Power and energy containers for multicore servers

Authors:
Kai Shen;Arrvindh Shriraman;Sandhya Dwarkadas;Xiao Zhang
Affiliations:
University of Rochester, Rochester, NY, USA;Simon Fraser University, Surrey, BC, Canada;University of Rochester, Rochester, NY, USA;University of Rochester, Rochester, NY, USA
Venue:
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
Year:
2012

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Abstract

Power capping and energy efficiency are critical concerns in server systems, particularly when serving dynamic workloads on resource-sharing multicores. We present a new operating system facility (power and energy containers) that accounts for and controls the power/energy usage of individual fine-grained server requests. This facility is enabled by novel techniques for multicore power attribution to concurrent tasks, measurement/modeling alignment to enhance predictability, and request power accounting and control.