dc.contributor.authorOuyang, Xuchang
dc.contributor.authorKwoh, Chee Keong
dc.date.accessioned2013-07-29T03:34:46Z
dc.date.available2013-07-29T03:34:46Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.citationOuyang, X., & Kwoh, C. K. (2012). GPU Accelerated Molecular Docking with Parallel Genetic Algorithm. 2012 IEEE 18th International Conference on Parallel and Distributed Systems.en_US
dc.identifier.urihttp://hdl.handle.net/10220/12426
dc.description.abstractMolecular 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 http://code.google.com/p/cudock/.en_US
dc.language.isoenen_US
dc.rights© 2012 IEEE.en_US
dc.subjectDRNTU::Engineering::Computer science and engineering
dc.titleGPU accelerated molecular docking with parallel genetic algorithmen_US
dc.typeConference Paper
dc.contributor.conferenceIEEE International Conference on Parallel and Distributed Systems (18th : 2012 : Singapore)en_US
dc.contributor.researchBioinformatics Research Centreen_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1109/ICPADS.2012.99


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