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Importance sampling for Ising computers using one-dimensional cellular automata

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4 Author(s)
Hortensius, P.D. ; IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA ; Card, H.C. ; McLeod, R.D. ; Pries, Werner

The authors demonstrate that one-dimensional (1-D) cellular automata (CA) form the basis of efficient VLSI architectures for computations involved in the Monte Carlo simulation of the two-dimensional (2-D) Ising model. It is shown that the time-intensive task of importance sampling the Ising configurations is expedited by the inherent parallelism in this approach. The CA architecture further provides a spatially distributed set of pseudorandom numbers that are required in the local nondeterministic decisions at the various sites in the array. The novel approach taken to random-number generation can also be applied to a variety of other highly nondeterministic algorithms from many fields, such as computational geometry, pattern recognition, and artificial intelligence

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Computers, IEEE Transactions on  (Volume:38 ,  Issue: 6 )