NTPT: On the End-to-End Traffic Prediction in the On-Chip Networks

Power and thermal distribution are critical issues in chip multiprocessors (CMPs). Most previous studies focus on cores and on-chip memory subsystems and discuss how to reduce their power and control thermal distribution by using dynamic voltage/ frequency scaling. However, the on-chip interconnection network, or network-on-chip (NoC), is also an important source of power consumption and heat generation. Particularly, the traffic flowing through the NoC affects directly its power and thermal distribution. Unfortunately, very few works discuss the dynamism of NoC. A key technique for NoC management is to capture its traffic patterns and predict future behaviors. In this paper, we propose a table-driven predictor called Network Traffic Prediction Table (NTPT) for recording and predicting traffic in NoC. The most unique feature of NTPT is its ability to predict end-toend traffic, rather than switch-to-switch traffic. Thus, more application behaviors can be captured and monitored. Evaluations on Tilera's TILE64 show that NTPT has very high prediction accuracy. Analyses also show that it incurs a low area overhead and is very feasible.