Predictive temperature-aware DVFS

Jong Sung Lee; Kevin Skadron; Sung Woo Chung

doi:10.1109/TC.2009.136

Predictive temperature-aware DVFS

Jong Sung Lee, Kevin Skadron, Sung Woo Chung

Department of Computer Science and Engineering

Research output: Contribution to journal › Article › peer-review

69 Citations (Scopus)

Abstract

In this paper, we propose predictive temperature-aware Dynamic Voltage and Frequency Scaling (DVFS) using the performance counters that are already embedded in commercial microprocessors. By using the performance counters and simple regression analysis, we can predict the localized temperature and efficiently scale the voltage/frequency. When localized thermal problems that were not detected by thermal sensors are found after layout (or fabrication), the thermal problems can be avoided by the proposed software solution without delaying time-to-market. The evaluation results show that in a Linux-based laptop with the Intel Core2 Duo processor, DVFS using the performance counters performs comparable to DVFS using the thermal sensor.

Original language	English
Article number	5255230
Pages (from-to)	127-133
Number of pages	7
Journal	IEEE Transactions on Computers
Volume	59
Issue number	1
DOIs	https://doi.org/10.1109/TC.2009.136
Publication status	Published - 2010

Keywords

DVFS
Dynamic thermal management
Microprocessor
Performance counter
Thermal sensor

ASJC Scopus subject areas

Software
Theoretical Computer Science
Hardware and Architecture
Computational Theory and Mathematics

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title = "Predictive temperature-aware DVFS",

abstract = "In this paper, we propose predictive temperature-aware Dynamic Voltage and Frequency Scaling (DVFS) using the performance counters that are already embedded in commercial microprocessors. By using the performance counters and simple regression analysis, we can predict the localized temperature and efficiently scale the voltage/frequency. When localized thermal problems that were not detected by thermal sensors are found after layout (or fabrication), the thermal problems can be avoided by the proposed software solution without delaying time-to-market. The evaluation results show that in a Linux-based laptop with the Intel Core2 Duo processor, DVFS using the performance counters performs comparable to DVFS using the thermal sensor.",

keywords = "DVFS, Dynamic thermal management, Microprocessor, Performance counter, Thermal sensor",

author = "Lee, {Jong Sung} and Kevin Skadron and Chung, {Sung Woo}",

note = "Funding Information: This paper is an extended version of [3]. This work was supported by the Korea Research Foundation Grant of the Korean Government (KRF-2006-331-D00452), and the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MEST) (No. R01-2007-000-20750-0). This work was also funded by the US National Science Foundation under grant no. EHS-0509245 and a grant from Intel MRL. The authors would like to thank Professor Gabriel Loh for providing Core 2 Duo related parameters. Finally, they would like to thank the anonymous reviewers for their helpful feedback. Sung Woo Chung is the corresponding author of this paper.",

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N1 - Funding Information: This paper is an extended version of [3]. This work was supported by the Korea Research Foundation Grant of the Korean Government (KRF-2006-331-D00452), and the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MEST) (No. R01-2007-000-20750-0). This work was also funded by the US National Science Foundation under grant no. EHS-0509245 and a grant from Intel MRL. The authors would like to thank Professor Gabriel Loh for providing Core 2 Duo related parameters. Finally, they would like to thank the anonymous reviewers for their helpful feedback. Sung Woo Chung is the corresponding author of this paper.

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AB - In this paper, we propose predictive temperature-aware Dynamic Voltage and Frequency Scaling (DVFS) using the performance counters that are already embedded in commercial microprocessors. By using the performance counters and simple regression analysis, we can predict the localized temperature and efficiently scale the voltage/frequency. When localized thermal problems that were not detected by thermal sensors are found after layout (or fabrication), the thermal problems can be avoided by the proposed software solution without delaying time-to-market. The evaluation results show that in a Linux-based laptop with the Intel Core2 Duo processor, DVFS using the performance counters performs comparable to DVFS using the thermal sensor.

KW - DVFS

KW - Dynamic thermal management

KW - Microprocessor

KW - Performance counter

KW - Thermal sensor

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Predictive temperature-aware DVFS

Abstract

Keywords

ASJC Scopus subject areas

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