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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 pr
Ising computers; cellular automata; VLSI architectures; Monte Carlo simulation; importance sampling; Ising configurations; CA architecture; random-number generation; nondeterministic algorithms; finite automata; Ising model; Monte Carlo methods; parallel algorithms; parallel architectures; random number generation.

R. McLeod, P. Hortensius, H. Card and W. Pries, "Importance Sampling for Ising Computers Using One-Dimensional Cellular Automata," in IEEE Transactions on Computers, vol. 38, no. , pp. 769-774, 1989.
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