An FPGA Design for the Stochastic Greenberg-Hastings Cellular Automata

Nikolaos Vlassopoulos 1 Nazim Fatès 1 Hugues Berry 2, 3 Bernard Girau 4
1 MAIA - Autonomous intelligent machine
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
2 COMBINING - COMputational BIology and data miNING
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information, Inria Grenoble - Rhône-Alpes
4 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : The stochastic Greenberg-Hastings cellular automaton is a model that mimics the propagation of reaction-diffusion waves in active media. Notably, this model undergoes a phase transition when the probability of excitation of a cell varies. We developed a specific FPGA design to study the critical behavior of this model. Using dedicated architectural optimizations, we obtain a significant speed-up with respect to software simulation for lattice sizes of 512×512. We exploited this speed-up to obtain improved estimations of the critical threshold.Our results indicate the existence of an asymptotic value of this threshold when the number of cell states increases.
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Conference papers
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https://hal.inria.fr/inria-00522193
Contributor : Bernard Girau <>
Submitted on : Thursday, September 30, 2010 - 10:09:25 AM
Last modification on : Wednesday, November 20, 2019 - 2:56:26 AM

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  • HAL Id : inria-00522193, version 1

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Nikolaos Vlassopoulos, Nazim Fatès, Hugues Berry, Bernard Girau. An FPGA Design for the Stochastic Greenberg-Hastings Cellular Automata. International Conference on High Performance Computing & Simulation - HPCS 2010, Jun 2010, Caen, France. pp.565-574. ⟨inria-00522193⟩

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