Dirigent

Abstract

Latency-critical applications suffer from both average performance degradation and reduced completion time predictability when collocated with batch tasks. Such variation forces the system to overprovision resources to ensure Quality of Service (QoS) for latency-critical tasks, degrading overall system throughput. We explore the causes of this variation and exploit the opportunities of mitigating variation directly to simultaneously improve both QoS and utilization. We develop, implement, and evaluate Dirigent, a lightweight performance-management runtime system that accurately controls the QoS of latency-critical applications at fine time scales, leveraging existing architecture mechanisms. We evaluate Dirigent on a real machine and show that it is significantly more effective than configurations representative of prior schemes.