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Multi-core systems are adopted quickly in the automotive domain, Proof of concepts have been implemented for power train, body and chassis, involving hard real-time constraints. However, depending on the degree of integration, it can be costly, especially in those cases where existing single-core software has to be migrated over. Furthermore, there seems to be a high level of uncertainty, whether a found solution, with regards to partitioning, mapping and orchestration of software is close to an optimum solution. Some integrated solutions demonstrate considerably less performance, for instance due to communication overhead compared to execution on single-core systems. This paper discusses a methodology, as to how to effectively and efficiently investigate the software architecture design space for multi-core software development.

In recent years, we see more and more ECUs integrating a huge number of application software components. This process mostly results from the increasing amount of so called in-house software in various fields like electric-drive, chassis and driver assistance systems. The software development for these systems is partially moved from the supplier to the car manufacturers. Another important trend is the introduction of new network architectures intending to meet the growing communication requirements. For such ECUs the software integration scenarios become more complicated, as more quality of service requirements with regards to timing, safety and security need to be considered [2]. Multi-core microcontrollers offer even more potential variants for integration scenarios. Understanding the interaction between the different software components, not only from a functional, but also from a timing view, is a key success factor for modern electronic systems [6,7,8,9].

Integration scenarios for ECU software become more complicated, as more constraints with regards to timing, safety and security need to be considered. Multi-core microcontrollers offer even more hardware potential for integration scenarios. To tackle the complexity, more and more model based approaches are used. Understanding the interaction between the different software components, not only from a functional but also from a timing view, is a key success factor for high integration scenarios. In particular for multi-core systems, an amazing amount of timing data can be generated. Usually a multi-core system handles more software functionality than a single-core system. Furthermore, there may be timing interference on the multicore systems, due to the shared usage of buses, memory banks or other hardware resources.