An Efficient Partitioning Strategy for Runnables in Weakly Dependent Tasks on Embedded Multi-Core Systems

International audienceWith multi-core controllers entering the area of automotive control ECUs, strategies for parallelizing the control- algorithms come into focus. This paper deals with a special part of automotive powertrain software, called state transitions. Since dependencies between runnables executed there are weak, the transitions provide a good basis for parallelization. We present a strategy of how to distribute efficiently the execution of runnables to different cores while taking care of inner and outer dependencies. The strategy is accompanied by two case studies demonstrating the performance of the concept. The first one is carried out to find the most efficient strategies of parallelize state transitions based on randomly generated, simulated state transitions. In the second one, the developed partitioning strategies are applied to a real software project for an automotive powertrain system