Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/83221
Title: A Variation-Aware Adaptive Fuzzy Control System for Thermal Management of Microprocessors
Authors: Cui, Yingnan
Zhang, Wei
He, Bingsheng
Keywords: Thermal management
Pragmatics
Issue Date: 2017
Source: Cui, Y., Zhang, W., & He, B. (2017). A Variation-Aware Adaptive Fuzzy Control System for Thermal Management of Microprocessors. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 25(2), 683-695.
Series/Report no.: IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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.
URI: https://hdl.handle.net/10356/83221
http://hdl.handle.net/10220/42493
ISSN: 1063-8210
DOI: 10.1109/TVLSI.2016.2596338
Schools: School of Computer Science and Engineering 
Rights: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TVLSI.2016.2596338].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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