Parallel cellular automaton tumor growth model Salguero Hidalgo, Alberto Gabriel Capel Tuñón, Manuel Isidoro Tomeu Hardasmal, Antonio J. Cellular automaton High performance computing Mathematical oncology Tumoral growth simulation Parallel programming Speedup 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. 2024-02-08T13:27:37Z 2024-02-08T13:27:37Z 2019-01-01 conference output Salguero, A.G., Capel, M.I., Tomeu, A.J. (2019). Parallel Cellular Automaton Tumor Growth Model. In: Fdez-Riverola, F., Mohamad, M., Rocha, M., De Paz, J., González, P. (eds) Practical Applications of Computational Biology and Bioinformatics, 12th International Conference. PACBB2018 2018. https://hdl.handle.net/10481/88754 https://doi.org/10.1007/978-3-319-98702-6_21 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Springer