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Porting and optimizing MAGFLOW on CUDA

Giuseppe Bilotta, Eugenio Rustico, Alexis Herault, Annamaria Vicari, Giovanni Russo, Ciro Del Negro, Giovanni Gallo
Universita di Catania, Dipartimento di Matematica e Informatica, Catania, Italy
Annals of Geophysics, 54, 5, 2011

@article{bilotta2011porting,

   title={Porting and optimizing MAGFLOW on CUDA},

   author={Bilotta, G. and Rustico, E. and H{‘e}rault, A. and Vicari, A. and Russo, G. and Del Negro, C. and Gallo, G.},

   journal={Annals of Geophysics},

   volume={54},

   number={5},

   year={2011}

}

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The 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 cell-based 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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