Fast Assessment of Wildfire Spatial Hazard with GPGPU

Donato D'Ambrosio, Salvatore Di Gregorio, Giuseppe Filippone, Rocco Rongo, William Spataro, Giuseppe A. Trunfio

2012

Abstract

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.

References

  1. Ager, A. and Finney, M. (2009). Application of wildfire simulation models for risk analysis. In Geophysical Research Abstracts, Vol. 11, EGU2009-5489, EGU General Assembly.
  2. Alexander, M. (1985). Estimating the length-to-breadth ratio of elliptical forest fire patterns. In Proc. 8th Conf. Fire and Forest Meteorology, pages 287-304.
  3. Anderson, H. (1983). Predicting wind-driven wildland fire size and shape. Technical Report INT-305, U.S Department of Agriculture, Forest Service.
  4. Andrews, P. (1986). BEHAVE: fire behavior prediction and fuel modeling system - burn subsystem, part 1. Technical Report INT-194, U.S Department of Agriculture, Forest Service.
  5. Blecic, I., Cecchini, A., and Trunfio, G. A. (2009). A general-purpose geosimulation infrastructure for spatial decision support. Transactions on Computational Science, 6:200-218.
  6. Carmel, Y., Paz, S., Jahashan, F., and Shoshany, M. (2009). Assessing fire risk using monte carlo simulations of fire spread. Forest Ecology and Management, 257(1):370 - 377.
  7. Cui, W. and Perera, A. H. (2008). A study of simulation errors caused by algorithms of forest fire growth models. Technical Report 167, Ontario Forest Research Institute.
  8. Filippone, G., Spataro, W., Spingola, G., D'Ambrosio, D., Rongo, R., Perna, G., and Di Gregorio, S. (2011). GPGPU programming and cellular automata: Implementation of the sciara lava flow simulation code. In 23rd European Modeling and simulation Symposium (EMSS), Rome, Italy.
  9. Forthofer, J., Shannon, K., and Butler, B. (2009). Simulating diurnally driven slope winds with windninja. In Proceedings of 8th Symposium on Fire and Forest Meteorological Society - Kalispell, MT.
  10. French, I., Anderson, D., and Catchpole, E. (1990). Graphical simulation of bushfire spread. Mathematical Computer Modelling, 13:67-71.
  11. Johnston, P., Kelso, J., and Milne, G. (2008). Efficient simulation of wildfire spread on an irregular grid. International Journal of Wildland Fire, 17:614-627.
  12. Kourtz, P. H. and O'Regan, W. G. (1971). A model for a small forest fire to simulate burned and burning areas for use in a detection model. Forest Science, 17(7):163-169.
  13. Krger, F., Maitre, O., Jimenez, S., Baumes, L., and Collet, P. (2010). Speedups between x70 and x120 for a generic local search (memetic) algorithm on a single gpgpu chip. In Di Chio, C., Cagnoni, S., Cotta, C., Ebner, M., Ekárt, A., Esparcia-Alcazar, A., Goh, C.-K., Merelo, J., Neri, F., Preu, M., Togelius, J., and Yannakakis, G., editors, EvoNum 2010, volume 6024 of LNCS, pages 501-511. Springer Berlin / Heidelberg.
  14. Lopes, A. M. G., Cruz, M. G., and Viegas, D. X. (2002). Firestation - an integrated software system for the numerical simulation of fire spread on complex topography. Environmental Modelling and Software, 17(3):269-285.
  15. McAlpine, R., Lawson, B., and Taylor, E. (1991). Fire spread across a slope. In Proceedings of the 11th Conference on Fire and Forest Meteorology (Society of American Foresters: Bethesda, MD), pages 218- 225.
  16. Miyamoto, H. and Sasaki, S. (1997). Simulating lava flows by an improved cellular automata method. Computers & Geosciences, 23(3):283-292.
  17. NVidia corp. (2010). CUDA C Programming Guide v. 3.2.
  18. NVidia corp. (2012). CUDA C Best Practices Guide.
  19. O'Regan, W. G., Kourtz, P., and Nozaki, S. (1976). Bias in the contagion analog to fire spread. Forest Science, 22.
  20. Pallipuram, V., Bhuiyan, M., and Smith, M. (2011). A comparative study of GPU programming models and architectures using neural networks. The Journal of Supercomputing, pages 1-46.
  21. Peterson, S. H., Morais, M. E., Carlson, J. M., Dennison, P. E., Roberts, D. A., Moritz, M. A., and Weise, D. R. (2009). Using HFIRE for spatial modeling of fire in shrublands. Technical Report PSW-RP-259, U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station, Albany, CA.
  22. Preis, T. (2011). GPU-computing in econophysics and statistical physics. The European Physical Journal - Special Topics, 194(1):87-119.
  23. Roberts, M., Sousa, M. C., and Mitchell, J. R. (2010). A work-efficient gpu algorithm for level set segmentation. In ACM SIGGRAPH 2010 Posters, SIGGRAPH 7810, pages 53:1-53:1, New York, NY, USA. ACM.
  24. Rongo, R., Lupiano, V., Avolio, M. V., D'Ambrosio, D., Spataro, W., and Trunfio, G. A. (2011). Cellular automata simulation of lava flows - applications to civil defense and land use planning with a cellular automata based methodology. In Kacprzyk, J., Pina, N., and Filipe, J., editors, SIMULTECH 2011, pages 37-44. SciTePress.
  25. Rongo, R., Spataro, W., D'Ambrosio, D., Avolio, M. V., Trunfio, G. A., and Gregorio, S. D. (2008). Lava flow hazard evaluation through cellular automata and genetic algorithms: an application to mt etna volcano. Fundam. Inform., 87(2):247-267.
  26. Rothermel, R. C. (1972). A mathematical model for predicting fire spread in wildland fuels. Technical Report INT-115, U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, Ogden, UT.
  27. Rothermel, R. C. (1983). How to predict the spread and intensity of forest and range fires. Technical Report INT143, U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, Ogden, UT.
  28. Sullivan, A. (2009). Wildland surface fire spread modelling, 1990-2007. 3: Simulation and mathematical analogue models. International Journal of Wildland Fire, 18:387-403.
  29. Szerwinski, R. and Güneysu, T. (2008). Exploiting the power of GPUs for asymmetric cryptography. In Proceedings of the 10th International Workshop on Cryptographic Hardware and Embedded Systems (CHES 2008), pages 79-99, Washington, DC, USA.
  30. Trunfio, G. A. (2004). Predicting wildfire spreading through a hexagonal cellular automata model. In Sloot, P. M. A., Chopard, B., and Hoekstra, A. G., editors, ACRI, volume 3305 of LNCS, pages 385-394. Springer.
  31. Trunfio, G. A., D'Ambrosio, D., Rongo, R., Spataro, W., and Gregorio, S. D. (2011). A new algorithm for simulating wildfire spread through cellular automata. ACM Trans. Model. Comput. Simul., 22(1):6.
  32. Yassemi, S., Dragicevic, S., and Schmidt, M. (2008). Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour. Ecological Modelling, 210(1-2):71-84.
Download


Paper Citation


in Harvard Style

D'Ambrosio D., Di Gregorio S., Filippone G., Rongo R., Spataro W. and A. Trunfio G. (2012). Fast Assessment of Wildfire Spatial Hazard with GPGPU . In Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-8565-20-4, pages 260-269. DOI: 10.5220/0004070902600269


in Bibtex Style

@conference{simultech12,
author={Donato D'Ambrosio and Salvatore Di Gregorio and Giuseppe Filippone and Rocco Rongo and William Spataro and Giuseppe A. Trunfio},
title={Fast Assessment of Wildfire Spatial Hazard with GPGPU},
booktitle={Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2012},
pages={260-269},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004070902600269},
isbn={978-989-8565-20-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Fast Assessment of Wildfire Spatial Hazard with GPGPU
SN - 978-989-8565-20-4
AU - D'Ambrosio D.
AU - Di Gregorio S.
AU - Filippone G.
AU - Rongo R.
AU - Spataro W.
AU - A. Trunfio G.
PY - 2012
SP - 260
EP - 269
DO - 10.5220/0004070902600269