Shaw David E
D. E. Shaw Research and Development, LLC and Center for Computational Biology and Bioinformatics, Columbia University, 120 W. New York, New York 10036, USA.
J Comput Chem. 2005 Oct;26(13):1318-28. doi: 10.1002/jcc.20267.
Classical molecular dynamics simulations of biological macromolecules in explicitly modeled solvent typically require the evaluation of interactions between all pairs of atoms separated by no more than some distance R, with more distant interactions handled using some less expensive method. Performing such simulations for periods on the order of a millisecond is likely to require the use of massive parallelism. The extent to which such simulations can be efficiently parallelized, however, has historically been limited by the time required for interprocessor communication. This article introduces a new method for the parallel evaluation of distance-limited pairwise particle interactions that significantly reduces the amount of data transferred between processors by comparison with traditional methods. Specifically, the amount of data transferred into and out of a given processor scales as O(R(3/2)p(-1/2)), where p is the number of processors, and with constant factors that should yield a substantial performance advantage in practice.
在显式建模溶剂中对生物大分子进行经典分子动力学模拟通常需要评估所有间距不超过某个距离R的原子对之间的相互作用,更远距离的相互作用则使用某种成本较低的方法处理。要进行时长约为一毫秒的此类模拟可能需要使用大规模并行计算。然而,这类模拟能够有效并行化的程度在历史上一直受到处理器间通信所需时间的限制。本文介绍了一种用于并行评估距离受限的成对粒子相互作用的新方法,与传统方法相比,该方法显著减少了处理器之间传输的数据量。具体而言,进出给定处理器传输的数据量按O(R(3/2)p(-1/2))缩放,其中p是处理器的数量,并且常数因子在实际应用中应能带来显著的性能优势。