Multiprogramming a distributed-memory multiprocessor

TL;DR: A model of a simple multiprocessor system with a two-program workload is reviewed and applied to an Intel iPSC/2 hypercube multipROcessor with a workload consisting of parallel wavefront algorithms for solving triangular systems of linear equations, indicating that significant performance improvements for multiproscessor systems are possible through multiprogramming.

Abstract: The development of computing systems with large numbers of processors has been motivated primarily by the need to solve large complex problems more quickly than is possible with uniprocessor systems. Traditionally, multiprocessor systems have been uniprogrammed, i.e., dedicated to the execution of a single set of related processes, since this approach provides the fastest response for an individual program once it begins execution. However, if the goal of a multiprocessor system is to minimize average response time or to maximize throughput, then multiprogramming must be considered. In this paper, a model of a simple multiprocessor system with a two-program workload is reviewed; the model is then applied to an Intel iPSC/2 hypercube multiprocessor with a workload consisting of parallel wavefront algorithms for solving triangular systems of linear equations. Throughputs predicted by the model are compared with throughputs obtained experimentally from an actual system. The results provide validation for the model and indicate that significant performance improvements for multiprocessor systems are possible through multiprogramming. 4 refs., 10 figs., 1 tab.