A new kind of science
GPU Cluster for High Performance Computing
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
OpenGL(R) Shading Language (2nd Edition)
OpenGL(R) Shading Language (2nd Edition)
Generating Surface Textures based on Cellular Networks
GMAI '06 Proceedings of the conference on Geometric Modeling and Imaging: New Trends
OpenGL(R) Programming Guide: The Official Guide to Learning OpenGL(R), Version 2 (5th Edition) (OpenGL)
Fast Genetic Programming and Artificial Developmental Systems on GPUs
HPCS '07 Proceedings of the 21st International Symposium on High Performance Computing Systems and Applications
Information Visualization of Multi-dimensional Cellular Automata using GPU Programming
IV '07 Proceedings of the 11th International Conference Information Visualization
Retina simulation using cellular automata and GPU programming
Machine Vision and Applications
A structurally dynamic cellular automaton with memory in the hexagonal tessellation
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
CA models of myxobacteria swarming
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
A cellular automata model for species competition and evolution
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
A flow modeling of lubricating greases under shear deformation by cellular automata
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
Modeling robot path planning with CD++
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
Structure and reversibility of 2D hexagonal cellular automata
Computers & Mathematics with Applications
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We propose a graphics processor unit (GPU)-accelerated method for real-time computing and rendering cellular automata (CA) that is applied to hexagonal grids.Based on our previous work [9] ---which introduced first and second dimensional cases--- this paper presents a model for hexagonal grid algorithms. Proposed method is novel and it encodes and transmits large CA key-codes to the graphics card and consequently, this technique allows to visualize the CA information flow in real-time to easily identify emerging behaviors even for large data sets. To show the efficiency of our model we first present a set of characteristic hexagonal behaviors, and then describe computational statistics for central processing unit (CPU) and GPU on a set of different hardware and operating system (OS) configurations. We show that our model is flexible and very efficient as it permits to compute CA close to a thousand times faster than classical CPU methods. Additionally, free access is provided to our downloadable software for hexagonal grid CA simulations.