Gain Scheduled Control for Nonlinear Power Management in CMPs
Bryan Donyanavard1,a, Amir M. Rahmani1,2,e, Tiago Mück1,b, Kasra Moazemmi1,c and Nikil Dutt 1,d
1University of California, Irvine, USA
abdonyana@uci.edu
btmuck@uci.edu
cmoazzemi@uci.edu
ddutt@uci.edu
2TU Wien, Vienna, Austria
eamirr1@uci.edu
ABSTRACT
Dynamic voltage and frequency scaling (DVFS) is a well‐established technique for power management of thermal‐ or energy‐sensitive chip multiprocessors (CMPs). In this context, linear control theoretic solutions have been successfully implemented to control the voltage‐frequency knobs. However, modern CMPs with a large range of operating frequencies and multiple voltage levels display nonlinear behavior in the relationship between frequency and power. State‐of‐the‐art linear controllers therefore under‐optimize DVFS operation. We propose a Gain Scheduled Controller (GSC) for nonlinear runtime power management of CMPs that simplifies the controller implementation of systems with varying dynamic properties by utilizing an adaptive control theoretic approach in conjunction with static linear controllers. Our design improves the accuracy of the controller over a static linear controller with minimal overhead. We implement our approach on an Exynos platform containing ARM's big.LITTLEbased heterogeneous multi-processor (HMP) and demonstrate that the system's response to changes in target power is improved by 2× while operating up to 12% more efficiently for tracking accuracy.
Keywords: DVFS, Non‐linear System Dynamics, Gain Scheduling, Control Theory, CMPs, Self‐Adaptive Power Management.
