CISE Seminar: Jiang Hu, Texas A&M University

Date: Friday, October 27, 2023
Time: 3:00pm – 4:00pm
Location: 665 Commonwealth Avenue, CDS 548

Professor Jiang Hu, Texas A&M University

Jiang Hu
Professor, Department of Electrical and Computer Engineering
Texas A&M University

Machine Learning for Chip Design and Design Automation for Machine Learning Chips
Machine learning provides a promising approach to chip design predictions, which play a critical role in expediting design turnaround time. Nevertheless, the non-determinism of certain design automation software introduces variability in data labels, posing a substantial hurdle to effective ML model training. In the first part of this talk, we will delve into the utilization of CNNs for predicting design rule violations, along with a stochastic technique to mitigate the challenges stemming from noisy data labels generated by parallel routers. The growing demand for CNN computation necessitates the development of specialized CNN hardware accelerators. In the second part, the talk will be focused on the co-optimization of CNN hardware architecture and dataflow mapping—an intricate problem characterized by an extensive discrete solution space. We will introduce an innovative analytical approach, making a significant advancement over current state-of-the-art methods in improving inference speed and reducing power consumption as well as computational cost.

Jiang Hu is a professor in the Department of Electrical and Computer Engineering at Texas A&M University. His research interests include electronic design automation, approximate computing and machine learning for chip designs. He has co-authored more than 250 technical papers, co-invented 10 patents and co-edited a book. He received best paper awards at DAC 2001, ICCAD 2011, IEEE International Conference on Vehicular Electronics and Safety 2018, MICRO 2021 and ASPDAC 2023. He served as the technical program chair and general chair of the ACM International Symposium on Physical Design in 2011 and 2012, respectively. He was named an IEEE fellow in 2016. He is the technical program co-chair for the ACM/IEEE Workshop on Machine Learning CAD 2023. 

Faculty Host: Wenchao Li
Student Host: Akua Kodie Dickson