Journal
JOURNAL OF COMPUTATIONAL CHEMISTRY
Volume 39, Issue 25, Pages 2110-2117Publisher
WILEY
DOI: 10.1002/jcc.25382
Keywords
trajectory analysis; parallel data analysis; molecular dynamics; trajectory ensembles; big data
Categories
Funding
- Blue Waters PAID program
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Advances in biomolecular simulation methods and access to large scale computer resources have led to a massive increase in the amount of data generated. The key enablers have been optimization and parallelization of the simulation codes. However, much of the software used to analyze trajectory data from these simulations is still run in serial, or in some cases many threads via shared memory. Here, we describe the addition of multiple levels of parallel trajectory processing to the molecular dynamics simulation analysis software CPPTRAJ. In addition to the existing OpenMP shared-memory parallelism, CPPTRAJ now has two additional levels of message passing (MPI) parallelism involving both across-trajectory processing and across-ensemble processing. All three levels of parallelism can be simultaneously active, leading to significant speed ups in data analysis of large datasets on the NCSA Blue Waters supercomputer by better leveraging the many available nodes and its parallel file system. (C) 2018 Wiley Periodicals, Inc.
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