy/helium complexes in tungsten and its impact on retention in fusion-relevant conditions Perez, Danny; Sandoval, Luis; Blondel, Sophie Scientific Reports, Vol. 7, Issue 1 https://doi.org/10.1038/s41598-017-02428-2	journal	May 2017
Representations in neural network based empirical potentials Cubuk, Ekin D.; Malone, Brad D.; Onat, Berk The Journal of Chemical Physics, Vol. 147, Issue 2 https://doi.org/10.1063/1.4990503	journal	July 2017
Computing long time scale biomolecular dynamics using quasi-stationary distribution kinetic Monte Carlo (QSD-KMC) Agarwal, Animesh; Hengartner, Nicolas W.; Gnanakaran, S. The Journal of Chemical Physics, Vol. 151, Issue 7 https://doi.org/10.1063/1.5094457	journal	August 2019
Evidence for percolation diffusion of cations and reordering in disordered pyrochlore from accelerated molecular dynamics Perriot, Romain; Uberuaga, Blas P.; Zamora, Richard J. Nature Communications, Vol. 8, Issue 1 https://doi.org/10.1038/s41467-017-00708-z	journal	September 2017

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