A Multi-GPU Approach to Fast Wildfire Hazard Mapping

  • Donato D’Ambrosio
  • Salvatore Di Gregorio
  • Giuseppe Filippone
  • Rocco Rongo
  • William Spataro
  • Giuseppe A. Trunfio
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 256)


Burn probability maps (BPMs) are among the most effective tools to support strategic wildfire and fuels management. In such maps, an estimate of the probability to be burned by a wildfire is assigned to each point of a raster landscape. A typical approach to build BPMs is based on the explicit propagation of thousands of fires using accurate simulation models. However, given the high number of required simulations, for a large area such a processing usually requires high performance computing. In this paper, we propose a multi-GPU approach for accelerating the process of BPM building. The paper illustrates some alternative implementation strategies and discusses the achieved speedups on a real landscape.


GPGPU Cellular Automata Wildfire Simulation Wildfire Susceptibility Hazard Maps 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Donato D’Ambrosio
    • 1
  • Salvatore Di Gregorio
    • 1
  • Giuseppe Filippone
    • 1
  • Rocco Rongo
    • 1
  • William Spataro
    • 1
  • Giuseppe A. Trunfio
    • 2
  1. 1.Department of Mathematics and Computer ScienceUniversity of CalabriaRende (CS)Italy
  2. 2.DADU, University of SassariAlghero (SS)Italy

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