Mitigating Resource Contention on Multicore Systems via Scheduling

摘要

This paper addresses the resource contention issue caused by the sharing of the last level caches by introducing a novel contention-aware scheduler. To accurately determine a task's resource requirements, i.e. the unique input of our scheduler, we develop a methodology to select the best heuristic metric from five candidates to represent a task's resource requirements. Based on the heuristic of each task acquired by exploiting the performance monitor unit, our scheduler co-schedules tasks with complementary resource requirements by combining scheduling order adjustments with task-to-core reassignments. The proposed scheduler has been implemented in the completely fair scheduler, rotating staircase deadline scheduler and O(1) schedulers. Using eight workloads constructed from nine NASA advanced supercomputing serial benchmarks on an Intel dual-core platform, the execution time of an individual task is reduced by up to 21%, system scalability and performance of a workload are improved by up to 13%, and the full potential of the contention-aware scheduling can be achieved if the time slice length and the period of executing each task once are short enough. In addition, our proposal exhibits benefits in the reduction of the execution time fluctuation of individual tasks due to an enforcement of reasonable usage of shared resources. Finally, we demonstrate an expected performance improvement on an Intel eight-core platform in order to suggest the broad applicability of our protocol.