Parallel N-ary speculative computation of simulated annealing

Author

Sohn, Andrew

Author_Institution

Dept. of Comput. & Inf. Sci., New Jersey Inst. of Technol., Newark, NJ, USA

Volume

6

Issue

10

fYear

1995

fDate

10/1/1995 12:00:00 AM

Firstpage

997

Lastpage

1005

Abstract

Simulated annealing is known to be an efficient method for combinatorial optimization problems. Its usage for realistic problem size, however, has been limited by the long execution time due to its sequential nature. This report presents a practical approach to synchronous simulated annealing for massively parallel distributed-memory multiprocessors. We use an n-ary speculative tree to execute n different iterations in parallel on n processors, called generalized speculative computation (GSC). Execution results of the 100- to 500-city traveling salesman problems on the AP1000 massively parallel multiprocessor demonstrate that the GSC approach can be an effective method for parallel simulated annealing as it gave over 20-fold speedup on 100 processors

Keywords

combinatorial mathematics; distributed memory systems; parallel algorithms; simulated annealing; travelling salesman problems; AP1000 massively parallel multiprocessor; combinatorial optimization problems; generalized speculative computation; massively parallel distributed-memory multiprocessors; parallel N-ary speculative computation; simulated annealing; traveling salesman problems; Circuit simulation; Computational modeling; Concurrent computing; Optimization methods; Parallel processing; Performance evaluation; Simulated annealing; Space exploration; Temperature; Traveling salesman problems;

fLanguage

English

Journal_Title

Parallel and Distributed Systems, IEEE Transactions on

Publisher

ieee

ISSN

1045-9219

Type

jour

DOI

10.1109/71.473510

Filename

473510