Scaling parallel programs for multiprocessors: methodology and examples

Abstract

Models for the constraints under which an application should be scaled, including constant problem-size scaling, memory-constrained scaling, and time-constrained scaling, are reviewed. A realistic method is described that scales all relevant parameters under considerations imposed by the application domain. This method leads to different conclusions about the effectiveness and design of large multiprocessors than the naive practice of scaling only the data set size. The primary example application is a simulation of galaxies using the Barnes-Hut hierarchical N-body method. >