Time-Sharing Parallel Jobs in the Presence of Multiple Resource Requirements

Buffered coscheduling is a new methodology that can substantially increase resource utilization, improve response time, and simplify the development of the run-time support in a parallel machine. In this paper, we provide an in-depth analysis of three important aspects of the proposed methodology: the impact of the communication pattern and type of synchronization, the impact of memory constraints, and the processor utilization. The experimental results show that if jobs use non-blocking or collectivecommunication patterns, the response time becomes largely insensitive to the job communication pattern. Using a simple job access policy, we also demonstrate the robustness of buffered coscheduling in the presence of memory constraints. Overall, buffered coscheduling generally outperforms backfilling and backfilling gang scheduling with respect to response time, wait time, run-time slowdown, and processor utilization.