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    STUDIA PHYSICA - Issue no. 1 / 2008  
         
  Article:   CELLULAR NEURAL NETWORK COMPUTERS AND THEIR APPLICATIONS IN PHYSICS.

Authors:  MÁRIA ERCSEY-RAVASZ. 		 
       
         
  Abstract:  The computational paradigm represented by Cellular Neural/Nonlinear Networks (CNN) and the CNN Universal Machine (CNN-UM) as a Cellular Wave Computer, gives new perspectives for computational physics. Many numerical problems and simulations can be elegantly addressed on this fully parallelized and analogic architecture: solving partial differential equations and implementing cellular automata models are just some basic examples. We also study the possibility of performing stochastic simulations on this chip. First a realistic random number generator is implemented on the CNN-UM, then as an example the site-percolation problem and the two-dimensional Ising model are studied by Monte Carlo type simulations. The results obtained on an experimental version of the CNN-UM with 128×128 cells (ACE16K) are in good agreement with the results obtained on digital computers. Computational time measurements suggest that the developing trend of the CNN-UM chips - increasing the lattice size and the number of local logic memories - will assure an important advantage for the CNN-UM in the near future.

Keywords. Computer modeling and simulation, Statistical physics and nonlinear dynamics, Computer science and technology

PACS: 07.05.Tp, 05.10.Ln, 89.20.Ff


  
         
     
         
         
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