Benchmarking the Performance of Irregular Computations in AutoDock-GPU Molecular Docking.

AutoDock CUDA OpenCL Variable execution performance early termination molecular docking

Journal

Parallel computing
ISSN: 0167-8191
Titre abrégé: Parallel Comput
Pays: Netherlands
ID NLM: 101469721

Informations de publication

Date de publication:
Mar 2022
Historique:
entrez: 13 12 2021
pubmed: 14 12 2021
medline: 14 12 2021
Statut: ppublish

Résumé

Irregular applications can be found in different scientific fields. In computer-aided drug design, molecular docking simulations play an important role in finding promising drug candidates. AutoDock is a software application widely used for predicting molecular interactions at close distances. It is characterized by irregular computations and long execution runtimes. In recent years, a hardware-accelerated version of AutoDock, called AutoDock-GPU, has been under active development. This work benchmarks the recent code and algorithmic enhancements incorporated into AutoDock-GPU. Particularly, we analyze the impact on execution runtime of techniques based on early termination. These enable AutoDock-GPU to explore the molecular space as necessary, while safely avoiding redundant computations. Our results indicate that it is possible to achieve average runtime reductions of 50% by using these techniques. Furthermore, a comprehensive literature review is also provided, where our work is compared to relevant approaches leveraging hardware acceleration for molecular docking.

Identifiants

pubmed: 34898769
doi: 10.1016/j.parco.2021.102861
pmc: PMC8654209
mid: NIHMS1757952
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : NIGMS NIH HHS
ID : R01 GM069832
Pays : United States

Déclaration de conflit d'intérêts

Declaration of interests X The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Leonardo Solis-Vasquez (L)

Embedded Systems and Applications Group. Technical University of Darmstadt, Darmstadt, Germany.
Hochschulstr. 10, D-64289, Darmstadt, Germany.

Andreas F Tillack (AF)

Department of Integrative Structural and Computational Biology. The Scripps Research Institute, La Jolla, CA, United States.

Diogo Santos-Martins (D)

Department of Integrative Structural and Computational Biology. The Scripps Research Institute, La Jolla, CA, United States.

Andreas Koch (A)

Embedded Systems and Applications Group. Technical University of Darmstadt, Darmstadt, Germany.

Scott LeGrand (S)

NVIDIA Corporation. Santa Clara, CA, United States.

Stefano Forli (S)

Department of Integrative Structural and Computational Biology. The Scripps Research Institute, La Jolla, CA, United States.

Classifications MeSH