GPGPU (General Purpose computing on GraphicsProcessing Units) has marked a revolution in the field of Parallel Computing allowing to achieve computational performance unimaginable until a few years ago. This hardware has proven to be extremely reliable and suitable to simulate Cellular Automata (CA) models for modeling complex systems whose evolution can be described in terms of local interactions. Starting from previous GPGPU implementations of CA models with CUDA, this paper presents an effective implementation of a well-known numerical model for simulating lava flows on Graphical Processing Units (GPU) based on the OpenCL (Open Computing Language) standard. In addition, a preliminary Civil Defence application related Hazard maps of an area located at Mt. Etna volcano (South Italy), confirms the validity of OpenCL and both low-cost and high-end graphics hardware as an alternative to expensive solutions for the simulation of CA models.

No abstract

No abstract

This paper presents the parallel implementation, using the Compute Unified Device Architecture (CUDA) architecture, of the SCIARA-fv3 Complex Cellular Automata model for simulating lava flows. The computational model is based on a Bingham-like rheology and both flow velocity and the physical time corresponding to a computational step have been made explicit. The parallelization design has involved, among other issues, the application of strategies that can avoid incorrect computation results due to race conditions and achieving the best performance and occupancy of the underlying available hardware. Two hardware types were adopted for testing different versions of the CUDA implementations of the SCIARA-fv3 model, namely the GTX 580 and GTX 680 graphic processors. Despite its computational complexity,carried out experiments of the model parallelization have shown significant performance improvements, confirming that graphic hardware can represent a valid solution for the implementation of Cellular Automata models.

No abstract