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Some massively parallel algorithms from nature

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Wuhan University Journal of Natural Sciences

Abstract

We introduced the work on parallel problem solvers from physics and biology being developed by the research team at the State Key Laboratory of Software Engineering, Wuhan University. Results on parallel solvers include the following areas: Evolutionary algorithms based on imitating the evolution processes of nature for parallel problem solving, especially for parallel optimization and model-building; Asynchronous parallel algorithms based on domain decomposition which are inspired by physical analogies such as elastic relaxation process and annealing process, for scientific computations, especially for solving nonlinear mathematical physics problems. All these algorithms have the following common characteristics: inherent parallelism, self-adaptation and self-organization, because the basic ideas of these solvers are from imitating the natural evolutionary processes.

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Authors and Affiliations

  1. The State Key Laboratory of Software Engineering, Wuhan University, 430072, Wuhan, Hubei, China

    Li Yan, Kang Li-shan, Chen Yu-ping, Liu Pu, Cao Hong-qing & Pan Zheng-jun

Authors
  1. Li Yan
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  2. Kang Li-shan
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  3. Chen Yu-ping
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  4. Liu Pu
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  5. Cao Hong-qing
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  6. Pan Zheng-jun
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Additional information

Foundation item: Supported by the National Natural Science Foundation of China (No. 60133010, No. 70071042, No. 60073043) and National Laboratory for Parallel and Distributed Processing

Biography: Li Yan (1974-), female, Ph. D candidate, research direction: evolutionary computation.

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Yan, L., Li-shan, K., Yu-ping, C. et al. Some massively parallel algorithms from nature. Wuhan Univ. J. Nat. Sci. 7, 37–46 (2002). https://doi.org/10.1007/BF02830011

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  • DOI: https://doi.org/10.1007/BF02830011

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