As the demand for computing power is quickly increasing in the automotive domain, car manufacturers and tier-one suppliers are gradually introducing multicore ECUs in their electronic architectures. In this paper we address the general problem of scheduling numerous elementary software components (called runnables) on a limited set of identical cores. In the context of an automotive design, we assume the use of the static task partitioning scheme which provides simplicity and better predictability for the ECU designers with respect to a global scheduling approach. We show how the global scheduling problem can be addressed as two sub-problems: partitioning the set of runnables and building the schedule on each core. Then, we prove that each of the sub-problems cannot be solved optimally due to their algorithmic complexity. We then present low complexity heuristics and derive lower bounds on their efficiency (i.e., competitive ratio). Finally, we assess the performance of our approach on realistic case-studies.