AN EFFICIENT PARALLEL ALGORITHM TO EVOLVE SIMULATIONS OF THE CELLULAR POTTS MODEL
Abstract
Applications of the cellular Potts model to investigate cellular structures are becoming widely spread in the scientific literature. Despite its realism and generality, the standard Monte Carlo algorithm used to evolve this model in the scientific literature lacks computational efficiency. As an alternative we introduce the Random Walker algorithm that is a modified Monte Carlo procedure of simpler parallelization. We test it in cell sorting and foam coarsening simulations obtaining velocity increase factors of 10 and 3 times, respectively, in relation to the standard algorithm. The results obtained with these simulations are equivalent to those obtained with the standard algorithm.
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