Restructuring TCAD System: Teaching Traditional TCAD New Tricks

Autor:	Sanghoon Myung, Wonik Jang, Seonghoon Jin, Jae Myung Choe, Changwook Jeong, Dae Sin Kim
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	Computer Science - Machine Learning Hardware_INTEGRATEDCIRCUITS Hardware_PERFORMANCEANDRELIABILITY Electrical Engineering and Systems Science - Signal Processing Statistics - Applications
Popis:	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. Comment: In Proceedings of 2021 IEEE International Electron Devices Meeting (IEDM)
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60743a1b36d51d64472e1830c12f14c8 http://arxiv.org/abs/2204.09578 Zobrazit plný text záznamu