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A high-resilience imprecise computing architecture for mixed-criticality systems
University of York, United Kingdom.
University of York, United Kingdom.
University of York, United Kingdom.
City, University of London, United Kingdom.
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2023 (English)In: IEEE Transactions on Computers, ISSN 0018-9340, E-ISSN 1557-9956, Vol. 72, no 1, p. 29-42Article in journal (Refereed) Published
Abstract [en]

Conventional mixed-criticality systems (MCS)s are designed to terminate the execution of less critical tasks in exceptional situations so that the timing properties of more critical tasks can be preserved. Such a strategy can be controversial and has proven difficult to implement in practice, as it can lead to hazards and reduced functionality due to the absence of the discarded tasks. To mitigate this issue, the imprecise mixed-critically system model (IMCS) has been proposed. In such a model, instead of completely dropping less-critical tasks, these tasks are executed as much as possible through the use of decreased computation precision. Although IMCS could effectively improve the survivability of the less-critical tasks, it also introduces three key drawbacks - run-time computation errors, real-time performance degradation, and lack of flexibility. In this paper, we present a novel IMCS framework, which can (i) mitigate the computation errors caused by imprecise computation; (ii) achieve real-time performance near to that of a conventional MCS; (iii) enhance system-level throughput; and (iv) provide flexibility for run-time configuration. We describe the design details of HIART-MCS, and then present the corresponding theoretical analysis and optimisation method for its run-time configuration. Finally, HIART-MCS is evaluated against other MCS frameworks using a variety of experimental metrics.

Place, publisher, year, edition, pages
IEEE, 2023. Vol. 72, no 1, p. 29-42
Keywords [en]
Clocks, Computational modeling, Hardware, Hardware/Software Co-design, Imprecise Computing, Real-Time Mixed-Criticality Systems, Registers, Schedulability Analysis, Software, Task analysis, Timing
National Category
Computer Sciences Computer Engineering
Identifiers
URN: urn:nbn:se:umu:diva-199468DOI: 10.1109/TC.2022.3202721ISI: 000899952600004Scopus ID: 2-s2.0-85137584727OAI: oai:DiVA.org:umu-199468DiVA, id: diva2:1698662
Available from: 2022-09-26 Created: 2022-09-26 Last updated: 2023-09-05Bibliographically approved

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Gu, Zonghua

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