A holistic approach towards intelligent hotspot prevention in network-on-chip-based multicores

Vassos Soteriou Soteriou, Theocharis Theocharides, Elena Kakoulli

    Research output: Contribution to journalArticle

    Abstract

    Traffic hotspots, a severe form of network congestion, can be caused unexpectedly in a network-on-chip (NoC) due to the immanent spatio-temporal unevenness of application traffic. Hotspots reduce the NoC's effective throughput, where in the worst-case scenario, network traffic flows can be frozen indefinitely. To alleviate this problematic phenomenon several adaptive routing algorithms employ online load-balancing schemes, aiming to reduce the possibility of hotspots arising. Since most are not explicitly hotspot-agnostic, they cannot completely prevent hotspot formation(s) as their reactive capability to hotspots is merely passive. This paper presents a pro-active Hotspot-Preventive Routing Algorithm (HPRA) which uses the advance knowledge gained from network-embedded artificial neural network-based (ANN) hotspot predictors to guide packet routing in mitigating any unforeseen near-future hotspot occurrences. First, these ANN-based predictors are trained offline and during multicore operation they gather online statistical data to predict about-to-be-formed hotspots, promptly informing HPRA to take appropriate hotspot-preventive action(s). Next, in a holistic approach, additional ANN training is performed with data acquired after HPRA interferes, so as to further improve hotspot prediction accuracy; hence, the ANN mechanism does not only predict hotspots, but is also aware of changes that HPRA imposes upon the interconnect infrastructure. Evaluation results, including utilizing real application traffic traces gathered from parallelized workload executions onto a chip multiprocessor architecture, show that HPRA can improve network throughput up to 81 percent when compared with prior-art. Hardware synthesis results affirm the HPRA mechanism's moderate overhead requisites.

    Original languageEnglish (US)
    Article number7110592
    Pages (from-to)819-833
    Number of pages15
    JournalIEEE Transactions on Computers
    Volume65
    Issue number3
    DOIs
    StatePublished - Mar 1 2016

    Fingerprint

    Routing algorithms
    Hot Spot
    Routing Algorithm
    Neural networks
    Throughput
    Artificial Neural Network
    Adaptive algorithms
    Network on chip
    Network-on-chip
    Resource allocation
    Traffic
    Predictors
    Hardware
    Packet Routing
    Adaptive Routing
    Predict
    Chip multiprocessors
    Network Flow
    Network Traffic
    Interconnect

    Keywords

    • Multiprocessor interconnection
    • neural network hardware
    • on-chip network
    • ultra-scale integration

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Software
    • Hardware and Architecture
    • Computational Theory and Mathematics

    Cite this

    A holistic approach towards intelligent hotspot prevention in network-on-chip-based multicores. / Soteriou, Vassos Soteriou; Theocharides, Theocharis; Kakoulli, Elena.

    In: IEEE Transactions on Computers, Vol. 65, No. 3, 7110592, 01.03.2016, p. 819-833.

    Research output: Contribution to journalArticle

    Soteriou, Vassos Soteriou ; Theocharides, Theocharis ; Kakoulli, Elena. / A holistic approach towards intelligent hotspot prevention in network-on-chip-based multicores. In: IEEE Transactions on Computers. 2016 ; Vol. 65, No. 3. pp. 819-833.
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