Extensible and Scalable Adaptive Sampling on Supercomputers

Eugen Hruska, Vivekanandan Balasubramanian, Hyungro Lee, Shantenu Jha, Cecilia Clementi

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The accurate sampling of protein dynamics is an ongoing challenge despite the utilization of high-performance computer (HPC) systems. Utilizing only "brute force"molecular dynamics (MD) simulations requires an unacceptably long time to solution. Adaptive sampling methods allow a more effective sampling of protein dynamics than standard MD simulations. Depending on the restarting strategy, the speed up can be more than 1 order of magnitude. One challenge limiting the utilization of adaptive sampling by domain experts is the relatively high complexity of efficiently running adaptive sampling on HPC systems. We discuss how the ExTASY framework can set up new adaptive sampling strategies and reliably execute resulting workflows at scale on HPC platforms. Here, the folding dynamics of four proteins are predicted with no a priori information.

Original languageEnglish (US)
Pages (from-to)7915-7925
Number of pages11
JournalJournal of Chemical Theory and Computation
Volume16
Issue number12
DOIs
StatePublished - Dec 8 2020

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Physical and Theoretical Chemistry

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