A Variation-Aware Adaptive Fuzzy Control System for Thermal Management of Microprocessors

Abstract

Thermal failures pose severe threats to reliability and performance of modern microprocessors, which calls for thermal management solutions to effectively control the temperature within a processor. Among various thermal management techniques, closed-loop thermal controllers have the advantages of high control accuracy and high response speed. However, it is challenging for closed-loop thermal controllers to deal with static and dynamic thermal model uncertainties, which significantly affect the control quality of the controller. In this paper, we propose an adaptive fuzzy controller for thermal management of microprocessors with adaptability to thermal model variations. The experiments with microbenchmarks and the SPEC CPU2006 benchmarks demonstrate that our adaptive fuzzy controller maintains the control quality when faced with severe variations of the thermal model. Compared with state-of-the-art thermal controllers with thermal model calibration capabilities, our design shows a comparable performance with much lower complexity and design cost.