Report
Compact Device Models for FinFET and Beyond
| العنوان: | Compact Device Models for FinFET and Beyond |
|---|---|
| المؤلفون: | Lu, Darsen D., Dunga, Mohan V., Niknejad, Ali M., Hu, Chenming, Liang, Fu-Xiang, Hung, Wei-Chen, Lee, Jia-Wei, Hsu, Chun-Hsiang, Chiang, Meng-Hsueh |
| سنة النشر: | 2020 |
| المجموعة: | Computer Science Physics (Other) |
| مصطلحات موضوعية: | Computer Science - Emerging Technologies, Physics - Applied Physics |
| الوصف: | Compact device models play a significant role in connecting device technology and circuit design. BSIM-CMG and BSIM-IMG are industry standard compact models suited for the FinFET and UTBB technologies, respectively. Its surface potential based modeling framework and symmetry preserving properties make them suitable for both analog/RF and digital design. In the era of artificial intelligence / deep learning, compact models further enhanced our ability to explore RRAM and other NVM-based neuromorphic circuits. We have demonstrated simulation of RRAM neuromorphic circuits with Verilog-A based compact model at NCKU. Further abstraction with macromodels is performed to enable larger scale machine learning simulation. Comment: Invited talk at the Asia-Pacific Workshop on Fundamentals and Applications of Advanced Semiconductor Devices (AWAD), Kitakyushu, Japan, July 2018 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2005.02580 |
| رقم الانضمام: | edsarx.2005.02580 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |