PARALLEL SIMULATION OF ASYNCHRONOUS CELLULAR AUTOMATA EVOLUTION
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For simulating physical and chemical processes on molecular level, asynchronous cellular automata with probabilistic transition rules are widely used being sometimes referred to as Monte-Carlo methods. The simulation requires a huge cellular space and millions of iterative steps for obtaining the CA evolution representing a real scene of the process. This may be attained by allocating the CA evolution program onto a multiprocessor system. We propose a new parallelization method of asynchronous CA based on its stochastic properties. The experiment results are presented.
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