Revisiting Symbiotic Job Scheduling

Abstract : —Symbiotic job scheduling exploits the fact that in a system with shared resources, the performance of jobs is impacted by the behavior of other co-running jobs. By coscheduling combinations of jobs that have low interference, the performance of a system can be increased. In this paper, we investigate the impact of using symbiotic job scheduling for increasing throughput. We find that even for a theoretically optimal scheduler, this impact is very low, despite the substantial sensitivity of per job performance to which other jobs are coscheduled: for example, our experiments on a 4-thread SMT processor show that, on average, the job IPC varies by 37% depending on coscheduled jobs, the per-coschedule throughput varies by 69%, and yet the average throughput gain brought by optimal symbiotic scheduling is only 3%. This small margin of improvement can be explained by the observation that all the jobs need to be eventually executed, restricting the job combinations a symbiotic job scheduler can select to optimize throughput. We explain why previous work reported a substantial gain from symbiotic job scheduling, and we find that (only) reporting turnaround time can lead to misleading conclusions. Furthermore , we show how the impact of scheduling can be evaluated in microarchitectural studies, without having to implement a scheduler.
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Stijn Eyerman, Pierre Michaud, Wouter Rogiest. Revisiting Symbiotic Job Scheduling. IEEE International Symposium on Performance Analysis of Systems and Software, Mar 2015, Philadelphia, United States. ⟨10.1109/ISPASS.2015.7095791⟩. ⟨hal-01139807⟩

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