Runtime voltage/frequency scaling for energy-aware streaming applications

Abstract

Power and energy consumption, today essential in all types of systems, can be reduced by scaling the voltage/frequency at runtime and/or powering down idle components. Efficient management requires not only pertinent decisions, but also early access to workload information, as well as domain specific solutions. This paper focuses on runtime energy management for streaming applications running on multiprocessor platforms with dynamic voltage/frequency (speed) scaling capabilities. Our energy management occurs at processor level, and employs a number of orthogonal techniques based on hints gathered from load history, buffer pressure and future workload estimates. The manager operates both through speed adjustments and priorities. A preliminary evaluation based on a high-level simulation of an MPEG-4 SP decoder, shows that a combination of specific and generic techniques is the closest to an ideal energy lower bound.