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arXiv · 2204.09578

Restructuring TCAD System: Teaching Traditional TCAD New Tricks

Sanghoon Myung·Wonik Jang·Seonghoon Jin·Jae Myung Choe·Changwook Jeong·Dae Sin Kim
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Abstract

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.

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Sanghoon Myung, Wonik Jang, Seonghoon Jin, Jae Myung Choe, Changwook Jeong, Dae Sin Kim. 2022-04-19. Restructuring TCAD System: Teaching Traditional TCAD New Tricks. https://doi.org/10.1109/iedm19574.2021.9720616

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