Parallel implementations of the statistical cooling algorithm

E.H.L. Aarts, F.M.J. Bont, de, E.H.A. Habers, P.J.M. Laarhoven, van

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    82 Citations (Scopus)
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    Statistical Cooling is an optimization technique based on Monte-Carlo techniques. Here we propose two parallel formulations of the statistical cooling algorithm, i.e. a systolic algorithm and a clustered algorithm. Both algorithms are based on the requirement that quasi-equilibrium is preserved throughout the optimization process. It is shown that the parallel algorithms can be executed with a polynomial-time complexity. Performance of the algorithms is discussed by means of implementations on an experimental multi-processor architecture. It is concluded that substantial reduction of computation time can be achieved by both parallel algorithms compared to the sequential algorithm.
    Original languageEnglish
    Pages (from-to)209-238
    JournalIntegration : the VLSI Journal
    Issue number3
    Publication statusPublished - 1986


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