Da Wang
20 Papers
Da Wang is an academic researcher. The author has contributed to research in topics: Computer science. The author has an hindex of 1, co-authored 7 publications.
Chat about Author
Papers
On the Understanding of pMOS NBTI Degradation in Advance Nodes: Characterization, Modeling, and Exploration on the Physical Origin of Defects
Yongkang Xue,Pengpeng Ren,Zhuyou Liu,Shuying Wang,Yu Li,Zirui Wang,Zixuan Sun,Da Wang,Yichen Wen,Shiyu Xia,Lining Zhang,Jian Zhang,Zhi-xin Ji,Junwei Luo,Huixiong Deng,Runsheng Wang,Lianfeng Yang,Ru Huang +17 more
TL;DR: Researchers characterized and modeled four types of traps in 7nm pFinFETs under NBTI stress, identifying their physical origins and proposing a unified aging prediction framework for long-term predictive capability and DTCO in advanced nodes.
9
New Insight into the Aging Induced Retention Time Degraded of Advanced DRAM Technology
Yong Liu,Pengpeng Ren,Da Wang,Longda Zhou,Zhigang Ji,Junhua Liu,Runsheng Wang,Ru Huang +7 more
- 01 Mar 2022
TL;DR: Wang et al. as discussed by the authors designed the accelerated aging test in wafer level and proposed aging leakage model based on Monte Carlo simulation, which predicted data retention time degradation (especially tail distribution) of high-capacity DRAM under long-term operating conditions.
4
Investigation of the Off-State Degradation in Advanced FinFET Technology—Part II: Compact Aging Model and Impact on Circuits
Zixuan Sun,Zirui Wang,Runsheng Wang,Lining Zhang,Jiayang Zhang,Zuodong Zhang,Jiahao Song,Da Wang,Zhigang Ji,Ru Huang +9 more
TL;DR: In this paper , a compact aging model of off-state degradation in advanced FinFETs is developed and validated by silicon data of 7-nm node, including the degradation and recovery phases.
4
Toward Reliability-and Variability-Aware Design-Technology Co-Optimization in Advanced Nodes: Defect Characterization, Industry-Friendly Modeling, and ML-Assisted Prediction
Zhi-xin Ji,Yongkang Xue,Pengpeng Ren,Jinfeng Ye,Yu Li,Yi Shan Wu,Da Wang,Shuying Wang,Junjie Wu,Zirui Wang,Yichen Wen,Shiyu Xia,Lining Zhang,Jian Zhang,Junhua Liu,Junwei Luo,Huixiong Deng,Runsheng Wang,Lianfeng Yang,Ru Huang +19 more
TL;DR: This work tackles issues by developing an efficient characterization method for separating defects, introducing a comprehensive test-data-verified defect-centric physical-based model and an industry-friendly open model interface (OMI)-based compact model, and proposing a machine learning (ML)-assisted approach to accelerate circuit-level prediction.
4
On the Understanding of Defects in Short-Term Negative Bias Temperature Instability (NBTI) for Sub-20-nm DRAM Technology
Da Wang,Longda Zhou,Yongkang Xue,Pengpeng Ren,Zixuan Sun,Zirui Wang,JianPing Wang,Blacksmith Wu,Zhigang Ji,Runsheng Wang,Ru Huang +10 more
TL;DR: In this article , a short-term Negative Bias Temperature Instability (NBTI) was investigated in sub-20-nm DRAM technology by using Variable Amplitude Charge Pumping measurement.
2