Teaching empirical performance analysis of parallel programs

Abstract

Performance is a central issue in parallel computing. In this paper, we describe our approach to teaching advanced undergraduates and graduate students about the fundamentals of measuring and analyzing the performance of programs running on a variety of parallel machines. This approach can be applied to virtually any type of parallel machine, as well as to parallel program simulators. Although performance analysis can serve many purposes, we focus on the needs of the parallel programmer: understanding the behavior of algorithms and programs, and making informed choices among them. © 1992, ACM. All rights reserved.