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Heterogeneity has been recognized as an important way of improving the performance of multiprocessors by using fast processors to reduce the execution time of the serial fraction of a parallel computation. This paper considers multiprogrammed multiprocessors and parallel programs modeled as random task graphs. A theoretical analytical model to study combinations of extreme cases of workload parallelism (highly parallel versus highly sequential) and of system utilization (light versus heavy load) is presented. A simulation model was used to study intermediate cases. From these two models, conditions under which heterogeneity presents a significant performance improvement over homogeneous architectures are derived. The paper concludes with a study of the effect of scheduling policies for heterogeneous architectures on workloads of different degrees of parallelism under various system load conditions.

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