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

Laxmikant V. Kalé, Sameer Kumar, Gengbin Zheng, Chee Wai Lee

Research output: Chapter in Book/Report/Conference proceedingChapter

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.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsPeter M. A. Sloot, David Abramson, Alexander V. Bogdanov, Yuriy E. Gorbachev, Jack J. Dongarra, Albert Y. Zomaya
PublisherSpringer
Pages23-32
Number of pages10
ISBN (Print)3540401970, 9783540401971
DOIs
StatePublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2660
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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