In this survey, we review several approaches for predicting performance of Network-on-Chip (NoC)-based multicore systems, starting from the traffic models to the complex NoC models for latency evaluation. We first review typical traffic models to represent the application workloads in NoC. Specifically, we review Markovian and non-Markovian (e.g., self-similar or long-range memory-dependent) traffic models and discuss their applications on multicore platform design. Then, we review the analytical techniques to predict NoC performance under given input traffic. We investigate analytical models for average as well as maximum delay evaluation. We also review the developments and design challenges of NoC simulators. One interesting research direction in NoC performance evaluation consists of combining simulation and analytical models in order to exploit their advantages together. Toward this end, we discuss several newly proposed approaches that use hardware-based or learning-based techniques. Finally, we summarize several open problems and our perspective to address these challenges.
['Zhiliang Qian', 'Paul Bogdan', 'Chi-Ying Tsui', 'Radu Marculescu']
Performance Evaluation of NoC-Based Multicore Systems: From Traffic Analysis to NoC Latency Modeling