Fast Assessment of Wildfire Spatial Hazard with GPGPU

In the field of wildfire risk management the so-called burn probability maps (BPMs) are increasingly used with the aim of estimating the probability of each point of a landscape to be burned under certain environmental conditions. Such BPMs are computed through the explicit simulation of thousands of fires using fast and accurate simulation models. However, even adopting the most optimized simulation algorithms, the building of simulation-based BPMs for large areas results in a highly intensive computational process that makes mandatory the use of high performance computing. In this paper, General-Purpose Computation with Graphics Processing Units (GPGPU) is applied, in conjunction with a specifically devised wildfire simulation model, to the process of BPM building. Using two different GPGPU devices, the paper illustrates two different implementation strategies and discusses some numerical results obtained on a real landscape.