GPU-Accelerated Exploration of Biomolecular Energy LandscapesReport as inadecuate


GPU-Accelerated Exploration of Biomolecular Energy Landscapes


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Publication Date: 2016-12-13

Journal Title: Journal of Chemical Theory and Computation

Publisher: American Chemical Society

Volume: 12

Issue: 12

Pages: 6182-6191

Language: English

Type: Article

This Version: VoR

Metadata: Show full item record

Citation: Mantell, R., Pitt, C., & Wales, D. (2016). GPU-Accelerated Exploration of Biomolecular Energy Landscapes. Journal of Chemical Theory and Computation, 12 (12), 6182-6191. https://doi.org/10.1021/acs.jctc.6b00934

Abstract: We present graphics processing unit (GPU)-acceleration of various computational energy landscape methods for biomolecular systems. Basin-hopping global optimization, the doubly nudged elastic band method (DNEB), hybrid eigenvector-following (EF), and a local rigid body framework are described, including details of GPU implementations. We analyze the results for eight different system sizes, and consider the effects of history size for minimization and local rigidification on the overall efficiency. We demonstrate improvement relative to CPU performance of up to 2 orders of magnitude for the largest systems.

Relationships: Is supplemented by: https://doi.org/10.5281/zenodo.163633

Sponsorship: EPSRC (Grant ID: EP/L504920/1)

Embargo Lift Date: 2100-01-01

Identifiers:

External DOI: https://doi.org/10.1021/acs.jctc.6b00934

This record's URL: https://www.repository.cam.ac.uk/handle/1810/262322



Rights: Attribution 4.0 International

Licence URL: http://creativecommons.org/licenses/by/4.0/





Author: Mantell, RGPitt, CE Wales, DJ

Source: https://www.repository.cam.ac.uk/handle/1810/262322



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