DocumentCode
2454114
Title
GPU-based Cloud computing for comparing the structure of protein binding sites
Author
Leinweber, Matthias ; Baumgartner, L. ; Mernberger, M. ; Fober, Thomas ; Hullermeier, Eyke ; Klebe, Gerhard ; Freisleben, Bernd
Author_Institution
Dept. of Math. & Comput. Sci., Univ. of Marburg, Marburg, Germany
fYear
2012
fDate
18-20 June 2012
Firstpage
1
Lastpage
6
Abstract
In this paper, we present a novel approach for using a GPU-based Cloud computing infrastructure to efficiently perform a structural comparison of protein binding sites. The original CPU-based Java version of a recent graph-based algorithm called SEGA has been rewritten in OpenCL to run on NVIDIA GPUs in parallel on a set of Amazon EC2 Cluster GPU Instances. This new implementation of SEGA has been tested on a subset of protein structure data contained in the CavBase, providing a structural comparison of protein binding sites on a much larger scale than in previous research efforts reported in the literature.
Keywords
Java; biology computing; cloud computing; graph theory; graphics processing units; Amazon EC2 Cluster GPU Instances; CPU-based Java version; GPU-based cloud computing; NVIDIA GPU; OpenCL; SEGA; graph-based algorithm; protein binding sites structure; Cavity resonators; Graphics processing unit; Hardware; Instruction sets; Kernel; Proteins; Runtime; Cloud computing; GPU; OpenCL; graph alignment; protein binding sites; structure comparison;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Ecosystems Technologies (DEST), 2012 6th IEEE International Conference on
Conference_Location
Campione d´Italia
ISSN
2150-4938
Print_ISBN
978-1-4673-1702-3
Electronic_ISBN
2150-4938
Type
conf
DOI
10.1109/DEST.2012.6227926
Filename
6227926
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