Copyright by William Lloyd Bircher 2010 - The Laboratory for ...

Chapter 7 Predictive Power Management
7.1 Core-Level Activity Prediction
Existing power management techniques operate by reducing performance capacity
(frequency, voltage, resource size) when performance demand is low, such as at idle or
similar low activity phases. In the case of multi-core systems, the performance and
power demand is the aggregate demand of all cores in the system. Monitoring aggregate
demand makes detection of phase changes difficult (active-to-idle, idle-to-active, etc.)
since aggregate phase behavior obscures the underlying phases generated by the
workloads on individual cores. This causes sub-optimal power management and over-
provisioning of power resources. In this study, these problems are addressed through
core-level, activity prediction.
The core-level view makes detection of phase changes more accurate, yielding more
opportunities for efficient power management. Due to the difficulty in anticipating
activity level changes, existing operating system power management strategies rely on
reaction rather than prediction. This causes sub-optimal power and performance since
changes in performance capacity by the power manager lag changes in performance
demand. To address this problem we propose the Periodic Power Phase Predictor
(PPPP). This activity level predictor decreases SYSmark 2007 client/desktop processor
power consumption by 5.4% and increases performance by 3.8% compared to the
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