Parallel cellular automaton tumor growth model

Salguero Hidalgo, Alberto Gabriel; Capel Tuñón, Manuel Isidoro; Tomeu Hardasmal, Antonio J.

doi:https://doi.org/10.1007/978-3-319-98702-6_21

Artículo procedente de comunicación a 12th International Conference Practical Applications of Computational Biology and Bioinformatics, . PACBB2018 2018 (1018.Kb)

Identificadores

URI: https://hdl.handle.net/10481/88754

DOI: https://doi.org/10.1007/978-3-319-98702-6_21

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Editorial

Springer

Materia

Cellular automaton

High performance computing

Mathematical oncology

Tumoral growth simulation Parallel programming

Speedup

Date

2019-01-01

Referencia bibliográfica

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.

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.

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