An Application Mapping Algorithm for Mesh-Based Hybrid Optical Network-on-Chip Architecture

Hybrid Optical Network-on-Chip (HONoC) recently emerged as a compelling solution for handling future communication needs in the many-core System-on-Chip (SoC). However, designing a HONoC poses a number of challenges that do not exist in the electronic realm, particularly crosstalk noise, which affects signal-to-noise ratios (SNR). As a result, it affects network scalability and power consumption. In this paper, we have used the Kernighan-Lin (KL) based application mapping technique to optimize the SNR. We have compared our proposed method with State-of-the-art (SOTA) methods, including the Reinforcement Learning (RL) based technique. Experimental results indicate improved performance compared to SOTA methods, in terms of maximizing SNR and throughput, highlighting the potential of our approach to enhance the efficiency of these synthesized network architectures.