Parallel sorting by regular sampling

Abstract

A new parallel sorting algorithm suitable for MIMD multiprocessor 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 2 of achieving ideal load balancing. In practice, there is almost a perfect partitioning of work. On a variety of shared and distributed memory machines, the algorithm achieves better than half-linear speedups.