Zheng Yan-Li, Song Ting-Ting, Chai Jun-Xiong, Yang Xiao-Ping, Yu Meng-Meng, Zhu Yun-Chao, Liu Yong, Xie Yi-Yuan
School of Electronic and Information Engineering, Southwest University, Chongqing 400715, China.
School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu 611731, China.
Micromachines (Basel). 2021 Jan 5;12(1):54. doi: 10.3390/mi12010054.
The photoelectric hybrid network has been proposed to achieve the ultrahigh bandwidth, lower delay, and less power consumption for chip multiprocessor (CMP) systems. However, a large number of optical elements used in optical networks-on-chip (ONoCs) generate high transmission loss which will influence network performance severely and increase power consumption. In this paper, the Dijkstra algorithm is adopted to realize adaptive routing with minimum transmission loss of link and reduce the output power of the link transmitter in mesh-based ONoCs. The numerical simulation results demonstrate that the transmission loss of a link in optimized power control based on the Dijkstra algorithm could be maximally reduced compared with traditional power control based on the dimensional routing algorithm. Additionally, it has a greater advantage in saving the average output power of optical transmitter compared to the adaptive power control in previous studies, while the network size expands. With the aid of simulation software OPNET, the network performance simulations in an optimized network revealed that the end-to-end (ETE) latency and throughput are not vastly reduced in regard to a traditional network. Hence, the optimized power control proposed in this paper can greatly reduce the power consumption of s network without having a big impact on network performance.
光电混合网络已被提出用于实现芯片多处理器（CMP）系统的超高带宽、更低延迟和更低功耗。然而，片上光网络（ONoC）中使用的大量光学元件会产生高传输损耗，这将严重影响网络性能并增加功耗。本文采用迪杰斯特拉算法在基于网格的片上光网络中实现具有最小链路传输损耗的自适应路由，并降低链路发射机的输出功率。数值模拟结果表明，与基于维度路由算法的传统功率控制相比，基于迪杰斯特拉算法的优化功率控制中链路的传输损耗可最大程度降低。此外，与先前研究中的自适应功率控制相比，在网络规模扩大时，它在节省光发射机平均输出功率方面具有更大优势。借助仿真软件OPNET，在优化网络中的网络性能仿真表明，与传统网络相比，端到端（ETE）延迟和吞吐量并没有大幅降低。因此，本文提出的优化功率控制可以在不对网络性能产生重大影响的情况下，极大地降低网络的功耗。
