Mapping of Hierarchical Parallel Genetic Algorithms for Protein Folding onto Computational Grids(Grid Computing, <Special Section> Parallel/Distributed Computing and Networking)

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概要

• 論文の詳細を見る

• 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.

• 社団法人電子情報通信学会の論文
• 2006-02-01

著者

• Liu Weiguo

  School Of Computer Engineering Nanyang Technological University

• SCHMIDT Bertil

  School of Computer Engineering, Nanyang Technological University

• Schmidt Bertil

  School Of Computer Engineering Nanyang Technological University

関連論文

• Mapping of Hierarchical Parallel Genetic Algorithms for Protein Folding onto Computational Grids(Grid Computing, Parallel/Distributed Computing and Networking)

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