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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 1, 2018.
Abstract: This paper presents the implementation of a parallelization strategy using the OpenMP library, while developing a simulation tool based on a cellular automaton (CA) to run urban growth simulations. The characterization of an urban growth model CA is shown and it consists of a digitization process of the land use in order to get all the necessary elements for the CA to work. During the first simulation tests we noticed high processing times due to large quantity of calculations needed to perform one single simulation, in order to minimize this we implemented a parallelization strategy using the fork-join model in order to optimize the use of available hardware. The results obtained show a significant improvement in execution times in function of the number of available cores and map sizes, as a future work, it is planned to implement artificial neural networks in order to generate more complex urban growth scenarios.
Alvaro Peraza Garzón, René Rodríguez Zamora and Wenseslao Plata Rocha, “OpenMP Implementation in the Characterization of a Urban Growth Model Cellular Automaton” International Journal of Advanced Computer Science and Applications(IJACSA), 9(1), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090179
@article{Garzón2018,
title = {OpenMP Implementation in the Characterization of a Urban Growth Model Cellular Automaton},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090179},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090179},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {1},
author = {Alvaro Peraza Garzón and René Rodríguez Zamora and Wenseslao Plata Rocha}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.