Unstructured tree search on SIMD parallel computers: A summary of results

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

In this paper, we present new methods for load balancing of unstructured tree computations on large-scale SIMD machines, and analyze the scalability of these and other existing schemes. An efficient formulation of tree search on a SIMD machine comprises of two major components: (i) a triggering mechanism, which determines when the search space redistribution must occur to balance search space over processors; and (ii) a scheme to redistribute the search space. We have devised a new redistribution mechanism and a new triggering mechanism. Either of these can be used in conjunction with triggering and redistribution mechanisms developed by other researchers. We analyze the scalability of these mechanisms, and verify the results experimentally. The analysis and experiments show that our new load balancing methods are highly scalable on SIMD architectures. Their scalability is shown to be no worse than that of the best load balancing schemes on MIMD architectures. We verify our theoretical results by implementing the 15-puzzle problem on a CM-21 SIMD parallel computer.

Original languageEnglish (US)
Title of host publicationProceedings of the 1992 ACM/IEEE conference on Supercomputing, Supercomputing 1992
EditorsRobert Werner
PublisherAssociation for Computing Machinery
Pages453-462
Number of pages10
ISBN (Electronic)0818626305
DOIs
StatePublished - Dec 1 1992
Event1992 ACM/IEEE conference on Supercomputing, Supercomputing 1992 - Minneapolis, United States
Duration: Nov 16 1992Nov 20 1992

Publication series

NameProceedings of the International Conference on Supercomputing
VolumePart F129723

Other

Other1992 ACM/IEEE conference on Supercomputing, Supercomputing 1992
Country/TerritoryUnited States
CityMinneapolis
Period11/16/9211/20/92

Bibliographical note

Funding Information:
1 Introduction Tree search is central to solving a variety of problems in artificial intelligence [12, 26], combinatorial optimization [11, 21], operations research [25] and Monte-Carlo evaluations of functional integrals [31]. The trees that need to be searched for most practical problems happen to be quite large, and for many tree search algorithms, different parts can be searched relatively independently. These trees tend to be highly irregular in nature and hence, a naive scheme for partitioning the search space can result in highly uneven distribution of work among processors and lead to poor overall performance. The job of partitioning irregular search spaces is particularly difficult for SIMD parallel computers such as the CM-2, in which all processors work in lock-step to execute the same *This work was supported by IST/SDIO through the Army Research Office grant #28408-MA-SDI and by the Army High Performance Computing Research Center at the University of Minnesota.

Publisher Copyright:
© 1992 IEEE.

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