Improving ML-Based Device Modeling Using Variational Autoencoder Techniques

A technical paper titled “Improving Semiconductor Device Modeling for Electronic Design Automation by Machine Learning Techniques” was published by researchers at Commonwealth Scientific and Industrial Research Organisation (CSIRO), Peking University, National University of Singapore, and University of New South Wales. Abstract: "The semiconductors industry benefits greatly from the integ... » read more

Improving Machine Learning-Based Modeling of Semiconductor Devices by Data Self-Augmentation

Abstract: "In the electronics industry, introducing Machine Learning (ML)-based techniques can enhance Technology Computer-Aided Design (TCAD) methods. However, the performance of ML models is highly dependent on their training datasets. Particularly in the semiconductor industry, given the fact that the fabrication process of semiconductor devices is complicated and expensive, it is of grea... » read more

Why Chips Die

Semiconductor devices contain hundreds of millions of transistors operating at extreme temperatures and in hostile environments, so it should come as no surprise that many of these devices fail to operate as expected or have a finite lifetime. Some devices never make it out of the lab and many others die in the fab. It is hoped that most devices released into products will survive until they be... » read more