On‐Chip Lifetime Prediction for Dependable Many‐Processor SoCs based on Data Fusion

Ghazanfar Ali, Jerrin Pathrose Vareed, Hans G. Kerkhoff

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    2 Citations (Scopus)
    1 Downloads (Pure)

    Abstract

    The developments in technology and complexity of many-processor Systems-on-Chips emerge at a very rapid pace as is their introduction in safety-critical applications, for instance the transport sector. The inherent decrease in dependability of these complex nanosystems must be compensated by counter measures. One promising approach is the usage of IJTAG-compatible embedded instruments in and around cores, monitoring the "health" of target processors. It has been anticipated that these instruments will be (primarily) used for reducing the cost of final testing. In case of degradation during life time, however, they can be reused and counteractions like run-time remapping can be carried out. In this paper, the on-line data of two types of embedded instruments will be used for the prognostics, a slack-delay monitor and an IDDX monitor. Their (correlated) data is being fused which enables a more accurate life-time prediction as compared to a single monitor approach. However, the computational requirements for the embedded dependability manager will increase to enable handling embedded instrument data fusion and/or multi-parameter life-time prediction.
    Original languageEnglish
    Title of host publication2018 IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)
    Pages44-51
    Number of pages8
    ISBN (Electronic)978-1-5386-6689-0
    DOIs
    Publication statusPublished - 2018
    EventIEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip - Vietnam National University, Hanoi, Viet Nam
    Duration: 12 Sep 201814 Sep 2018
    Conference number: 12
    http://mcsoc-forum.org/2018/

    Conference

    ConferenceIEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip
    Abbreviated title MCSoC-2018
    CountryViet Nam
    CityHanoi
    Period12/09/1814/09/18
    Internet address

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    Data fusion
    Nanosystems
    Managers
    Health
    Degradation
    Monitoring
    Testing
    Costs

    Cite this

    Ali, G., Pathrose Vareed, J., & Kerkhoff, H. G. (2018). On‐Chip Lifetime Prediction for Dependable Many‐Processor SoCs based on Data Fusion. In 2018 IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC) (pp. 44-51) https://doi.org/10.1109/MCSoC2018.2018.00019
    Ali, Ghazanfar ; Pathrose Vareed, Jerrin ; Kerkhoff, Hans G. / On‐Chip Lifetime Prediction for Dependable Many‐Processor SoCs based on Data Fusion. 2018 IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC). 2018. pp. 44-51
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    title = "On‐Chip Lifetime Prediction for Dependable Many‐Processor SoCs based on Data Fusion",
    abstract = "The developments in technology and complexity of many-processor Systems-on-Chips emerge at a very rapid pace as is their introduction in safety-critical applications, for instance the transport sector. The inherent decrease in dependability of these complex nanosystems must be compensated by counter measures. One promising approach is the usage of IJTAG-compatible embedded instruments in and around cores, monitoring the {"}health{"} of target processors. It has been anticipated that these instruments will be (primarily) used for reducing the cost of final testing. In case of degradation during life time, however, they can be reused and counteractions like run-time remapping can be carried out. In this paper, the on-line data of two types of embedded instruments will be used for the prognostics, a slack-delay monitor and an IDDX monitor. Their (correlated) data is being fused which enables a more accurate life-time prediction as compared to a single monitor approach. However, the computational requirements for the embedded dependability manager will increase to enable handling embedded instrument data fusion and/or multi-parameter life-time prediction.",
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    Ali, G, Pathrose Vareed, J & Kerkhoff, HG 2018, On‐Chip Lifetime Prediction for Dependable Many‐Processor SoCs based on Data Fusion. in 2018 IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC). pp. 44-51, IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip, Hanoi, Viet Nam, 12/09/18. https://doi.org/10.1109/MCSoC2018.2018.00019

    On‐Chip Lifetime Prediction for Dependable Many‐Processor SoCs based on Data Fusion. / Ali, Ghazanfar ; Pathrose Vareed, Jerrin ; Kerkhoff, Hans G.

    2018 IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC). 2018. p. 44-51.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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    AU - Pathrose Vareed, Jerrin

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    AB - The developments in technology and complexity of many-processor Systems-on-Chips emerge at a very rapid pace as is their introduction in safety-critical applications, for instance the transport sector. The inherent decrease in dependability of these complex nanosystems must be compensated by counter measures. One promising approach is the usage of IJTAG-compatible embedded instruments in and around cores, monitoring the "health" of target processors. It has been anticipated that these instruments will be (primarily) used for reducing the cost of final testing. In case of degradation during life time, however, they can be reused and counteractions like run-time remapping can be carried out. In this paper, the on-line data of two types of embedded instruments will be used for the prognostics, a slack-delay monitor and an IDDX monitor. Their (correlated) data is being fused which enables a more accurate life-time prediction as compared to a single monitor approach. However, the computational requirements for the embedded dependability manager will increase to enable handling embedded instrument data fusion and/or multi-parameter life-time prediction.

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    Ali G, Pathrose Vareed J, Kerkhoff HG. On‐Chip Lifetime Prediction for Dependable Many‐Processor SoCs based on Data Fusion. In 2018 IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC). 2018. p. 44-51 https://doi.org/10.1109/MCSoC2018.2018.00019