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Artificial Chemistries on GPU

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Massively Parallel Evolutionary Computation on GPGPUs

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Abstract

An Artificial Chemistry is an abstract model of a chemistry that can be used to model real chemical and biological processes, as well as any natural or artificial phenomena involving interactions among objects and their transformations. It can also be used to perform computations inspired by chemistry, including heuristic optimization algorithms akin to evolutionary algorithms, among other usages. Artificial chemistries are conceptually parallel computations, and could greatly benefit from parallel computer architectures for their simulation, especially as GPU hardware becomes widespread and affordable. However, in practice it is difficult to parallelize artificial chemistry algorithms efficiently for GPUs, particularly in the case of stochastic simulation algorithms that model individual molecular collisions and take chemical kinetics into account. This chapter surveys the current state of the art in the techniques for parallelizing artificial chemistries on GPUs, with focus on their stochastic simulation and their applications in the evolutionary computation domain. Since this problem is far from being entirely solved to satisfaction, some suggestions for future research are also outlined.

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Acknowledgements

We would like to thank the University of Strasbourg and the Region d’Alsace for funding a postdoctoral stay of L. Yamamoto and a visiting stay of W. Banzhaf under the EVOL grant. W. Banzhaf also acknowledges support through the NSERC Discovery Grant program under RGPIN 283304-12.

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Authors and Affiliations

  1. ICUBE, University of Strasbourg, Illkirch, France

    Lidia Yamamoto & Pierre Collet

  2. Memorial University of Newfoundland, St. John’s, Canada

    Wolfgang Banzhaf

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  1. Lidia Yamamoto
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  2. Pierre Collet
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  3. Wolfgang Banzhaf
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Correspondence to Lidia Yamamoto .

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  1. and Information Science, Hannan University Dept. of Management, Matsubara, Osaka, Japan

    Shigeyoshi Tsutsui

  2. ICube Laboratory UMR CNRS 7357, Université de Strasbourg, Illkirch, France

    Pierre Collet

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Yamamoto, L., Collet, P., Banzhaf, W. (2013). Artificial Chemistries on GPU. In: Tsutsui, S., Collet, P. (eds) Massively Parallel Evolutionary Computation on GPGPUs. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37959-8_18

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