PySAGES, Enhanced Sampling Molecular Dynamics Simulations on GPUs
ORAL
Abstract
When performing molecular dynamics simulations, there exists a large gap between the time scales that can be probed computationally to the ones observed in experiments. To tackle this issue two strategies are commonly used: 1) algorithms that explore the simulated configurational space more efficiently; or 2) hardware accelerators such as GPUs. We combine both in PySAGES (Python Suite for Advanced General Ensemble Simulations), which can be hooked to different molecular dynamics (MD) simulation packages, allowing the user to perform enhanced sampling simulations through a uniform interface without sacrificing the efficiency of the underlying MD implementation (at the time of writing we provide support for HOOMD-blue and OpenMM). The library, is a Python implementation of SSAGES with support for GPUs. Having a Python frontend provides the user flexibility and the ability to easily extend it. We will discuss its features, advantages, technical aspects of the implementation, and present some examples and benchmarks.
*This work was supported by MICCoM, as part of the Computational Materials Sciences Program funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences, and Engineering Division through Argonne National Laboratory.
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Publication: Pablo Zubieta, Ludwig Schneider, John Parker, Gustavo Perez-Lemus, and Juan J. de Pablo. "PySAGES, Enhanced Sampling Molecular Dynamics Simulations on GPUs." (Planned paper)
Presenters
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Pablo Zubieta
- Pritzker School of Molecular Engineering, University of Chicago