容错mpsoc混合关键应用的静态映射

Shin-Haeng Kang, Hoeseok Yang, Sungchan Kim, Iuliana Bacivarov, S. Ha, L. Thiele
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引用次数: 38

摘要

提出了一种用于容错混合临界mpsoc的静态映射优化技术。由于系统强化和混合临界算法带来的不确定性,如动态任务丢弃等,使得这类系统的最坏情况响应时间分析变得困难。我们解决了这一挑战,并提出了一个考虑可靠性和混合临界性问题的最坏情况分析框架。在此基础上,我们建立了一个设计空间探索引擎,优化容错混合临界mpsoc并提供最坏情况保证。我们研究了考虑可能造成一定服务退化的任务丢弃的映射优化问题。广泛的现实生活和合成基准实验证实了所提出的技术的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Static mapping of mixed-critical applications for fault-tolerant MPSoCs
This paper presents a static mapping optimization technique for fault-tolerant mixed-criticality MPSoCs. The uncertainties imposed by system hardening and mixed criticality algorithms, such as dynamic task dropping, make the worst-case response time analysis difficult for such systems. We tackle this challenge and propose a worst-case analysis framework that considers both reliability and mixed-criticality concerns. On top of that, we build up a design space exploration engine that optimizes fault-tolerant mixed-criticality MPSoCs and provides worst-case guarantees. We study the mapping optimization considering judicious task dropping, that may impose a certain service degradation. Extensive experiments with real-life and synthetic benchmarks confirm the effectiveness of the proposed technique.
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