Application driven traffic modeling for NoCs

The network on chip (NoC) design process requires an adequate characterization of the application running on it to optimize communication resources utilization and dimensioning. The traffic modeling process is the most essential step for characterizing complex applications. It is possible to identify three methods to model traffic in NoC literature. The first one assumes sources continually send data at a constant rate to the network and it is the most commonly used. The second method employs probabilistic functions to model the traffic behavior for typical applications, as audio and video streams. The accuracy of this method is better, at the extra cost of modeling complexity and simulation time. The third method employs traffic traces to evaluate network performance. Even with small traces, simulation time can be prohibitive. The advantage is accuracy, superior to the previous models. Even if a given application is correctly modeled, other flows interfere on how the application traffic behaves within the network. Results about the mutual interference of different traffic flows in NoCs are scarce. This work has two main objectives: (i) compare NoC performance, in terms of throughput and latency, when different traffic models are used for the same application; (ii) evaluate the impact of network noise traffic on some specific modeled flow. Preliminary results show how far is the real NoC performance for a given application when an oversimplified model is employed. The conclusion is that NoCs must employ internal mechanisms to ensure QoS, since noise traffic makes modeled traffic to depart from its predicted behavior.