Abstract-Next generations of compute-intensive real-time applications in automotive systems will require more powerful computing platforms. One promising power-efficient solution for such applications is to use clustered many-core architectures. However, ensuring that real-time requirements are satisfied in the presence of contention in shared resources, such as memories, remains an open issue.This work presents a novel contention-free execution framework to execute automotive applications on such platforms. Privatization of memory banks together with defined access phases to shared memory resources is the backbone of the framework. An Integer Linear Programming (ILP) formulation is presented to find the optimal time-triggered schedule for the on-core execution as well as for the access to shared memory. Additionally a heuristic solution is presented that generates the schedule in a fraction of the time required by the ILP. Extensive evaluations show that the proposed heuristic performs only 0.5% away from the optimal solution while it outperforms a baseline heuristic by 67%. The applicability of the approach to industrially sized problems is demonstrated in a case study of a software for Engine Management Systems.

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The Hierarchical Scheduling Framework (HSF) has been introduced as a design-time framework to enable compositional schedulability analysis of embedded software systems with real-time properties. In this paper, a software system consists of a number of semi-independent components called subsystems. Subsystems are developed independently and later integrated to form a system. To support this design process, in the paper, the proposed methods allow non-intrusive configuration and tuning of subsystem timing-behavior via subsystem interfaces for selecting scheduling parameters. This paper considers three methods to handle overruns due to resource sharing between subsystems in the HSF. For each one of these three overrun methods corresponding scheduling algorithms and associated schedulability analysis are presented together with analysis that shows under what circumstances one or the other is preferred. The analysis is generalized to allow for both Fixed Priority Scheduling (FPS) and Earliest Deadline First (EDF) scheduling. Also, a further contribution of the paper is the technique of calculating resource-holding times within the framework under different scheduling algorithms; the resource holding times being an important parameter in the global schedulability analysis.

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