Online Fault Detection for Networks-on-Chip Interconnect

Junxiu Liu, Jim Harkin, Yuhua Li, Liam Maguire

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

A key requirement for modern Networks-on-Chip (NoC) is the ability to detect and diagnose faults and failures. A novel approach is proposed which addresses the challenge of fault detection using an online mechanism. The approach minimises online intrusion by employing dynamic rates of testing to maximize NoC throughput while still ensuring sufficient testing. This is achieved using a novel Monitor Module based on the back-off algorithm. The paper presents results on the minimal impact on the intrusion of the NoC for a range of test conditions and also highlights the low area/power overheads for scalability.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages8
Publication statusPublished - 17 Jul 2014
EventNASA/ESA Conference on Adaptive Hardware and Systems (AHS-2014) - Leicester, UK
Duration: 17 Jul 2014 → …

Conference

ConferenceNASA/ESA Conference on Adaptive Hardware and Systems (AHS-2014)
Period17/07/14 → …

Fingerprint

Fault detection
Testing
Failure analysis
Scalability
Throughput
Network-on-chip

Keywords

  • Networks-on-Chip
  • Fault detection
  • Online testing
  • Low area/power overhead

Cite this

Liu, Junxiu ; Harkin, Jim ; Li, Yuhua ; Maguire, Liam. / Online Fault Detection for Networks-on-Chip Interconnect. Unknown Host Publication. 2014.
@inproceedings{d5bf609193b9478e8f78bb7b006e0f66,
title = "Online Fault Detection for Networks-on-Chip Interconnect",
abstract = "A key requirement for modern Networks-on-Chip (NoC) is the ability to detect and diagnose faults and failures. A novel approach is proposed which addresses the challenge of fault detection using an online mechanism. The approach minimises online intrusion by employing dynamic rates of testing to maximize NoC throughput while still ensuring sufficient testing. This is achieved using a novel Monitor Module based on the back-off algorithm. The paper presents results on the minimal impact on the intrusion of the NoC for a range of test conditions and also highlights the low area/power overheads for scalability.",
keywords = "Networks-on-Chip, Fault detection, Online testing, Low area/power overhead",
author = "Junxiu Liu and Jim Harkin and Yuhua Li and Liam Maguire",
year = "2014",
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}

Liu, J, Harkin, J, Li, Y & Maguire, L 2014, Online Fault Detection for Networks-on-Chip Interconnect. in Unknown Host Publication. NASA/ESA Conference on Adaptive Hardware and Systems (AHS-2014), 17/07/14.

Online Fault Detection for Networks-on-Chip Interconnect. / Liu, Junxiu; Harkin, Jim; Li, Yuhua; Maguire, Liam.

Unknown Host Publication. 2014.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Maguire, Liam

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N2 - A key requirement for modern Networks-on-Chip (NoC) is the ability to detect and diagnose faults and failures. A novel approach is proposed which addresses the challenge of fault detection using an online mechanism. The approach minimises online intrusion by employing dynamic rates of testing to maximize NoC throughput while still ensuring sufficient testing. This is achieved using a novel Monitor Module based on the back-off algorithm. The paper presents results on the minimal impact on the intrusion of the NoC for a range of test conditions and also highlights the low area/power overheads for scalability.

AB - A key requirement for modern Networks-on-Chip (NoC) is the ability to detect and diagnose faults and failures. A novel approach is proposed which addresses the challenge of fault detection using an online mechanism. The approach minimises online intrusion by employing dynamic rates of testing to maximize NoC throughput while still ensuring sufficient testing. This is achieved using a novel Monitor Module based on the back-off algorithm. The paper presents results on the minimal impact on the intrusion of the NoC for a range of test conditions and also highlights the low area/power overheads for scalability.

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KW - Online testing

KW - Low area/power overhead

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