Accelerating Wild Fire Simulator Using GPU

Abstract

In the last years, forest fire spread simulators have proven to be very promising tools in the fight against these disasters. Due to the necessity to achieve realistic predictions of the fire behavior in a relatively short time, execution time may be reduced. Moreover, several studies have tried to apply the computational power of GPUs (Graphic Processors Units) to accelerate the simulation of the propagation of fires. Most of these studies use forest fires simulators based on Cellular Automata (CA). CA approaches are fast and its parallelization is relatively easy; conversely, they suffer from precision lack. Elliptical wave propagation is an alternative approach for performing more reliable simulations. Unfortunately, its higher complexity makes their parallelization challenging. Here we explore two different parallel strategies based on Elliptical wave propagation forest fire simulators; the multicore architecture of CPU (Central Processor Unit) and the computational power of GPUs to improve execution times. The aim of this work is to assess the performance of the simulation of the propagation of forest fires on a CPU and a GPU, and finding out when the execution on GPU is more efficient than on CPU. In this study, a fire simulator has been designed based on the basic model for one point evolution in the FARSITE simulator. As study case, a synthetic fire with an initial circular perimeter has been used; the wind, terrain and vegetation conditions have been maintained constant throughout the simulation. Results highlighted that GPUs allow obtaining more accurate results while reducing the execution time of the simulations.