Predicting Vt variation and static IR drop of ring oscillators using model-fitting techniques

Tzu Hsuan Huang, Wei Tse Hung, Hao Yu Yang, Wen Hsiang Chang, Ying Yen Chen, Chun Yi Kuo, Jih Nung Lee, Chia-Tso Chao

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

This paper presents a statistical model-fitting framework to efficiently decompose the impact of device Vt variation and power-network IR drop from the measured ring-oscillator frequencies without adding any extra circuitry to the original ring oscillators. The framework applies Gaussian process regression as its core model-fitting technique and stepwise regression as a pre-process to select significant predictor features. The experiments conducted based on the SPICE simulation of an industrial 28nm technology demonstrate that our framework can simultaneously predict the NMOS Vt, PMOS Vt and static IR drop of the ring oscillators based on their frequencies measured at different external supply voltages. The final resulting R squares of the predicted features are all more than 99.93%.

原文English
主出版物標題2017 22nd Asia and South Pacific Design Automation Conference, ASP-DAC 2017
發行者Institute of Electrical and Electronics Engineers Inc.
頁面426-431
頁數6
ISBN(電子)9781509015580
DOIs
出版狀態Published - 16 2月 2017
事件22nd Asia and South Pacific Design Automation Conference, ASP-DAC 2017 - Chiba, Japan
持續時間: 16 1月 201719 1月 2017

出版系列

名字Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC

Conference

Conference22nd Asia and South Pacific Design Automation Conference, ASP-DAC 2017
國家/地區Japan
城市Chiba
期間16/01/1719/01/17

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