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A Performance and Energy Evaluation of OpenCL-Accelerated Molecular Docking

Solis-Vasquez, Leonardo ; Koch, Andreas (2017)
A Performance and Energy Evaluation of OpenCL-Accelerated Molecular Docking.
5th International Workshop on OpenCL (IWOCL 2017). Toronto, Canada (16.-18.05.)
doi: 10.1145/3078155.3078167
Conference or Workshop Item, Bibliographie

Abstract

Molecular Docking is a methodology used extensively in modern drug design. It aims to predict the binding position of two molecules by calculating the energy of their possible binding poses. One of the most cited docking tools is AutoDock. At its core, it solves an optimization problem by generating a large solution space of possible poses, and searches among them for the one having the lowest energy. These complex algorithms thus benefit from parallelization based run-time acceleration. This work presents an OpenCL implementation of AutoDock, and a corresponding performance evaluation on two different platforms based on multi-core CPU and GPU accelerators. It shows that OpenCL allows highly efficient docking simulations, achieving speedups of ~4x and ~56x over the original serial AutoDock version, as well as energy efficiency gains of ~2x and ~6x. respectively. To the best of our knowledge, this work is the first one also considering the energy efficiency of molecular docking programs.

Item Type: Conference or Workshop Item
Erschienen: 2017
Creators: Solis-Vasquez, Leonardo ; Koch, Andreas
Type of entry: Bibliographie
Title: A Performance and Energy Evaluation of OpenCL-Accelerated Molecular Docking
Language: English
Date: 2017
Publisher: Association for Computing Machinery
Event Title: 5th International Workshop on OpenCL (IWOCL 2017)
Event Location: Toronto, Canada
Event Dates: 16.-18.05.
DOI: 10.1145/3078155.3078167
Abstract:

Molecular Docking is a methodology used extensively in modern drug design. It aims to predict the binding position of two molecules by calculating the energy of their possible binding poses. One of the most cited docking tools is AutoDock. At its core, it solves an optimization problem by generating a large solution space of possible poses, and searches among them for the one having the lowest energy. These complex algorithms thus benefit from parallelization based run-time acceleration. This work presents an OpenCL implementation of AutoDock, and a corresponding performance evaluation on two different platforms based on multi-core CPU and GPU accelerators. It shows that OpenCL allows highly efficient docking simulations, achieving speedups of ~4x and ~56x over the original serial AutoDock version, as well as energy efficiency gains of ~2x and ~6x. respectively. To the best of our knowledge, this work is the first one also considering the energy efficiency of molecular docking programs.

Uncontrolled Keywords: AutoDock, energy efficiency, Molecular docking, parallelization, GPU, OpenCL
Additional Information:

Art. No.: 3

Divisions: 20 Department of Computer Science
20 Department of Computer Science > Embedded Systems and Applications
Date Deposited: 23 Nov 2020 10:31
Last Modified: 23 Nov 2020 10:31
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