Green High Performance Simulation for AMB models of Aedes aegypti

  • Erica Soledad Montes de Oca Instituto de Investigación en Informática LIDI, Facultad de Informática, Universidad Nacional de La Plata
  • Remo Suppi Universitat Autònoma de Barcelona, Department of Computer Architecture and Operating Systems, School of Engineering, Campus Bellaterra, Barcelona, Spain
  • Laura Cristina De Gisuti Computer Science Research Institute LIDI (III-LIDI), School of Computer Science, National University of La Plata (UNLP) – Scientific Research Agency of the Province of Buenos Aires (CICPBA), La Plata, Buenos Aires, Argentina
  • Marcelo Naiouf Computer Science Research Institute LIDI (III-LIDI), School of Computer Science, National University of La Plata (UNLP) – Scientific Research Agency of the Province of Buenos Aires (CICPBA), La Plata, Buenos Aires, Argentina
Keywords: Aedes aegypti, GPU, Green Computing, ABM models, High Performance Simulation

Abstract

The increase in temperature caused by the climate change has resulted in the rapid dissemination of infectious diseases. Given the alert for the current situation, the World Health Organization (WHO) has declared a state of health emergency, highlighting the severity of the situation in some countries. For this reason, coming up with knowledge and tools that can help control and eradicate the vectors propagating these diseases is of the utmost importance. High-performance modeling and simulation can be used to produce knowledge and strategies that allow predicting infections, guiding actions and/or training health/civil protection agents. The model developed as part of this research work is aimed at assisting the decision-making process for disease prevention and control, as well as evaluating the reproduction and predicting the evolution of the Aedes aegypti mosquito, which is the transmitting vector of the dengue, Zika and chikungunya diseases. Since a large number of simulation runs are required to achieve results with statistical variability, GPU has been used. This platform has enough computational power to reduce execution time while maintaining a lower energy consumption. Different scenarios and experiments are proposed to corroborate the benefits of the architecture proposed.

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to be published in Proc. of MAS2019: E. Montes de Oca, R. Suppi, L. De Gisuti, M. Naiouf. ABM in FlameGPU for assessment of the pupal productivity of the vector transmitting infectious diseases Aedes Aegypti. Octubre, Lisboa, Portugal.

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Published
2020-05-26
How to Cite
Montes de OcaE. S., SuppiR., De GisutiL. C., & NaioufM. (2020). Green High Performance Simulation for AMB models of Aedes aegypti. Journal of Computer Science and Technology, 20(1), e02. https://doi.org/10.24215/16666038.20.e02
Section
Original Articles