Artificial Chemistries on GPU

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. L. Yamamoto ( ) P. Collet ICUBE, University of Strasbourg, Illkirch, France e-mail: [email protected]; [email protected] W. Banzhaf Memorial University of Newfoundland, St. John’s, Canada e-mail: [email protected] S. Tsutsui and P. Collet (eds.), Massively Parallel Evolutionary Computation on GPGPUs, Natural Computing Series, DOI 10.1007/978-3-642-37959-8 18, © Springer-Verlag Berlin Heidelberg 2013 389 390 L. Yamamoto et al.