Massively parallel chemical potential calculation on graphics processing units
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- 作者：Kevin B. Daly ; Jay B. Benziger ; Pablo G. Debenedetti ; Athanassios Z. Panagiotopoulos
- 关键词：Monte Carlo methods ; Phase equilibria ; Graphics processing units ; Free energy
- 刊名：Computer Physics Communications
- 出版年：2012
- 出版时间：October, 2012
- 年：2012
- 卷：183
- 期：10
- 页码：2054-2062
- 全文大小：470 K
文摘
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 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.