DMCA
Speculative Parallelism Improves Search? (1995)
| Citations: | 2 - 1 self |
BibTeX
@MISC{Marsland95speculativeparallelism,
author = {T. A. Marsland and Yaoqing Gao},
title = {Speculative Parallelism Improves Search? },
year = {1995}
}
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Abstract
The extreme efficiency of sequential search, and the natural tendency of tree pruning systems to produce wide variations in workload, partly explains why it is proving difficult to achieve more than 30-50 % efficiency for massively parallel implementations of the; algorithm. Here we introduce typical enhanced sequential algorithms and address the major issues of parallel game-tree searching under conditions of severe pruning. It is this pruning that makes the parallelization difficult. After examining previous work on parallel; algorithms, we present a new method called Dynamic Multiple Principal Variation Splitting (DM-PVSplit) and implement it on the AP1000. In this algorithm, high performance is achieved by using some novel approaches: Parallel speculative search of candidate principal variations is used to reduce re-search delay and so obtain more quickly a better estimate of the subtree value. This is achieved by configuring a at processor arrangement as a dynamically changeable tree structure. Also, with the aid of a group-based scheduling strategy, the game tree is split dynamically at different levels. This provides better load balance and takes more advantage of parallelism. Preliminary experiments show that the scalability of the DM-PVSplit algorithm is good for massively parallel machines.
Keyphrases
speculative parallelism parallel implementation dm-pvsplit algorithm new method wide variation natural tendency candidate principal variation novel approach sequential algorithm group-based scheduling strategy major issue different level 30-50 efficiency parallel machine previous work changeable tree structure severe pruning high performance parallel speculative search game tree subtree value sequential search processor arrangement re-search delay extreme efficiency dynamic multiple principal variation splitting load balance preliminary experiment
