Scaling molecular dynamics to 3000 processors with projections: a performance analysis case study

Authors:
Laxmikant V. Kalé;Sameer Kumar;Gengbin Zheng;Chee Wai Lee
Affiliations:
Department of Computer Science, University of Illinois at Urbana-Champaign;Department of Computer Science, University of Illinois at Urbana-Champaign;Department of Computer Science, University of Illinois at Urbana-Champaign;Department of Computer Science, University of Illinois at Urbana-Champaign
Venue:
ICCS'03 Proceedings of the 2003 international conference on Computational science
Year:
2003

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Abstract

Some of the most challenging applications to parallelize scalably are the ones that present a relatively small amount of computation per iteration. Multiple interacting performance challenges must be identified and solved to attain high parallel efficiency in such cases. We present a case study involving NAMD, a parallel molecular dynamics application, and efforts to scale it to run on 3000 processors with Tera-FLOPS level performance. NAMD is implemented in Charm++, and the performance analysis was carried out using "projections", the performance visualization/analysis tool associated with Charm++. We will showcase a series of optimizations facilitated by projections. The resultant performance of NAMD led to a Gordon Bell award at SC2002.