Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/36521

TitleParallel evolutionary computation in bioinformatics applications
Author(s)Pinho, Jorge
Sobral, João Luís Ferreira
Rocha, Miguel
KeywordsEvolutionary computation
Parallel software development
Aspect oriented programming
Bioinformatics
Issue dateMay-2013
PublisherElsevier
JournalComputer Methods and Programs in Biomedicine
Abstract(s)A large number of optimization problems within the field of Bioinformatics require methods able to handle its inherent complexity (e.g. NP-hard problems) and also demand increased computational efforts. In this context, the use of parallel architectures is a necessity. In this work, we propose ParJECoLi, a Java based library that offers a large set of metaheuristic methods (such as Evolutionary Algorithms) and also addresses the issue of its efficient execution on a wide range of parallel architectures. The proposed approach focuses on the easiness of use, making the adaptation to distinct parallel environments (multicore, cluster, grid) transparent to the user. Indeed, this work shows how the development of the optimization library can proceed independently of its adaptation for several architectures, making use of Aspect-Oriented Programming. The pluggable nature of parallelism related modules allows the user to easily configure its environment, adding parallelism modules to the base source code when needed. The performance of the platform is validated with two case studies within biological model optimization.
TypeArticle
DescriptionSupplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/ j.cmpb.2012.10.001
URIhttp://hdl.handle.net/1822/36521
DOI10.1016/j.cmpb.2012.10.001
ISSN0169-2607
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CCTC - Artigos em revistas internacionais
DI/CCTC - Artigos (papers)

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