A New Scalable Parallel Method for Molecular Dynamics Based on Cell-Block Data Structure

摘要

A scalable parallel algorithm especially for large-scale three dimensional simulations with seriously non-uniform particles distributions is presented. In particular, based on cell-block data structures, this algorithm uses Hilbert space filling curve to convert three-dimensional domain decomposition for load distribution across processors into one-dimensional load balancing problems for which measurement-based multilevel averaging weights(MAW) method can be applied successfully. Against inverse space-filling partition-ing(ISP), MAW redistributes blocks by monitoring change of total load in each processor. Numerical experimental results have shown that MAW is superior to ISP in rendering balanced load for large-scale multi-medium MD simulation in high temperature and high pressure physics. Excellent scalability was demonstrated, with a speedup larger than 200 with 240 processors of one MPP. The largest run with 1.1x10~9 particles on 500 processors took 80 seconds per time step.