Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/7603
AuthorsBilotta, G.* 
Rustico, E.* 
Herault, A.* 
Vicari, A.* 
Russo, G.* 
Del Negro, C.* 
Gallo, G.* 
TitlePorting and optimizing MAGFLOW on CUDA
Issue Date2011
Series/Report no.5/54 (2011)
DOI10.4401/ag-5341
URIhttp://hdl.handle.net/2122/7603
KeywordsGPGPU, Modeling, High-performance computing, Parallel computation, Hazard, Lava
Subject Classification04. Solid Earth::04.08. Volcanology::04.08.07. Instruments and techniques 
05. General::05.01. Computational geophysics::05.01.05. Algorithms and implementation 
05. General::05.02. Data dissemination::05.02.03. Volcanic eruptions 
05. General::05.05. Mathematical geophysics::05.05.99. General or miscellaneous 
AbstractThe MAGFLOW lava simulation model is a cellular automaton developed by the Sezione di Catania of the Istituto Nazionale di Geofisica e Vulcanologia (INGV) and it represents the peak of the evolution of cellbased models for lava-flow simulation. The accuracy and adherence to reality achieved by the physics-based cell evolution of MAGFLOW comes at the cost of significant computational times for long-running simulations. The present study describes the efforts and results obtained by porting the original serial code to the parallel computational platforms offered by modern video cards, and in particular to the NVIDIA Compute Unified Device Architecture (CUDA). A number of optimization strategies that have been used to achieve optimal performance on a graphic processing units (GPU) are also discussed. The actual benefits of running on the GPU rather than the central processing unit depends on the extent and duration of the simulated event; for large, long-running simulations, the GPU can be 70-to-80-times faster, while for short-lived eruptions with a small extents the speed improvements obtained are 40-to-50 times.
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