Accelerators for Classical Molecular Dynamics Simulations of Biomolecules

Derek Jones(Lawrence Livermore National Laboratory), Jonathan Allen(Lawrence Livermore National Laboratory), Yue Yang(Lawrence Livermore National Laboratory), William F. Bennett(Lawrence Livermore National Laboratory), Maya Gokhale(Lawrence Livermore National Laboratory), Niema Moshiri(University of California San Diego), Tajana Rosing(University of California San Diego)
Journal of Chemical Theory and Computation
June 16, 2022
Cited by 72Open Access
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Abstract

Atomistic Molecular Dynamics (MD) simulations provide researchers the ability to model biomolecular structures such as proteins and their interactions with drug-like small molecules with greater spatiotemporal resolution than is otherwise possible using experimental methods. MD simulations are notoriously expensive computational endeavors that have traditionally required massive investment in specialized hardware to access biologically relevant spatiotemporal scales. Our goal is to summarize the fundamental algorithms that are employed in the literature to then highlight the challenges that have affected accelerator implementations in practice. We consider three broad categories of accelerators: Graphics Processing Units (GPUs), Field-Programmable Gate Arrays (FPGAs), and Application Specific Integrated Circuits (ASICs). These categories are comparatively studied to facilitate discussion of their relative trade-offs and to gain context for the current state of the art. We conclude by providing insights into the potential of emerging hardware platforms and algorithms for MD.


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