Towards the Derivation of Guidelines for the Deployment of Real-Time Tasks on a Multicore Processor

The deployment of automotive software on a multicore processor includes the task of mapping executables to cores. Given the number of possible solutions, integrators have to solve a complex problem. Considering multiple, often conflicting goals like minimizing task response times and memory consumption, complexity further increased with the advent of multicore processors. We present a model-based approach for deriving design rules supporting integrators with statically mapping tasks to a multicore ECU. First, an evolutionary algorithm is used to sample the design space. For each sample, a model-based analysis is performed, resulting in the required fitness values according to the system metric objectives. Finally, subsets of the sample population are used to derive deployment guidelines by evaluating similarities between highly ranked solutions. This reduces the number of solutions to be considered by the integrators by orders of magnitude. In a case-study, we demonstrate the developed approach on an artificial automotive engine management system.