Abstract
The Duplicate Removal Problem (DRP) appears in a number of applications such as protocol verification, database operations and image processing. Although numerous parallel sorting algorithms have been proposed, DRP has received relatively little attention. In this paper we propose and study three parallel duplicate removal algorithms. The algorithms are implemented and evaluated on an Intel iPSC/2 hypercube. We assume that all the data are resident in the main memory and do not consider the I/O access times. The results indicate that the performance of a parallel duplicate removal algorithm is a function of the system and data conditions, viz. the number of nodes, the number of data values, the uniqueness factors, and the processing and data transfer speeds. The results suggest amethod of selecting an optimum algorithm based on the data and system conditions. To interpret and scale the results of the experiments, we developed analytical models of the algorithms. Those models compare favorably to the results obtained experimentally. Finally the average computational complexity of each of the three algorithms is presented.
Published Version
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