Advancing simulations of biological materials: applications of coarse-grained models on graphics processing unit hardware |
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Authors: | David N. LeBard |
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Affiliation: | 1. Department of Chemistry, Yeshiva University, 2495 Amsterdam Ave, New York, NY 10033, USAlebard@yu.edu |
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Abstract: | The timescales of biological processes, primarily those inherent to the molecular mechanisms of disease, are long (>μs) and involve complex interactions of systems consisting of many atoms (>106). Simulating these systems requires an advanced computational approach, and as such, coarse-grained (CG) models have been developed and highly optimised for accelerator hardware, primarily graphics processing units (GPUs). In this review, I discuss the implementation of CG models for biologically relevant systems, and show how such models can be optimised and perform well on GPU-accelerated hardware. Several examples of GPU implementations of CG models for both molecular dynamics and Monte Carlo simulations on purely GPU and hybrid CPU/GPU architectures are presented. Both the hardware and algorithmic limitations of various models, which depend greatly on the application of interest, are discussed. |
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Keywords: | coarse-grained models GPGPU molecular dynamics simulations Monte Carlo simulations biomolecular self-assembly |
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