Parallelized event chain algorithm for dense hard sphere and polymer systems
Abstract
We combine parallelization and cluster Monte Carlo for hard sphere systems and present a parallelized event chain algorithm for the hard disk system in two dimensions. For parallelization we use a spatial partitioning approach into simulation cells. We find that it is crucial for correctness to ensure detailed balance on the level of Monte Carlo sweeps by drawing the starting sphere of event chains within each simulation cell with replacement. We analyze the performance gains for the parallelized event chain and find a criterion for an optimal degree of parallelization. Because of the cluster nature of event chain moves massive parallelization will not be optimal. Finally, we discuss first applications of the event chain algorithm to dense polymer systems, i.e., bundleforming solutions of attractive semiflexible polymers.
 Authors:
 Publication Date:
 OSTI Identifier:
 22382172
 Resource Type:
 Journal Article
 Resource Relation:
 Journal Name: Journal of Computational Physics; Journal Volume: 281; Other Information: Copyright (c) 2014 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ALGORITHMS; COMPUTERIZED SIMULATION; DRAWING; FILAMENTS; GAIN; MAGNETIC DISKS; MATHEMATICAL SOLUTIONS; MONTE CARLO METHOD; PARTITION; PERFORMANCE; POLYMERS; SPHERES
Citation Formats
Kampmann, Tobias A., Email: tobias.kampmann@tudortmund.de, Boltz, HorstHolger, and Kierfeld, Jan, Email: jan.kierfeld@tudortmund.de. Parallelized event chain algorithm for dense hard sphere and polymer systems. United States: N. p., 2015.
Web. doi:10.1016/J.JCP.2014.10.059.
Kampmann, Tobias A., Email: tobias.kampmann@tudortmund.de, Boltz, HorstHolger, & Kierfeld, Jan, Email: jan.kierfeld@tudortmund.de. Parallelized event chain algorithm for dense hard sphere and polymer systems. United States. doi:10.1016/J.JCP.2014.10.059.
Kampmann, Tobias A., Email: tobias.kampmann@tudortmund.de, Boltz, HorstHolger, and Kierfeld, Jan, Email: jan.kierfeld@tudortmund.de. Thu .
"Parallelized event chain algorithm for dense hard sphere and polymer systems". United States.
doi:10.1016/J.JCP.2014.10.059.
@article{osti_22382172,
title = {Parallelized event chain algorithm for dense hard sphere and polymer systems},
author = {Kampmann, Tobias A., Email: tobias.kampmann@tudortmund.de and Boltz, HorstHolger and Kierfeld, Jan, Email: jan.kierfeld@tudortmund.de},
abstractNote = {We combine parallelization and cluster Monte Carlo for hard sphere systems and present a parallelized event chain algorithm for the hard disk system in two dimensions. For parallelization we use a spatial partitioning approach into simulation cells. We find that it is crucial for correctness to ensure detailed balance on the level of Monte Carlo sweeps by drawing the starting sphere of event chains within each simulation cell with replacement. We analyze the performance gains for the parallelized event chain and find a criterion for an optimal degree of parallelization. Because of the cluster nature of event chain moves massive parallelization will not be optimal. Finally, we discuss first applications of the event chain algorithm to dense polymer systems, i.e., bundleforming solutions of attractive semiflexible polymers.},
doi = {10.1016/J.JCP.2014.10.059},
journal = {Journal of Computational Physics},
number = ,
volume = 281,
place = {United States},
year = {Thu Jan 15 00:00:00 EST 2015},
month = {Thu Jan 15 00:00:00 EST 2015}
}

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