Journal
COMPUTER PHYSICS COMMUNICATIONS
Volume 183, Issue 10, Pages 2054-2062Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.cpc.2012.05.006
Keywords
Monte Carlo methods; Phase equilibria; Graphics processing units; Free energy
Funding
- National Science Foundation [CHE-0908265]
- Department of Energy, Office of Basic Energy Sciences [DE-SC0002128]
- Direct For Mathematical & Physical Scien
- Division Of Chemistry [0908265] Funding Source: National Science Foundation
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One- and two-stage free energy methods are common approaches for calculating the chemical potential from a molecular dynamics or Monte Carlo molecular simulation trajectory. Although these methods require significant amounts of CPU time spent on post-simulation analysis, this analysis step is well-suited for parallel execution. In this work, we implement this analysis step on graphics processing units (GPUs), an architecture that is optimized for massively parallel computation. A key issue in porting these free energy methods to GPUs is the trade-off between software efficiency and sampling efficiency. In particular, fixed performance costs in the software favor a higher number of insertion moves per configuration. However, higher numbers of moves lead to lower sampling efficiency. We explore this issue in detail, and find that for a dense, strongly interacting system of small molecules like liquid water, the optimal number of insertions per configuration can be as high as 10(5) for a two-stage approach like Bennett's method. We also find that our GPU implementation accelerates chemical potential calculations by as much as 60-fold when compared to an efficient, widely available CPU code running on a single CPU core. (C) 2012 Elsevier B.V. All rights reserved.
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