The performance potential of run-to-completion (RTC) parallel processor scheduling policies is investigated by examining whether (1) application execution rate characteristics such as average parallelism (avg) and processor working set (PWS) and/or (2) limited preemption can be used to improve the performance of these policies. We address the first question by comparing policies (previous as well as new) that differ only in whether or not they use execution rate characteristics and by examining a wider range of the workload parameter space than previous studies. We address the second question by comparing a simple two-level queueing policy with RTC scheduling in the second level queue against RTC policies that don't allow any preemption and against dynamic equiallocation(EQ).

Using simulation to estimate mean response times we find that for promising RTC policies such as adaptive static partitioning (ASP) and shortest demand first (SDF), a maximum allocation constraint that is for all practical purposes independent of avg and pws provides greater and more consistent improvement in policy performance than using avg or pws. Also, under the assumption that job demand information is unavailable to the scheduler we show that the ASP-max policy outperforms all previous high performance RTC policies for workloads with coefficient of variation in processing requirement greater than one. Furthermore, a two-level queue that allows at most one preemption per job outperforms ASP-max but is not competitive with EQ.