National Institute of Chemistry, Hajdrihova 19, Ljubljana SI-1000, Slovenia.
J Comput Chem. 2011 Nov 15;32(14):3005-13. doi: 10.1002/jcc.21882. Epub 2011 Jul 26.
Parallelization is an effective way to reduce the computational time needed for molecular dynamics simulations. We describe a new parallelization method, the distributed-diagonal force decomposition method, with which we extend and improve the existing force decomposition methods. Our new method requires less data communication during molecular dynamics simulations than replicated data and current force decomposition methods, increasing the parallel efficiency. It also dynamically load-balances the processors' computational load throughout the simulation. The method is readily implemented in existing molecular dynamics codes and it has been incorporated into the CHARMM program, allowing its immediate use in conjunction with the many molecular dynamics simulation techniques that are already present in the program. We also present the design of the Force Decomposition Machine, a cluster of personal computers and networks that is tailored to running molecular dynamics simulations using the distributed diagonal force decomposition method. The design is expandable and provides various degrees of fault resilience. This approach is easily adaptable to computers with Graphics Processing Units because it is independent of the processor type being used.
并行化是减少分子动力学模拟所需计算时间的有效方法。我们描述了一种新的并行化方法,即分布式对角力分解方法,通过该方法扩展和改进了现有的力分解方法。与复制数据和当前的力分解方法相比,我们的新方法在分子动力学模拟过程中需要更少的数据通信,从而提高了并行效率。它还可以在整个模拟过程中动态平衡处理器的计算负载。该方法易于在现有的分子动力学代码中实现,并已被整合到 CHARMM 程序中,使其能够与该程序中已经存在的许多分子动力学模拟技术立即配合使用。我们还介绍了 Force Decomposition Machine 的设计,这是一个由个人计算机和网络组成的集群,专门用于使用分布式对角力分解方法运行分子动力学模拟。该设计具有可扩展性,并提供了不同程度的容错能力。这种方法很容易适应具有图形处理单元的计算机,因为它不依赖于所使用的处理器类型。