Adaptive Packet Resizing by Spatial Locality and Data Sharing for Energy-Efficient NOC

Abstract

Single-processor chips have given way to multicore chips to enable a cost-effective implementation of computer systems. Toward continuous performance scaling, Network-On-Chip (NOC) is the communication architecture supporting the core count increase to hundreds or thousands in multicore chips. Low-power, low-latency, and high-bandwidth support in the NOC design is critical for meeting performance and energy targets of the overall system. Much of previous work has focused on improving the NOC design but without more fully taking into consideration the communication characteristics and the interplay with cache memory that can be exploited in the NOC design. In this paper, low spatial locality within cache blocks is exploited in reducing memory traffic toward energy savings in the NOC. We present a spatial locality predictor that separately manages different degrees of spatial locality across shared and private blocks for better prediction accuracy. To further optimize performance and power in the NOC, we present the adaptive control of the predictor and packet data resizing techniques. Evaluations for the 16-core system running PARSEC benchmarks reveal that our spatial-locality based packet resizing improves NOC power consumption on average by 21% (up to 33%).