Pacific Time

Thursday 29th



Yervant Zorian (Synopsys), Opening remarks
Mehdi Tahoori (KIT), Program Introduction


Keynote 1

Sudhanva Gurumurthi (AMD)
Heterogeneous Systems Resilience: From Research to Industry Standards


Human Factor break


Technical Session 1

Amit Pandey (Amazon), High Speed IO Access for Test forms the foundation for Silicon Lifecycle Management

Sandeep Bhatia (Google), Functional Testing for HBM and DDR Memories


End of Day 1


Friday 30th


Technical Session 2

Andrea Matteucci, Alex Burlak, Marc Hutner, Nir Server (proteanTecs), GUC’s GLink case study: Performance and reliability monitoring for heterogeneous packaging, combining deep data with machine learning algorithms

Mahta Mayahinia, Mehdi Tahoori (KIT), Gurgen Harutyunyan, Grigor Tshagharyan, Karen Amirkhanyan (Synopsys), An Efficient Test Strategy for Detection of Electromigration Impact in Advanced FinFET Memories

Firooz Massoudi, Ash Patel (Synopsys), Silicon Lifecycle Management optimizes Vmin search enabling efficient & reliable chip operation

Andy Gothard, Richard Oxland (Siemens), Validation and monitoring through the silicon lifecycle: challenges, requirements and solutions




Keynote 2 and Invited Talk 

Subhasish Mitra (Stanford)
A Cambrian Explosion in Electronic System Testing is Dead Ahead

Puneet Gupta (UCLA), Software-Defined Memory Error Correction




Keynote 3 

Patrick Groeneveld (Cerebras Systems)
Extreme Scale Machine Learning Hardware


Technical Session 3

Fadi Kurdahi (UC Irvine), Trust, But Verify: Towards Self-Aware, Safe, Autonomous Self-Driving Systems

Rajesh Gupta (UCSD), Building Computing Machines That Sense, Adapt, and Approximate


Human Factor break


Technical Session 4

Wes Smith (Galaxy Semiconductor), Demonstrating Data Analytics for Sensor Data Processing; An Industrial Use Case

Lee Harrison (Siemens), Securing the connected and autonomous vehicle



Yervant Zorian (Synopsys) and Mehdi Tahoori (KIT), Closing remarks

Keynote 3: Extreme Scale Machine Learning Hardware
Speaker: Patrick Groeneveld

Bio: Patrick Groeneveld currently works at Cerebras Systems, a machine learning hardware startup that makes the world’s first monolithic supercomputer. Before that he worked for many years in the EDA industry. He was Chief Technologist at Magma Design Automation where he was part of the team that developed a groundbreaking RTL-to-GDS2 synthesis product. Patrick was as also a Full Professor of Electrical Engineering at Eindhoven University. He is a lecturer in the EE department at Stanford University and serves as finance chair in the Executive Committee of the Design Automation Conference. Patrick received his MSc and PhD degrees from Delft University of Technology in the Netherlands.