Profile-based spatial partitioning for parallel simulation of large-scale wildfires

Spatial partitioning is commonly used for parallel simulation of spatial–temporal systems, such as simulations of wildfires. Achieving effective spatial partitioning is a challenging task due to the dynamic behavior of the simulation models. This paper presents a partitioning method named profile-based spatial partitioning for parallel simulation of large scale wildfires. The profile-based partitioning exploits the dynamic behavior of a wildfire spread simulation model and uses it as a profile to guide the spatial partitioning for parallel simulations. Experimental results show that the profile-based partitioning can increase the degree of parallelism and improve the scalability of parallel simulations of large-scale wildfires.