NDLI: Leakage-aware Kalman filter for accurate temperature tracking

Content Provider	IEEE Xplore Digital Library
Author	Yufu Zhang Srivastava, A.
Copyright Year	2011
Description	Author affiliation: Dept. of Electrical and Computer Engineering, University of Maryland, College Park, USA (Yufu Zhang; Srivastava, A.)
Abstract	Due to the effect of technology scaling, leakage power now consists of a significant portion of the total power consumption of a silicon chip. Leakage power also increases exponentially with chip temperature, while temperature itself is a strong function in total power (positive feedback effect). Most of the existing techniques for estimating the runtime chip temperature do not consider the nonlinear leakage effect. This could lead to many problems such as under-estimation of the real chip temperature, improper thermal control actions and eventually, unreliable chip behavior. In this paper we discuss two linearization techniques that can be used to extend the existing thermal tracking approaches and explicitly account for the leakage effect. The first one uses Taylor series expansion to approximate leakage power to the first order (extended Kalman filter). The second one uses concepts from probabilistic matching. Both methods can approximate leakage power with high accuracy while maintaining similar computational efficiency compared to the standard Kalman filter. The experimental results demonstrated that our approaches can reduce the temperature estimation error by 60%, thus significantly improving the thermal-awareness of chip system and enhancing the performance of many dynamic power/thermal management techniques.
Starting Page	1
Ending Page	7
File Size	235711
Page Count	7
File Format	PDF
ISBN	9781457712227
e-ISBN	9781457712210
DOI	10.1109/IGCC.2011.6008561
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Temperature sensors Computational modeling Temperature tracking Kalman filter Model Covariance matrix Mathematical model Kalman filters Leakage power Equations Sensor
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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