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Cited by 529

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Accelerating molecular dynamic simulation on graphics processing units

Open access
Friedrichs, Mark S., Eastman, Peter, Vaidyanathan, Vishal, Houston, Mike, Legrand, Scott, Beberg, Adam L., Ensign, Daniel L., Bruns, Christopher M., Pande, Vijay S.·2009·Journal of Computational Chemistry

Abstract

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

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Crossref · 10.1002/jcc.21209

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Metadata

Authors
Friedrichs, M. S., Eastman, P., Vaidyanathan, V., Houston, M., Legrand, S., Beberg, A. L., Ensign, D. L., Bruns, C. M., & Pande, V. S.
Venue
Journal of Computational Chemistry
Publisher
Wiley
Published
2009-02-03
Volume
30
Issue
6
Pages
864-872
ISSN
  • 0192-8651 (ISSN-L)
  • 1096-987X
OpenAlex
W1973858832
Cited by
529
References
2
FWCI
104.93
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Accelerating molecular dynamic simulation on graphics processing units. https://app.cochat.ai/papers/10.1002/jcc.21209
The paper
Friedrichs, M. S., Eastman, P., Vaidyanathan, V., Houston, M., Legrand, S., Beberg, A. L., Ensign, D. L., Bruns, C. M., & Pande, V. S. (2009). Accelerating molecular dynamic simulation on graphics processing units. Journal of Computational Chemistry. https://doi.org/10.1002/jcc.21209

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.