Tail Fitting Yield Estimation Method for Resistive Non-Volatile Memory

被引：0
|
作者：
Na, Taehui [1 ,2 ]
Kang, Seung H. [3 ]
Jung, Seong-Ook [4 ]
机构：
[1] Incheon Natl Univ, Dept Elect Engn, Incheon 22012, South Korea
[2] Incheon Natl Univ, Res Inst Engn & Technol, Incheon 22012, South Korea
[3] Qualcomm Technol Inc, San Diego, CA 92121 USA
[4] Yonsei Univ, Dept Elect & Elect Engn, Seoul 03722, South Korea
来源：
2020 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC) | 2020年
关键词：
Monte Carlo; process variation; read yield; resistive non-volatile memory; tail fitting; yield estimation;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper demonstrates that the read output voltage difference between data and reference voltages in a resistive non-volatile memory is not a Gaussian distribution but composed of two Gaussian distributions. In addition, a tail fitting method is proposed to estimate a read yield with high accuracy. Monte Carlo HSPICE simulation results based on industrycompatible 45-nm model parameters show that the proposed tail fitting method improves accuracy by 5.2x and 2.5x compared to the normal fitting and the importance sampling methods, respectively.
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页数：2
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