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Advancing simulations of biological materials: applications of coarse-grained models on graphics processing unit hardware
Authors:David N. LeBard
Affiliation:1. Department of Chemistry, Yeshiva University, 2495 Amsterdam Ave, New York, NY 10033, USAlebard@yu.edu
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.
Keywords:coarse-grained models  GPGPU  molecular dynamics simulations  Monte Carlo simulations  biomolecular self-assembly
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