Analysis and optimization of prediction-based flow control in networks-on-chip

Networks-on-Chip (NoC) communication architectures have emerged recently as a scalable solution to on-chip communication problems. While the NoC architectures may offer higher bandwidth compared to traditional bus-based communication, their performance can degrade significantly in the absence of effective flow control algorithms. Unfortunately, flow control algorithms developed for macronetworks, either rely on local information, or suffer from large communication overhead and unpredictable delays. Hence, using them in the NoC context is problematic at best. For this reason, we propose a predictive closed-loop flow control mechanism and make the following contributions: First, we develop traffic source and router models specifically targeted to NoCs. Then, we utilize these models to predict the possible congestion in the network. Based on this information, the proposed scheme controls the packet injection rate at traffic sources in order to regulate the total number of packets in the network. We also illustrate the proposed traffic source model and the applicability of the proposed flow controller to actual designs using real NoC implementations. Finally, simulations and experimental study using our FPGA prototype show that the proposed controller delivers a better performance compared to the traditional switch-to-switch flow control algorithms under various real and synthetic traffic patterns.