Multi-core technology is recognized as a key component to develop new cost-efficient products. It can lead to reduction of the overall hardware cost through hardware consolidation. However, it also results in tremendous challenges related to the combination of predictability and performance. The AUTOSAR consortium has developed as the worldwide standard for automotive embedded software systems. One of the prominent aspects of this consortium is to support multi-core systems. In this paper, the ongoing work on addressing the challenge of achieving a resource efficient and predictable mapping of AUTOSAR runnables onto a multi-core system is discussed. The goal is to minimize the runnables' communication cost besides meeting timing and precedence constraints of the runnables. The basic notion utilized in this research is to consider runnable granularity, which leads to an increased flexibility in allocating runnables to various cores, compared of task granularity in which all of the runnables hosted on a task should be allocated on the same core. This increased flexibility can potentially enhance communication cost. In addition, a heuristic algorithm is introduced to create a task set according to the mapping of runnables on the cores. In our current work, we are formulating the problem as an Integer Linear Programming (ILP). Therefore, conventional ILP solvers can be easily applied to derive a solution.