Mainstream electronic designs are realized by Systems-on-Chips (SoCs) that push the limits of integration. The advancement of manufacturing technologies in terms of integration leads us to SoCs with many (e.g., 10-1000) digital units (e.g., processor cores, controllers, storage, application-specific units) that need to be interconnected in an efficient and reliable way. The Network-on-Chip (NoC) design paradigm emerged recently as a promising alternative to classical bus-based communication architectures. Aside from better predictability and lower power consumption, the NoC approach offers greater scalability compared to previous solutions for on-chip communication. The design flow of NoCs include several key issues. Among other parameters, the decision of where cores have to be topologically mapped and also the routing algorithm represent two highly correlated design problems that must be carefully solved for any given application in order to optimize different performance metrics. The strong correlation between the different parameters often makes that the optimization of a given performance metric has a negative effect on a different performance metric. In this paper we propose a new strategy that simultaneously refines the mapping and the routing function to determine the Pareto optimal configurations which optimize average communication delay and routing robustness. The proposed strategy has been applied on both synthetic and real traffic scenarios. The obtained results show how the solutions found by the proposed approach outperforms those provided by other approaches proposed in literature, in terms of both performance and fault tolerance.

networks-on-chip, topological mapping, multi-objective optimization, routing algorithm, genetic algorithm, fault-tolerance, performance analysis