Green high performance simulation for AMB models of Aedes aegypti

Título:

Green high performance simulation for AMB models of Aedes aegypti

Autor:

Montes de Oca, Erica Soledad

Colaboradores:

; Suppi, Remo; De Giusti, Laura Cristina; Naiouf, Ricardo Marcelo

Temas:

PROCESADORES GRÁFICOS (GPUs)COMPUTACIÓN DE ALTO RENDIMIENTO - HPC

En:

Journal of Computer Science & Technology, 20(1), pp. 15-22.

Resumen:

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. Highperformance 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. Decisionmaking based on these models requires a large number of simulations to achieve results with statistical variability. The objective of this paper is to demonstrate that the GPU is a suitable platform from the point of view of the reduction of energy consumed for HPC simulations. It is also shown that it is possible to define energy prediction models that allow scientists to plan their experiments based on energy consumption and select those that are representative for decision making by reducing energy consumption in HPC simulations.

URL/DOI:

https://doi.org/10.24215/16666038.20.e02

Palabras clave:

Aedes aegypti

Medio:

Soporte electrónico

Tipo de documento:

Artículo

Descripción física:

1 archivo (1,0 MB)

Idioma:

Inglés

Publicación:

, 2020

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