Repeater Insertion to Reduce Delay and Power in Copper and Carbon Nanotube-Based Nanointerconnects

IEEE Access

Wen-Sheng Zhao¹  Gaofeng Wang¹  Peng-Wei Liu¹  Yue Hu¹  Huan Yu²  Madhavan Swaminathan² 

[1] Key Laboratory of RF Circuits and Systems of Ministry of Education, School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China;School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA;

关键词: Carbon nanotube;    copper;    nanointerconnect;    neural network;    particle swarm optimization;    repeater insertion;   

DOI  :  10.1109/ACCESS.2019.2893960

来源: DOAJ

【 摘 要 】

Optimal repeater designs are performed for Cu and carbon nanotube (CNT)-based nanointerconnects to reduce the delay and power dissipation. The effects of inductance and metal-CNT contact resistance are treated appropriately. In this paper, the circuit parameters are calculated analytically, while they can be extracted experimentally for a specific foundry at a specific technology node. The particle swarm optimization (PSO) technique is employed to numerically calculate the optimal repeater size and the optimal number of repeaters in the Cu and CNT-based nanointerconnects. The results are verified against the analytical and genetic algorithm results. To facilitate CAD design, the machine-learning neural network (NN) is adopted. The data obtained using the PSO algorithm are used to train the NN and the feasibility of the NN is investigated and validated.

【 授权许可】

Unknown