Modern real-time systems consist of a combination of hard real-time, firm real-time and soft real-time tasks. Hard real-time (HRT) tasks mandate strict timing requirements by requiring that a static timing analysis can be performed to compute a worst-case latency (WCL) bound. Firm real-time (FRT) and soft real-time (SRT) tasks, on the other hand, do not impose such stringent requirements. Instead, they tolerate infrequent violations of deadlines in favour of improved average-case performance. When deploying such a system on a multi-core platform, the hardware resources such as the main memory, caches and shared bus are shared between the tasks. This results in interference by FRT or SRT tasks on HRT tasks, which complicates the timing analysis for HRT tasks, and potentially yields unbounded WCL. This thesis presents a time-based cache coherence protocol, HourGlass, to predictably share data in a multi-core system across different criticality tasks. HourGlass is derived from the conventional Modified Shared Invalid (MSI) cache coherence protocol, and it is equipped with a timer mechanism that allows the cores to hold a valid copy of data in its private cache for certain duration. HourGlass is designed to ensure WCL bounds for HRT tasks, and it also provides performance improvements for FRT and SRT tasks. Such a coherence protocol encourages a trade-off between the WCL bounds for hard real-time tasks, and performance offered to firm or soft real-time tasks with the help of timer mechanisms. HourGlass was prototyped in gem5, a micro-architectural simulator, and evaluated with multi-threaded benchmarks.
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Predictable Cache Coherence Protocols for Mixed-Time-Criticality Multi-core Systems
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