Parallel Job Scheduling in Homogeneous Distributed Systems

Abstract

The performance of parallel programs such as those involving fork-join instructions is significantly affected by the method used to schedule program tasks. This article studies parallel job scheduling in homogeneous distributed systems. A simulation model is used to address performance issues associated with scheduling. Various policies are employed to schedule parallel jobs over a variety of workloads. Fairness is required among competing jobs. The authors examine cases in which the distribution of the number of parallel tasks per job, as well as the distribution of task service demand, varies with time. They also examine the impact of overhead necessary to collect global system information about processor queues on performance. Simulated results indicate that although all scheduling methods have merit, one significantly improves the overall performance and guarantees fairness in terms of individual job execution.