Work in Progress: ACAC: An Adaptive Congestion-aware Approximate Communication Mechanism for Network-on-Chip Systems

Abstract

Data-intensive applications, such as machine learning and pattern recognition, result in heavy Network-on-Chip (NoC) communication loads and a tremendous increase in the communication latency. At the same time, the error-tolerant nature of these applications makes approximate communication an effective way to relieve the sharp increase of the network latency. This paper proposes an adaptive congestion-aware approximate communication mechanism (ACAC) that can alleviate the communication congestion of NoC systems in heavy communication loads. Our cycle-accurate simulations have shown that the proposed ACAC effectively reduces the network latency similar to ABDTR under a 22% to 52% lower data approximate ratio and significantly decreases the additional compression control traffic volume under real applications.