mccormick.northwestern.edu

New Machine Learning Framework Enables Data-Efficient Design of Advanced Metamaterials

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
Semiconductor Engineering

Machine Learning Tools Help Bridge Design-To-Manufacturing Gap

More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...
EurekAlert!

Beyond small data limitations: Transfer learning-enabled framework for predicting mechanical properties of aluminum matrix composites

A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences (CAS), has developed an innovative machine learning framework ...
Semiconductor Engineering

Applying Machine Learning to EDA, FPGA Design Automation Tools

A technical paper titled “Application of Machine Learning in FPGA EDA Tool Development” was published by researchers at the University of Texas Dallas. “With the recent advances in hardware ...
EurekAlert!

Chip design with machine learning: a survey from algorithm perspective

This paper comprehensively surveys existing works of chip design with ML algorithms from an algorithm perspective. To accomplish this goal, the authors propose a novel and systematical taxonomy for ...