CARP:多核混合临界系统的数据通信机制

A. Kaushik, Paulos Tegegn, Zhuanhao Wu, Hiren D. Patel
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引用次数: 13

摘要

本文提出了一种多核混合临界系统(MCS)的可预测的高性能数据通信机制CARP。CARP是作为硬件缓存一致性协议实现的,它支持关键任务和非关键任务之间的通信,同时确保非关键任务不会干扰关键任务的安全需求。CARP的关键新颖之处在于它是临界感知的,因此可以适当地处理关键任务和非关键任务之间的通信模式。我们推导了使用CARP的请求的分析最坏情况延迟界限,并注意到观察到的每个请求延迟都在分析最坏情况延迟界限之内。我们使用合成和SPLASH-2基准将CARP与先前的数据通信机制进行比较。我们的评估表明,与之前的数据通信机制相比,CARP提高了MCS的平均性能,同时保持了关键任务的安全要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CARP: A Data Communication Mechanism for Multi-core Mixed-Criticality Systems
We present CARP, a predictable and high-performance data communication mechanism for multi-core mixed-criticality systems (MCS). CARP is realized as a hardware cache coherence protocol that enables communication between critical and non-critical tasks while ensuring that non-critical tasks do not interfere with the safety requirements of critical tasks. The key novelty of CARP is that it is criticality-aware, and hence, handles communication patterns between critical and non-critical tasks appropriately. We derive the analytical worst-case latency bounds for requests using CARP and note that the observed per-request latencies are within the analytical worst-case latency bounds. We compare CARP against prior data communication mechanisms using synthetic and SPLASH-2 benchmarks. Our evaluation shows that CARP improves the average-case performance of MCS compared to prior data communication mechanisms, while maintaining the safety requirements of critical tasks.
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