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Adaptive and autonomous thermal tracking for high performance computing systems

Published: 13 June 2010 Publication History

Abstract

Many DTM schemes rely heavily on the accurate knowledge of the chip's dynamic thermal state to make optimal performance/temperature trade-off decisions. This information is typically generated using a combination of thermal sensor inputs and various estimation schemes such as Kalman filter. A basic assumption used by such schemes is that the statistical characteristics of the power consumption do not change. This is problematic since such characteristics are heavily application dependent. In this paper, we first present autonomous schemes for detecting the change in the statistical characteristics of power and then propose adaptive schemes for capturing such new statistical parameters dynamically. This could enable accurate temperature estimation during runtime given dynamically changing power statistical states. Our schemes use a combination of hypothesis testing and residual whitening methods and can improve the accuracy by 67% as compared to the traditional non-adaptive schemes.

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Cited By

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  • (2021)A Method for Run-Time Prediction of On-Chip Thermal Conditions in Dynamically Reconfigurable SOPCsInternational Journal of Reconfigurable Computing10.1155/2021/88187882021Online publication date: 7-Jan-2021
  • (2020)Applying Chaos Theory for Runtime Hardware Trojan Monitoring and DetectionIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2018.286473317:4(716-729)Online publication date: 1-Jul-2020
  • (2019)Model-based temperature estimation of power electronics systemsControl Engineering Practice10.1016/j.conengprac.2019.01.00685(206-215)Online publication date: Apr-2019
  • Show More Cited By

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    cover image ACM Conferences
    DAC '10: Proceedings of the 47th Design Automation Conference
    June 2010
    1036 pages
    ISBN:9781450300025
    DOI:10.1145/1837274
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 13 June 2010

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    Author Tags

    1. adaptive
    2. power characteristics
    3. sensor
    4. statistical
    5. temperature tracking

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    Cited By

    View all
    • (2021)A Method for Run-Time Prediction of On-Chip Thermal Conditions in Dynamically Reconfigurable SOPCsInternational Journal of Reconfigurable Computing10.1155/2021/88187882021Online publication date: 7-Jan-2021
    • (2020)Applying Chaos Theory for Runtime Hardware Trojan Monitoring and DetectionIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2018.286473317:4(716-729)Online publication date: 1-Jul-2020
    • (2019)Model-based temperature estimation of power electronics systemsControl Engineering Practice10.1016/j.conengprac.2019.01.00685(206-215)Online publication date: Apr-2019
    • (2017)Dynamic temperature estimation of power electronics systems2017 American Control Conference (ACC)10.23919/ACC.2017.7963482(3463-3469)Online publication date: May-2017
    • (2015)Temperature Tracking: Toward Robust Run-Time Detection of Hardware TrojansIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2015.242492934:10(1577-1585)Online publication date: Oct-2015
    • (2015)Near-Optimal Thermal Monitoring Framework for Many-Core Systems-on-ChipIEEE Transactions on Computers10.1109/TC.2015.239542364:11(3197-3209)Online publication date: 1-Nov-2015
    • (2015)Applying chaos theory for runtime Hardware Trojan detection2015 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)10.1109/CISDA.2015.7208642(1-6)Online publication date: May-2015
    • (2015)Power-Thermal Modeling and Control of Energy-Efficient Servers and DatacentersHandbook on Data Centers10.1007/978-1-4939-2092-1_29(857-913)Online publication date: 17-Mar-2015
    • (2014)A Secure Algorithm for Task Scheduling against Side-channel AttacksProceedings of the 4th International Workshop on Trustworthy Embedded Devices10.1145/2666141.2666142(3-12)Online publication date: 3-Nov-2014
    • (2014)Temperature-Assisted Clock Synchronization and Self-Calibration for Sensor NetworksIEEE Transactions on Wireless Communications10.1109/TWC.2014.051414.13027013:6(3419-3429)Online publication date: Jun-2014
    • Show More Cited By

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