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Cited by 919

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ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

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Harvey, M. J., Giupponi, G., Fabritiis, G. De·2009·Journal of Chemical Theory and Computation
DOI 10.1021/ct9000685
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Abstract

The high arithmetic performance and intrinsic parallelism of recent graphical processing units (GPUs) can offer a technological edge for molecular dynamics simulations. ACEMD is a production-class biomolecular dynamics (MD) engine supporting CHARMM and AMBER force fields. Designed specifically for GPUs it is able to achieve supercomputing scale performance of 40 ns/day for all-atom protein systems with over 23 000 atoms. We provide a validation and performance evaluation of the code and run a microsecond-long trajectory for an all-atom molecular system in explicit TIP3P water on a single workstation computer equipped with just 3 GPUs. We believe that microsecond time scale molecular dynamics on cost-effective hardware will have important methodological and scientific implications.

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Metadata

Authors
Harvey, M. J., Giupponi, G., & Fabritiis, G. D.
Venue
Journal of Chemical Theory and Computation
Publisher
American Chemical Society (ACS)
Published
2009-05-21
Volume
5
Issue
6
Pages
1632-1639
ISSN
  • 1549-9618 (ISSN-L)
  • 1549-9626
DOI
10.1021/ct9000685
OpenAlex
W2082586732
Cited by
919
References
3
FWCI
47.51
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale. https://app.cochat.ai/papers/10.1021/ct9000685
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Harvey, M. J., Giupponi, G., & Fabritiis, G. D. (2009). ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale. Journal of Chemical Theory and Computation. https://doi.org/10.1021/ct9000685

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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.