Abstract

A new parallel sorting algorithm suitable for MIMD multiprocessors is presented. The algorithm reduces memory and bus contention, which many parallel sorting algorithms suffer from, by using a regular sampling of the data to ensure good pivot selection. For n data elements to be sorted and p processors, when n p 3 the algorithm is shown to be asymptotically optimal. In theory, the algorithm is within a factor of two of achieving ideal load balancing. In practice, there is almost perfect partitioning of work. On a variety of shared and distributed memory machines, the algorithm achieves better than half-linear speedups. - 1. Introduction Sorting is one of most studied problems in computer science because of its theoretical interest and practical importance. With the advent of parallel processing, parallel sorting has become an important area for algorithm research. Although considerable work has been done on the theory of parallel sorting and efficient implementations on SIMD arch...

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