Future Generation Computer Systems - Special issue on cellular automata: promise in computational science
Theory of Self-Reproducing Automata
Theory of Self-Reproducing Automata
Parallel evolutionary modelling of geological processes
Parallel Computing
A work-efficient GPU algorithm for level set segmentation
ACM SIGGRAPH 2010 Posters
Mathematical and Computer Modelling: An International Journal
Cellular Automata and GPGPU: An Application to Lava Flow Modeling
International Journal of Grid and High Performance Computing
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The individuation of areas that are more likely to be impacted by new events in volcanic regions is of fundamental relevance for mitigating possible consequences, both in terms of loss of human lives and material properties. For this purpose, the lava flow hazard maps are increasingly used to evaluate, for each point of a map, the probability of being impacted by a future lava event. Typically, these maps are computed by relying on an adequate knowledge about the volcano, assessed by an accurate analysis of its past behavior, together with the explicit simulation of thousands of hypothetical events, performed by a reliable computational model. In this paper, General-Purpose Computation with Graphics Processing Units (GPGPU) is applied, in conjunction with the SCIARA lava flow Cellular Automata model, to the process of building the lava invasion maps. Using different GPGPU devices, the paper illustrates some different implementation strategies and discusses numerical results obtained for a case study at Mt. Etna (Italy), Europe's most active volcano.