Sponsor: Orange County Section Chapter,EP21
Speaker: Dr. Boris Vaisband

Date: 25 Sep 2025
Time: 06:00 PM PDT to 08:00 PM PDT

Cost:
Location: Irvine, California
Reservations: IEEE
Summary:
The demand for computation and memory in applications such as large language models, has increased well beyond the reticle boundaries of a system-on-chip (SoC). Chiplet-based integration is a paradigm shift that shapes the way we design our future high-performance systems. The concept is to move away from large SoCs that are limited by communication, thermal design power, and reticle size, toward a robust plug-and-play approach, where small, hardened IP heterogeneous off-the-shelf chiplets are seamlessly integrated on a single platform. In this talk, we will discuss the current state-of-the-art and challenges in chiplet integration and introduce the silicon interconnect fabric (Si-IF), an ultra-large wafer-scale heterogeneous integration platform, for applications such as artificial intelligence acceleration, high-performance computing, and neuromorphic hardware, will be discussed.

Bio: Boris Vaisband (Senior Member, IEEE) is the Samueli Development Chair Assistant Professor at the University of California, Irvine, working on heterogeneous systems integration. In 2024 he was the Acting Director of UCLA CHIPS, and from 2019 to 2024, an Assistant Professor at McGill University. He received a B.S. degree in Computer Engineering from the Technion – Israel Institute of Technology in 2011, and M.S. and Ph.D. degrees in Electrical Engineering from the University of Rochester, NY, in, respectively, 2012 and 2017. From 2017 to 2019, he was a Postdoctoral Scholar at UCLA. From 2008 to 2015, he held various hardware design positions at Intel, Cisco, and Google. His current research interests are in heterogeneous integration, advanced packaging, and neuromorphic systems, with a focus on circuits, EDA tools, and design methodologies for power delivery, communication, thermal aware design and floorplanning, and testing. Some applications of interest are ultra-large-scale artificial intelligence systems and high performance computing.