Ranking and selection in a high performance computing environment

Abstract

We explore the adaptation of a ranking and selection procedure, originally designed for a sequential computer, to a high-performance (parallel) computing setting. We pay particular attention to screening and explaining why care is required in implementing screening in parallel settings. We develop an algorithm that allows screening at both the master and worker levels, and that apportions work to processors in such a way that excessive communication is avoided. In doing so we rely on a random number generator with many streams and substreams.