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A parallel solution to the extended set union problem with unlimited backtracking

机译:通过无限返回的扩展集合问题的并行解决方案

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We study on the EREW-PRAM model a parallel solution to the extended set union problem with unlimited backtracking which maintains a dynamic partition /spl Pi/ of an n-element set S subject to the usual operations Find, Union, Backtrack and Restore as well as the new operations SetUnion, MultiUnion. The SetUnion operation as a special case of the commonly known Union operation aimed to unify two pre-specified set-names, while MultiUnion operation deals with a batch of Union operations. A new data structure, called k-Parallel Union Find (or, k-PUF) trees, is introduced to represent a disjoint set in /spl Pi/. The structure is defined for a wide range for the parameter k, but the more interesting results are achieved for k=log n/log log n. In this case, using the k-PUF trees, both SetUnion and Restore operations are performed in constant parallel time requiring optimal work O(k). This constant-time performance is not achievable parallelizing the existing data structures. Moreover, using p=O(k) processors, MultiUnion for a batch of p operations is performed in O(k) time, requiring optimal work O(pk).
机译:我们在Erew-PRAM模型中研究了扩展集合问题的并行解决方案,通过无限的回溯,维护了一个动态分区/ SPL PI / N元素集的N元素集,同时,Union,Backtrack和Restore也是如此作为新的操作setUnion,multiunion。 SETUNION操作作为常用的联合操作的特殊情况,旨在统一两个预先指定的设置名称,而Multiunion操作处理批次的工会操作。引入了一个新的数据结构,称为k平行联合查找(或K-PUF)树,以表示/ SPL PI /的不相交集合。对于参数k的宽范围定义了该结构,但是对于k = log n / log log n来实现更有趣的结果。在这种情况下,使用K-PUF树,SETUNION和恢复操作都以恒定的并行时间执行,需要最佳工作O(k)。这种恒定时间性能并行并行化现有数据结构并行化。此外,使用P = O(k)处理器,在O(k)时间中执行用于批次P操作的多元,需要最佳工作O(PK)。

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