Paper Info
Title
A new scalable parallel method for molecular dynamics based on cell-block data structure
Abstract
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 partitioning(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 1.1 × 109 particles on 500 processors took 80 seconds per time step.
Year
DOI
Venue
2004
10.1007/978-3-540-30566-8_88
ISPA
Keywords
Field
DocType
balanced load,one-dimensional load,total load,new scalable parallel method,cell-block data structure,high pressure physic,large-scale multi-medium md simulation,non-uniform particles distribution,maw redistributes block,molecular dynamic,load distribution,scalable parallel algorithm,high temperature,high pressure,parallel algorithm,three dimensional,domain decomposition,hilbert space,load balance,data structure
Data structure,Load balancing (computing),Parallel algorithm,Computer science,Block (data storage),Algorithm,Real-time computing,Computational science,Space-filling curve,Domain decomposition methods,Scalability,Speedup
Conference
Volume
ISSN
ISBN
3358
0302-9743
3-540-24128-0
Citations 
PageRank 
References 
1
0.35
3
Authors
2
Name
Order
Citations
PageRank
XiaoLin Cao130.80
Zeyao Mo27319.48