Although the manual creation of time-triggered schedules for multi-core real-time systems can be a daunting task, state-of-the-art scheduling algorithms are far from being widely used. This suggests that the availability of sound algorithms is only one side of the story: real-time systems have to be groomed substantially before they can serve as input to available algorithms. Moreover, systems engineers struggle with the temporal effects of their design decisions, in addition to the intended timing properties. Therefore, we believe that appropriate tools are the other side of the story. In this paper, we present the multicore extension of the Real-Time Systems Compiler, a compiler-based tool that analyses given event-triggered real-time systems and transforms them into time-triggered equivalents. We focus on the challenges and pitfalls in the transition from theory to practical implementation and present concrete solutions to resolve them. Existing algorithms need to be adapted for performance and, at model level, bound together appropriately to be applicable, for example. Our experiments substantiate the effectiveness and scalability of our approach, even for large tasks sets. Finally, lessons learned give an insight into implementation and hardware details and their impact on schedulability.

This paper proposes a continuous toolchain from the original control system model to the resulting schedules. As a first step towards control-aware yet adaptive system design, we focused on a global, context-sensitive analysis of control and data flow across control-application layers and threads of execution. This step is of vital importance as these dependencies manifest differently on the various levels of abstraction. Consequently, we extract semantics and internal dependencies directly from control-system models by an extended version of the Real-Time Systems Compiler (RTSC), which is capable of analyzing and transforming real-time applications on the source code level.