Stochastic simulations on the cellular wave computers |
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Authors: | M Ercsey-Ravasz T Roska Z Néda |
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Institution: | (1) Department of Information Technology, Pázmány Péter Catholic University, HU-1083 Budapest, Hungary;(2) Department of Physics, Babeş-Bolyai University, 400084 Cluj, Romania;(3) Los Alamos National Laboratory, Center for Nonlinear Sciences, Los Alamos, NM 87545, USA |
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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. Here we study the possibility of performing
stochastic simulations on this chip. First a realistic random number generator is implemented on the
CNN-UM, and then as an example the two-dimensional Ising model is studied by Monte Carlo type simulations. The results obtained
on an experimental version of the CNN-UM with 128 ×128 cells 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. |
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Keywords: | 07 05 Tp Computer modeling and simulation 05 10 Ln Monte Carlo methods 89 20 Ff Computer science and technology |
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