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A parallel Boltzmann machine on distributed-memory multiprocessors

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4 Author(s)
J. H. Nang ; Dept. of Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea ; D. H. Oh ; Hyunsoo Yoon ; S. R. Maeng

An efficient mapping scheme of Boltzmann machine computations onto a distributed-memory multiprocessor, which exploits the synchronous spatial parallelism, is presented. In this scheme, the neurons in a Boltzmann machine are partitioned into p disjoint sets, and each set is mapped on a processor of a p-processor system. Parallel convergence and learning algorithms of Boltzmann machines, the necessary communication pattern among the processors, and their time complexities when neurons are partitioned and mapped onto a distributed-memory multiprocessor are investigated. An expected p -processor speed-up of the parallelizing scheme over a single processor is also analyzed theoretically. This analysis can be used as a basis for determining the most cost-effective or optimal number of processors according to the given communication capabilities and interconnection topologies

Published in:

Neural Networks, 1991. 1991 IEEE International Joint Conference on

Date of Conference:

18-21 Nov 1991