Dynamic power management under uncertain information

ABSTRACT

This paper tackles the problem of dynamic power management (DPM) in nanoscale CMOS design technologies that are typically affected by increasing levels of process, voltage, and temperature (PVT) variations and fluctuations. This uncertainty significantly undermines the accuracy and effectiveness of traditional DPM approaches. More specifically, we propose a stochastic framework to improve the accuracy of decision making in power management, while considering the manufacturing process and/or design induced uncertainties. A key characteristic of the framework is that uncertainties are effectively captured by a partially observable semi-Markov decision process. As a result, the proposed framework brings the underlying probabilistic PVT effects to the forefront of power management policy determination. Experimental results with a RISC processor demonstrate the effectiveness of the technique and show that our proposed variability-aware power management technique ensures robust system-wide energy savings under probabilistic variations.

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