Distributed game-tree searching
- Computing Science Dept., Univ. of Alberta, Alberta (CA)
Conventional parallelizations of the alpha-beta ({alpha}{beta}) algorithm have met with limited success. Implementations suffer primarily from the synchronization and search overheads of parallelization. This paper describes a parallel {alpha}{beta} searching program that achieves high performance through the use of four different types of processes: Controllers, Searchers, Table Managers, and Scouts. Synchronization is reduced by having Controller process reassigning idle processes to help out busy ones. Search overhead is reduced by having two types of parallel table management: global Table Managers and the periodic merging and redistribution of local tables. Experiments show that nine processors can achieve 5.67-fold speedups but beyond that, additional processors provide diminishing returns. Given that additional resources are of little benefit, speculative computing is introduced as a means of extending the effective number of processors that can be utilized. Scout processes speculatively search ahead in the tree looking for interesting features and communicate this information back to the {alpha}{beta} program. In this way, the effective search depth is extended. These ideas have been tested experimentally and empirically as part of the chess program ParaPhoenix.
- OSTI ID:
- 5145338
- Journal Information:
- Journal of Parallel and Distributed Computing; (USA), Journal Name: Journal of Parallel and Distributed Computing; (USA) Vol. 6:1; ISSN JPDCE; ISSN 0743-7315
- Country of Publication:
- United States
- Language:
- English
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