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题名

Fast Machine-Learning-Driven Supply Noise-Aware Macromodeling for High-Speed Nonlinear Drivers

作者
发表日期
2024
DOI
发表期刊
ISSN
1937-4151
卷号PP期号:99
摘要
Emerging domains such as artificial intelligence, 5G mobile and automotive are increasingly reliant on high-speed circuits for efficient processing, in which achieving high operating frequencies and data rates is crucial to enable productive data exchange and rapid responses. High-speed data as well as low noise margin in the high-speed serial links call for efficient models of drivers. In this paper, we propose a fast machine-learning-driven macromodel for high-speed drivers, which can efficiently capture the nonlinear characteristics of drivers considering dynamic supply noise with low model complexity. A decoupling-superposition strategy is employed to effectively calculate the impact of power supply noise. Additionally, we introduce a piecewise-segmented method for macromodel solving to further enhance the speed of model utilization. Experimental results demonstrate that compared to HSPICE, the proposed macromodel achieves up to 50-1200× speedup while maintaining sufficient accuracy, even for signals with GHz data rate.
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成果类型期刊论文
条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/828606
专题南方科技大学
作者单位
1.Zhejiang University, Hangzhou, China
2.Southern University of Science and Technology, Shenzhen, China
推荐引用方式
GB/T 7714
Songyu Sun,Xiao Dong,Qi Sun,et al. Fast Machine-Learning-Driven Supply Noise-Aware Macromodeling for High-Speed Nonlinear Drivers[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems,2024,PP(99).
APA
Songyu Sun,Xiao Dong,Qi Sun,Xunzhao Yin,Quan Chen,&Cheng Zhuo.(2024).Fast Machine-Learning-Driven Supply Noise-Aware Macromodeling for High-Speed Nonlinear Drivers.IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems,PP(99).
MLA
Songyu Sun,et al."Fast Machine-Learning-Driven Supply Noise-Aware Macromodeling for High-Speed Nonlinear Drivers".IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems PP.99(2024).
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