Parallel cellular automaton tumor growth model

Abstract

In silico” experimentation allows us to simulate the effect of different therapies by handling model parameters. Although the computational simulation of tumors is currently a well-known technique, it is however possible to contribute to its improvement by parallelizing simulations on computer systems of many and multi-cores. This work presents a proposal to parallelize a tumor growth simulation that is based on cel-lular automata by partitioning of the data domain and by dynamic load balancing. The initial results of this new approach show that it is pos-sible to successfully accelerate the calculations of a known algorithm for tumor growth.