Dietrich, ChristianChristianDietrichLohmann, DanielDanielLohmann2021-04-122021-04-122018IEEE Real-Time Systems Symposium 2018http://hdl.handle.net/11420/9255Memory is an expensive and, therefore, limited resource in deeply embedded real-time systems. Thread stacks substantially contribute to the RAM requirements. To reduce the system's worst-case stack consumption (WCSC), it is state of the art to exploit thread-level preemption constraints to let multiple threads share the same stack. However, deriving a tight, yet correct bound for the shared stack is a difficult undertaking and stack sharing is currently restricted to run-to-completion threads, which are preemptable, but cannot block (i.e., passively wait for an event) at run time. With semi-extended tasks (SETs), we propose a solution for efficient stack sharing among blocking and non-blocking threads on the system level. For this, we refine the stack-sharing granularity from the thread to function level. We provide an efficient intra-thread stack-switch mechanism and an ILP-based WCSC analysis that considers fine-grained preemption constraints and possible function-level switching points from the private to the shared stack. A genetic algorithm then selects switching points that lead to the reduction of the overall WCSC. Compared to systems that run only non-blocking threads on the shared stack, semi-extended tasks decrease the WCSC in our benchmarks on average by 7 percent and up to 52 percent for some systems.enConference Paper10.1109/RTSS.2018.00049Altmeyer, SebastianSebastianAltmeyerOther