Improving DVFS in NoCs with Coherence Prediction

Abstract

As Networks-on-Chip (NoCs) continue to consume a large fraction of the total chip power budget, dynamic voltage and frequency scaling (DVFS) has evolved into an integral part of NoC designs. Efficient DVFS relies on accurate predictions of future network state. Most previous approaches are reactive and based on network-centric metrics, such as buffer occupation and channel utilization. However, we find that there is little correlation between those metrics and subsequent NoC traffic, which leads to suboptimal DVFS decisions. In this work, we propose to utilize highly predictable properties of cache-coherence communication to derive more specific and reliable NoC traffic predictions. A DVFS mechanism based on our traffic predictions, reduces power by 41% compared to a baseline without DVFS and by 21% on average when compared to a state-of-the-art DVFS implementation, while only degrading performance by 3%.