Scalability of a multi-physics system for forest fire spread prediction in multi-core platforms

Angel Farguell; Ana Cortés; Tomàs Margalef; Josep R. Miró; J. Mercader

doi:10.1007/s11227-018-2330-9

Scalability of a multi-physics system for forest fire spread prediction in multi-core platforms

Angel Farguell, Ana Cortés, Tomàs Margalef, Josep R. Miró, J. Mercader

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1 Citation (Scopus)

Abstract

© 2018, The Author(s). Advances in high-performance computing have led to an improvement in modeling multi-physics systems because of the capacity to solve complex numerical systems in a reasonable time. WRF–SFIRE is a multi-physics system that couples the atmospheric model WRF and the forest fire spread model called SFIRE with the objective of considering the atmosphere–fire interactions. In systems like WRF–SFIRE, the trade-off between result accuracy and time required to deliver that result is crucial. So, in this work, we analyze the influence of WRF–SFIRE settings (grid resolutions) into the forecasts accuracy and into the execution times on multi-core platforms using OpenMP and MPI parallel programming paradigms.

Original language	English
Pages (from-to)	1163-1174
Journal	Journal of Supercomputing
Volume	75
Issue number	3
DOIs	https://doi.org/10.1007/s11227-018-2330-9
Publication status	Published - 1 Mar 2019

Keywords

Forest fire simulation
Multi-core
Multi-physics model
Scalability

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abstract = "{\textcopyright} 2018, The Author(s). Advances in high-performance computing have led to an improvement in modeling multi-physics systems because of the capacity to solve complex numerical systems in a reasonable time. WRF–SFIRE is a multi-physics system that couples the atmospheric model WRF and the forest fire spread model called SFIRE with the objective of considering the atmosphere–fire interactions. In systems like WRF–SFIRE, the trade-off between result accuracy and time required to deliver that result is crucial. So, in this work, we analyze the influence of WRF–SFIRE settings (grid resolutions) into the forecasts accuracy and into the execution times on multi-core platforms using OpenMP and MPI parallel programming paradigms.",

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AU - Cortés, Ana

AU - Margalef, Tomàs

AU - Miró, Josep R.

AU - Mercader, J.

PY - 2019/3/1

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AB - © 2018, The Author(s). Advances in high-performance computing have led to an improvement in modeling multi-physics systems because of the capacity to solve complex numerical systems in a reasonable time. WRF–SFIRE is a multi-physics system that couples the atmospheric model WRF and the forest fire spread model called SFIRE with the objective of considering the atmosphere–fire interactions. In systems like WRF–SFIRE, the trade-off between result accuracy and time required to deliver that result is crucial. So, in this work, we analyze the influence of WRF–SFIRE settings (grid resolutions) into the forecasts accuracy and into the execution times on multi-core platforms using OpenMP and MPI parallel programming paradigms.

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