Traditional TCAD simulation has succeeded in predicting and optimizing the device performance; however, it still faces a massive challenge - a high computational cost. There have been many attempts to replace TCAD with deep learning, but it has not yet been completely replaced. This paper presents a novel algorithm restructuring the traditional TCAD system. The proposed algorithm predicts three-dimensional (3-D) TCAD simulation in real-time while capturing a variance, enables deep learning and TCAD to complement each other, and fully resolves convergence errors.
@article{arxiv.2204.09578,
title = {Restructuring TCAD System: Teaching Traditional TCAD New Tricks},
author = {Sanghoon Myung and Wonik Jang and Seonghoon Jin and Jae Myung Choe and Changwook Jeong and Dae Sin Kim},
journal= {arXiv preprint arXiv:2204.09578},
year = {2022}
}
Comments
In Proceedings of 2021 IEEE International Electron Devices Meeting (IEDM)