Accelerating Molecular Dynamic Simulation on Graphics Processing Units

By M. Friedrichs, P. Eastman, V. Vishal, M. Houston, S. LeGrand, A. L. Beberg, D. Ensign, C. M. Bruns, Vijay S. Pande. Journal of Computational Chemistry, 2009

542 citations recorded by the source corpus.

We describe a complete implementation of all‐atom protein molecular dynamics running entirely on a graphics processing unit (GPU), including all standard force field terms, integration, constraints, and implicit solvent. We discuss the design of our algorithms and important optimizations needed to fully take advantage of a GPU. We evaluate its performance, and show that it can be more than 700 times faster than a conventional implementation running on a single CPU core. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009

Subfields: Artificial Intelligence, Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/d3c41281a5adb9626c1e05f5fc59ef2f8242438e

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Citations in the corpus

SPFP: Speed without compromise - A mixed precision model for GPU accelerated molecular dynamics simulations (2013, background): “…of scientific applications has long been realized [2] [3] and mature implementations are available for molecular dynamics (MD) simulations of condensed phase biomolecular systems providing capabilities to researchers that can surpass traditional CPU-based implementations [4] [5] [6] [7] [8] [9].”
Improving structure-based function prediction using molecular dynamics (2009, methodology): “With improvements in molecular dynamics algorithms and implementations on special purpose hardware, it may become possible to run the dynamics for longer time period and to apply the algorithm described here on a large scale to many proteins in the PDB (Friedrichs et al., 2009).”
In silico methods and tools for drug discovery (2021, methodology): “To resolve this limitation, recently, graphics processing units with a large number of cores have been used to increase the speed of MD simulations [196 – 198].”
On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods (2009, background): “Examples include Stone et al. (2007) and Friedrichs et al. (2009), which discuss their use in molecular modelling and dynamics.”
Bridging Molecular Docking to Molecular Dynamics in Exploring Ligand-Protein Recognition Process: An Overview (2018, background): “…development of code able to exploit the speed of GPUs (Graphics Processing Units), which has given access to tera-scale performances with the use of a common workstation, and a consequent relatively low cost (Van Meel et al., 2008; Friedrichs et al., 2009; Harvey et al., 2009; Nobile et al., 2017).”
Molecular dynamics simulations and drug discovery (2011, background): “Conse quently, the same graphics-processing-units (GPUs) designed to speed up video games can be used to speed up molecular dynamics simulations as well, usually by an order of magnitude [34-36].”
Computational solutions to large-scale data management and analysis (2010, background): “Although GPUs constitute only 5% of the processors that are actively engaged in this project, they contribute 60% of the total FLOP”