July 4, 2007 to July 6, 2007
Stephane Gobron , University of Aix-Marseille II, Luminy, F-13009 Marseille, France
Daniel Mestre , University of Aix-Marseille II, Luminy, F-13009 Marseille, France
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IV.2007.69
We propose a method for generating all possible rules of multidimension Boolean cellular automata (CA). Based on an original encoding method and the programming of graphical processor units (GPU), this method allows us to visualize the CA information flow in real-time so that emerging behaviors can be easily identified. Algorithms of first and von Neumann neighborhood second degrees are detailed with their respective Fragment Shaders programs. As symmetrical CA rules are especially useful in many research fields, we propose an encoding technique to automatically derive their codes; we then apply this technique to identify the 4096 possible cases for surface CA. To show the efficiency of our model a set of converging global behaviors are listed and described. In the last part of the paper we present methods for developing Moore neighborhood in two and in three dimensions. Finally we discus issues concerning computation and the visualization of non-Boolean and higher dimension CA.
Stephane Gobron, Daniel Mestre, "Information Visualization of Multi-dimensional Cellular Automata using GPU Programming", IV, 2007, 2013 17th International Conference on Information Visualisation, 2013 17th International Conference on Information Visualisation 2007, pp. 33-39, doi:10.1109/IV.2007.69