Prediction-based flow control for network-on-chip traffic

Networks-on-chip (NoC) architectures provide a scalable solution to on-chip communication problem but the bandwidth offered by NoCs can be utilized efficiently only in presence of effective flow control algorithms. Unfortunately, the flow control algorithms published to date 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 cases of 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. Evaluations involving real and synthetic traffic patterns show that the proposed controller delivers a superior performance compared to the traditional switch-to-switch flow control algorithms.