Restructuring TCAD System: Teaching Traditional TCAD New Tricks

TL;DR

This paper introduces a novel algorithm that restructures traditional TCAD systems to enable real-time 3-D simulation, reduce computational costs, and integrate deep learning effectively.

Contribution

It presents a new algorithm that combines TCAD and deep learning, achieving real-time 3-D simulation and resolving convergence issues.

Findings

Real-time 3-D TCAD simulation achieved

Convergence errors fully resolved

Deep learning and TCAD are effectively integrated

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.