Building analytical models into an interactive performance prediction tool

In this paper we describe an interactive tool designed for performance prediction of parallel programs. Static performance prediction, in general, is a very difficult task. In order to avoid some inherent problems, we concentrate on reasonably structured scientific programs. Our prediction system, which is built as a sub-system of a larger interactive environment, uses a parser, dependence analyzer, database and an X-window based front end in analyzing programs. The system provides the user with execution times of different sections of programs. When there are unknowns involved, such as number of processors or unknown loop bounds, the output is an algebraic expression in terms of these variables. We propose a simple analytical model as an attempt to predict performance degradation due to data references in hierarchical memory systems. The predicted execution times of some Lawrence Livermore loop kernels are given together with the experimental values obtained by executing the loops on Alliant FX/8.