A common statistical problem is that of finding the median element in a set of data. This parallel MPI code implements an efficient, randomized high-level parallel algorithms for finding the median given a set of elements distributed across a parallel machine. In fact, our algorithm solves the general selection problem that requires the determination of the element of rank k, for an arbitrarily given integer k. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The algorithms have been coded in the message passing standard MPI, and our experimental results from the IBM SP-2 illustrate the scalability and efficiency of our algorithm and improve upon all the related experimental results known to the authors.

References:

D.A. Bader and J. Já Já. "Practical Parallel Algorithms for Dynamic Data Redistribution, Median Finding, and Selection," presented at the 10th International Parallel Processing Symposium (IPPS 96) Conference, Honolulu, HI, pp. 292-301, April 15-19, 1996.

D.A. Bader, "An Improved Randomized Selection Algorithm With an Experimental Study," presented at the Second Workshop on Algorithm Engineering and Experiments (ALENEX00), (sponsored by DIMACS, ACM SIGACT, and SIAM), San Francisco, CA, January 7-8, 2000.