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Distributed versus Centralized Storage and Control for Parallel Branch and Bound: Mixed Integer Programming on the CM-5

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Abstract

This paper describes parallel, non-shared-memoryimplementation of the classical general mixed integer branch and boundalgorithm, with experiments on the CM-5 family of parallel processors. Themain issue in such an implementation is whether task scheduling and certaindata-storage functions should be handled by a single processor, orspread among multiple processors. The centralized approach riskscreating processing bottlenecks, while the more decentralizedimplementations differ more from the fundamental serial algorithm.Extensive computational tests on standard MIPLIB problems comparecentralized, clustered, and fully decentralized task scheduling methods, using a novel combination of random work scattering and rendezvous-basedglobal load balancing, along with a distributed “control by token”technique. Further experiments compare centralized and distributedschemes for storing heuristic “pseudo-cost” branching data. The distributed storage method is based on continual asynchronous reductionalong a tree of redundant storage sites. On average, decentralized taskscheduling appears at least as effective as central control, butpseudo-cost storage should be kept as centralized as possible.

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  1. Faculty of Management and RUTCOR, Rutgers University, P.O. Box 5062, New Brunswick, NJ, 08903-5062, USA

    Jonathan Eckstein

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  1. Jonathan Eckstein
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Eckstein, J. Distributed versus Centralized Storage and Control for Parallel Branch and Bound: Mixed Integer Programming on the CM-5. Computational Optimization and Applications 7, 199–220 (1997). https://doi.org/10.1023/A:1008699010646

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