Error-Safe, Portable, and Efficient Evolutionary Algorithms Implementation with High Scalability

Dieterich, J. M. and Hartke, Bernd (2016) Error-Safe, Portable, and Efficient Evolutionary Algorithms Implementation with High Scalability Journal of Chemical Theory and Computation, 12 (10). pp. 5226-5233. DOI 10.1021/acs.jctc.6b00716.

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Abstract

We present an efficient massively parallel implementation of genetic algorithms for chemical and materials science problems, solely based on Java virtual machine (JVM) technologies and standard networking protocols. The lack of complicated dependencies allows for a highly portable solution exploiting strongly heterogeneous components within a single computational context. At runtime, our implementation is almost completely immune to hardware failure, and additional computational resources can be added or subtracted dynamically, if needed. With extensive testing, we show that despite all these benefits, parallel scalability is excellent.

Document Type: Article
Additional Information: Times Cited: 0 Dieterich, Johannes M. Hartke, Bernd
Research affiliation: Kiel University
OceanRep > The Future Ocean - Cluster of Excellence
Refereed: Yes
DOI etc.: 10.1021/acs.jctc.6b00716
ISSN: 1549-9618
Projects: Future Ocean
Date Deposited: 27 Feb 2017 09:38
Last Modified: 27 Feb 2017 09:38
URI: http://eprints.uni-kiel.de/id/eprint/36054

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