Generic Parallel Genetic Algorithm Framework for Protein Optimisation

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Title Generic Parallel Genetic Algorithm Framework for Protein Optimisation
Author Folkman, Lukas; Pullan, Wayne John; Stantic, Bela
Publication Title 11th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP 2011)
Editor Yang Xiang Alfredo Cuzzocrea Michael Hobbs Wanlei Zhou
Year Published 2011
Place of publication Germany
Publisher Springer
Abstract Proteins are one of the most vital macromolecules on the cellular level. In order to understand the function of a protein, its structure needs to be determined. For this purpose, different computational approaches have been introduced. Genetic algorithms can be used to search the vast space of all possible conformations of a protein in order to find its native structure. A framework for design of such algorithms that is both generic, easy to use and performs fast on distributed systems may help further development of genetic algorithm based approaches. We propose such a framework based on a parallel master-slave model which is implemented in C++ and Message Passing Interface. We evaluated its performance on distributed systems with a different number of processors and achieved a linear acceleration in proportion to the number of processing units.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1007/978-3-642-24669-2_7
ISBN 978-3-642-24649-4
Conference name ICA3PP 2011
Location Melbourne, Australia
Date From 2011-10-24
Date To 2011-10-26
URI http://hdl.handle.net/10072/43564
Date Accessioned 2012-02-02; 2012-03-12T05:41:21Z
Date Available 2012-03-12T05:41:21Z
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Neural, Evolutionary and Fuzzy Computation
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

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