Partitioning Embedded Real-Time Control Software based on Communication Dependencies

Electronic Control Units (ECUs), such as for automotive engine control, execute highly interdependent software units. These software units and their interaction are optimized for single-cores and need to be parallelized for upcoming multi-core processors. In this paper we investigate how to leverage the parallelism of the physical environment for the parallelization of legacy control software. Key for efficient parallelization is the knowledge of the physically required data flow timing which is often more relaxed than the timing of the single-core implementation. As this knowledge is often not documented, a domain expert needs to be involved. We propose an iterative model-based approach that minimizes the evaluation effort of the domain expert when parallelizing. In our case study, using a real-world automotive engine control software, we show that the presented approach can exploit parallelism while guaranteeing a correct data flow timing.