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
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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