Abstract
Optical interconnect is a disruptive technology solution that can overcome the power and bandwidth limitations of traditional electrical Networks-on-Chip (NoCs). However, the static power dissipated in the external laser may limit the performance of future optical NoCs by dominating the stringent network power budget. From the analysis of real benchmarks for multicores, it is observed that high static power is consumed due to the external laser even for low channel utilization. In this paper, we propose PROBE, Prediction-based Optical Bandwidth Scaling for Energy-efficient NoCs by exploiting the latency/bandwidth trade-off to reduce the static power consumption by increasing the average channel utilization. With a lightweight prediction technique, we scale the bandwidth adaptively to the changing traffic demands while maintaining reasonable performance. The performance on synthetic and real traffic (PARSEC, Splash2) for 64-cores indicate that our proposed bandwidth scaling technique can reduce optical power by about 60% with at most 11% throughput penalty.
Li Zhou
Senior Machine Learning Engineer
My research interests lie in the broad area of computer architecture/system, large-scale graph processing, distributed machine learning, and security.