Please use this identifier to cite or link to this item:
Title: GPU accelerated molecular docking with parallel genetic algorithm
Authors: Ouyang, Xuchang
Kwoh, Chee Keong
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2012
Source: Ouyang, X., & Kwoh, C. K. (2012). GPU Accelerated Molecular Docking with Parallel Genetic Algorithm. 2012 IEEE 18th International Conference on Parallel and Distributed Systems.
Abstract: Molecular docking is a widely used tool in Computer-aided Drug Design and Discovery. Due to the complexity of simulating the chemical events when two molecules interact, highly accelerated molecular docking programs are of great interest and importance for practical use. In this paper, we present a GPU accelerated docking program implemented with CUDA. The hardware-enabled texture interpolation is employed for fast energy evaluation. Two types of parallel genetic algorithms are mapped to the CUDA computing architecture and used for the search of optimal docking result. Comparing to the CPU implementation, the GPU accelerated docking program achieved significant speedup while producing comparable results to the CPU version. The source code is made public at
DOI: 10.1109/ICPADS.2012.99
Rights: © 2012 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Conference Papers

Citations 20

Updated on Mar 6, 2021

Citations 20

Updated on Mar 3, 2021

Page view(s) 10

Updated on May 15, 2021

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.