Runtime Steering of Molecular Dynamics Simulations Through In Situ Analysis and Annotation of Collective Variables

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This paper targets one of the most common simulations on petascale and, very likely, on exascale machines: molecular dynamics (MD) simulations studying the (classical) time evolution of a molecular system at atomic resolution. Specifically, this work addresses the data challenges of MD simulations at exascale through (1) the creation of a data analysis method based on a suite of advanced collective variables (CVs) selected for annotation of structural molecular properties and capturing rare conformational events at runtime, (2) the definition of an in situ framework to automatically identify the frames where the rare events occur during an MD simulation and (3) the integration of both method and framework into two MD workflows for the study of early termination or termination and restart of a benchmark molecular system for protein folding —the Fs peptide system (Ace-A_5(AAARA)_3A-NME)— using Summit. The approach achieves faster exploration of the conformational space compared to extensive ensemble simulations. Specifically, our in situ framework with early termination alone achieves 99.6% coverage of the reference conformational space for the Fs peptide with just 60% of the MD steps otherwise used for a traditional execution of the MD simulation. Annotation-based restart allows us to cover 94.6% of the conformational space, just running 50% of the overall MD steps.

Recommended citation: Caino-Lores, S., Cuendet, M., Marquez, J., Kots, E., Estrada, T., Deelman, E., … & Taufer, M. (2023, June). Runtime Steering of Molecular Dynamics Simulations Through In Situ Analysis and Annotation of Collective Variables. In Proceedings of the Platform for Advanced Scientific Computing Conference (pp. 1-11).