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Implementation of Parallel Tree Skeletons on Distributed Systems

Trees are useful data types, but developing efficient parallel programs manipulating trees is known to be difficult, because of their irregular and imbalance structure. Parallel tree skeletons are designed to ease parallel programming by encouraging programmers to build parallel programs by combining them. However, for distributed systems, efficient implementations of these parallel tree skeletons are known to be hard. In this paper, we propose an implementation of parallel tree skeletons that run efficiently on distributed systems. Our approach is as follows, first we partition a tree by using m-bridge technique, and locally compute by composing functions, then propagate the results over the tree. The results of several experiments shows that our approach is promising, even if the tree is imbalanced. Furthermore, we present the conditions for efficient implementation. . . .