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A variety of methodologies to use embedded multicore controllers efficiently has been discussed in the last years. Several assumptions are usually made in the automotive domain, such as static assignment of tasks to the cores. This paper shows an approach for efficient task allocation depending on different system modes. An engine management system (EMS) is used as application example, and the performance improvement compared to static allocation is assessed. The paper is structured as follows: First the control algorithms for the EMS will be classified according to operating modes. The classified algorithms will be allocated to the cores, depending on the operating mode. We identify mode transition points, allowing a reliable switch without neglecting timing requirements. As a next step, it will be shown that a load distribution by mode-dependent task allocation would be better balanced than a static task allocation.

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.

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].