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

Research output: Contribution to journalArticleScientificpeer-review

82 Citations (Scopus)


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
Number of pages30
JournalIntegration : the VLSI Journal
Issue number3
Publication statusPublished - 1986
Externally publishedYes


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