Sorting large data sets on a massively parallel system

Abstract

This paper presents a performance study for many of today's popular parallel sorting algorithms. It is the first to present a comparative study on a large scale MIMD system. The machine, a Parsytec GCel, contains 1024 processors connected as a two-dimensional grid. To justify the experimental results, we develop a theoretical model to predict the performance in terms of communication and computation times. We get a very close relation between the experiments and the theoretical model as long as the edge congestion caused by the algorithms is predicted precisely. We compare: Bitonicsort, Shearsort, Gridsort, Samplesort, and Radixsort. Experiments were performed using random instances according to a well known benchmark problem. Results show that for the machine we used, Bitonicsort performs best for smaller numbers of keys per processor (<2048) and Samplesort outperforms all other methods for larger instances.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>