串联并行图上并行算法设计的新框架

Yuval Caspi, E. Dekel
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引用次数: 0

摘要

作者提出了一种新的框架,用于在串联并行图上设计高效的并行算法。最近,d.e ppstein提出了一种新的序列平行图识别方法。Eppstein探索了一系列并行图的耳朵分解的特征,可以有效地并行识别。作者推广了Eppstein的结果,并通过寻找图的一个特殊的耳分解,统一地展示了如何有效地并行求解串联并行图上的问题。他们通过展示O(log n)并发读独占写(CREW)并行随机存取机(PRAM)算法来展示他们的新框架的实用性,该算法用于在序列并行图上构建深度优先生成树、st-编号和宽度优先生成树。
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A new framework for designing parallel algorithms on series parallel graphs
The authors propose a novel framework for designing efficient parallel algorithms on series parallel graphs. Recently, a novel approach for recognizing series parallel graphs was presented by D. Eppstein. Eppstein explored characterizations of the ear decomposition of series parallel graphs, which can be identified efficiently, in parallel. The authors extend Eppstein's results and show in a unified manner how to solve problems on series parallel graphs efficiently, in parallel, by finding a special ear decomposition of the graph. They demonstrate the utility of their novel framework by presenting O(log n) concurrent read exclusive write (CREW) parallel random access machine (PRAM) algorithms for the construction of a depth-first spanning tree, st-numbering, and a breadth-first spanning tree on series parallel graphs.<>
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