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Mapping of Hierarchical Parallel Genetic Algorithms for Protein Folding onto Computational Grids Weiguo LIU Bertil SCHMIDT Publication IEICE TRANSACTIONS on Information and Systems Vol.E89-D No.2 pp.589-596 Publication Date: 2006/02/01 Online ISSN: 1745-1361 DOI: 10.1093/ietisy/e89-d.2.589 Print ISSN: 0916-8532 Type of Manuscript: Special Section PAPER (Special Section on Parallel/Distributed Computing and Networking) Category: Grid Computing Keyword: protein folding, HP lattice models, hierarchical parallel genetic algorithms, computational grids, generic programming, Full Text: PDF(606.7KB)>>
Summary: Genetic algorithms are a general problem-solving technique that has been widely used in computational biology. In this paper, we present a framework to map hierarchical parallel genetic algorithms for protein folding problems onto computational grids. By using this framework, the two level communication parts of hierarchical parallel genetic algorithms are separated. Thus both parts of the algorithm can evolve independently. This permits users to experiment with alternative communication models on different levels conveniently. The underlying programming techniques are based on generic programming, a programming technique suited for the generic representation of abstract concepts. This allows the framework to be built in a generic way at application level and thus provides good extensibility and flexibility. Experiments show that it can lead to significant runtime savings on PC clusters and computational grids. | ||||||||||
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