WRF-SFIRE: Análisis de rendimiento y optimización de recursos en ambientes HPC

  • Rodolfo Alejandro Schmidt Universidad Empresarial Siglo 21
  • Natalia Magris Universidad Empresarial Siglo 21
  • Eduardo Piray Universidad Empresarial Siglo 21
  • Miguel Mendez-Garabetti Universidad Empresarial Siglo 21

Abstract

The WRF-SFIRE model has become a valuable tool for wildfire prediction worldwide. However, its performance in parallel environments can be affected by the complexity of the model and resource limitations. This study evaluates the model’s performance in parallel environments and proposes optimization strategies to improve its efficiency and resource management/utilization. Representative cases will be conducted to assess the model’s performance with different software and hardware configurations, including CPU/GPU. The results of this study
can be useful for enhancing wildfire prediction capabilities and resource management efficiency in emergency situations.

Published
2023-10-12
How to Cite
Schmidt, R., Magris, N., Piray, E., & Mendez-Garabetti, M. (2023). WRF-SFIRE: Análisis de rendimiento y optimización de recursos en ambientes HPC. Proceedings of JAIIO, 9(6), 103-108. Retrieved from https://ojs.sadio.org.ar/index.php/JAIIO/article/view/785
Section
EST - Concurso de Trabajos Estudiantiles