Affiliation:
1. University of California, San Diego, La Jolla, California
Abstract
Simultaneous Multithreading machines benefit from jobscheduling software that monitors how well coscheduled jobs share CPU resources, and coschedules jobs that interact well to make more efficient use of those resources. As a result, informed coscheduling can yield significant performance gains over naive schedulers. However, prior work on coscheduling focused on equal-priority job mixes, which is an unrealistic assumption for modern operating systems.This paper demonstrates that a scheduler for an SMT machine can both satisfy process priorities and symbiotically schedule low and high priority threads to increase system throughput. Naive priority schedulers dedicate the machine to high priority jobs to meet priority goals, and as a result decrease opportunities for increased performance from multithreading and coscheduling. More informed schedulers, however, can dynamically monitor the progress and resource utilization of jobs on the machine, and dynamically adjust the degree of multithreading to improve performance while still meeting priority goals.Using detailed simulation of an SMT architecture, we introduce and evaluate a series of five software and hardware-assisted priority schedulers. Overall, our results indicate that coscheduling priority jobs can significantly increase system throughput by as much as 40%, and that (1) the benefit depends upon the relative priority of the coscheduled jobs, and (2) more sophisticated schedulers are more effective when the differences in priorities are greatest. We show that our priority schedulers can decrease average turnaround times for a random jobmix by as much as 33%.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications,Hardware and Architecture,Software
Cited by
18 articles.
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