Abstract
One of the challenges still open to wildland fire simulators is the capacity of working under real- time constrains with the aim of providing fire spread predictions that could be useful in fire mitigation interventions. In this paper, a parallel optimization framework for improving wildland fire prediction is applied to a real laboratory fire. The proposed prediction methodology has been tested on a Linux cluster using MPI.
This work has been financially supported by the Comisión Interministerial de Ciencia y Tecnología (CICYT) under contract TIC2001-2592 and by the European Commission under contract EVG1-CT-2001-00043 SPREAD
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Abdalhaq, B., Bianchini, G., Cortés, A., Margalef, T., Luque, E. (2003). Improving Wildland Fire Prediction on MPI Clusters. In: Dongarra, J., Laforenza, D., Orlando, S. (eds) Recent Advances in Parallel Virtual Machine and Message Passing Interface. EuroPVM/MPI 2003. Lecture Notes in Computer Science, vol 2840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39924-7_69
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DOI: https://doi.org/10.1007/978-3-540-39924-7_69
Publisher Name: Springer, Berlin, Heidelberg
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