AI Meets Device Modeling: Transforming Compact Modeling With Machine Learning


As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure reliable circuit simulation and design. Correspondingly, these accuracy requirements raise demands on the accuracy and efficiency of device modeling. Modern device models often involve hundreds o... » read more

Rapid Prototyping For Emerging Semiconductor Devices


A technical paper titled “Generating Predictive Models for Emerging Semiconductor Devices” was published by researchers at TU Darmstadt and NaMLab. Abstract: "Circuit design requires fast and scalable models which are compatible to modern electronic design automation tools. For this task typically analytical compact models are preferred. However, for emerging device concepts with altered ... » read more

Data-driven RRAM device models using Kriging interpolation


New technical paper from The George Washington University and NIST with support from DARPA and others. Abstract "A two-tier Kriging interpolation approach is proposed to model jump tables for resistive switches. Originally developed for mining and geostatistics, its locality of the calculation makes this approach particularly powerful for modeling electronic devices with complex behavior la... » read more