https://scholars.lib.ntu.edu.tw/handle/123456789/607011
標題: | Minimum Operating Voltage Prediction in Production Test Using Accumulative Learning | 作者: | CHIEN-MO LI Kuo Y.-T Lin W.-C Chen C Hsieh C.-H Li J.C.-M Jia-Wei Fang E Hsueh S.S.-Y. CHIEN-MO LI |
關鍵字: | Chip Performance Prediction;Machine Learning;Process variation;Machine learning;Chip performance;Chip performance prediction;Key feature;Machine-learning;Minimum operating voltages (Vmin);Operating voltage;Performance prediction;Process Variation;Production test;Voltage prediction;Forecasting | 公開日期: | 2021 | 起(迄)頁: | 47-52 | 來源出版物: | Proceedings - International Test Conference | 摘要: | We propose a new methodology to predict minimum operating voltage (Vmin) for production chips. In addition, we propose two new key features to improve the prediction accuracy. Our proposed accumulative learning can reduce the impact of lot-to-lot variations. Experimental results on two 7nm industry designs (about 1.2M chips from 142 lots) show that we can achieve above 95% good prediction. Our methodology can save 75% test time compared with traditional testing. To implement this method, we will need to have a separate test flow for the initial training and accumulative training. ? 2021 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123054369&doi=10.1109%2fITC50571.2021.00012&partnerID=40&md5=3e6dffb9d18703e5973fd632343dd15b https://scholars.lib.ntu.edu.tw/handle/123456789/607011 |
ISSN: | 10893539 | DOI: | 10.1109/ITC50571.2021.00012 |
顯示於: | 電機工程學系 |
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