Pierre Paulin

Synopsys, Canada

Generative AI on the Edge

Abstract

In this talk, we explore the emerging trends in generative AI and the role of transformer-based neural networks at their core. We investigate the distinct attributes of transformers and how they diverge from conventional convolutional neural networks (CNNs). The talk underscores that CNN-optimized accelerators do not effectively scale for transformers. We discuss key requirements for emerging Neural Processing Units (NPU) to support Transformers and Generative AI constructs.  We use transformer-based vision models, text-to-image, and large language model generative AI examples to illustrate the requirements for efficient mapping onto an NPU.

Biography

Dr. Pierre G. Paulin is Executive Director of R&D for Embedded AI and Vision Processors at Synopsys. He is responsible for the system architecture group, with cross-functional responsibilities covering AI innovation trends, system architecture design and S/W programming tools for the Synopsys embedded Neural Processing Units (NPUs).

Prior to this, he was director of System-on-Chip Platform Automation at STMicroelectronics in Canada, working on platform programming tools for multi-processor systems-on-a-chip, targeting computer vision, video codecs and network processors.

This followed his previous positions as director of Embedded Systems Technologies for STMicroelectronics in Grenoble, France, and manager of Embedded Software and High-level synthesis tools with Nortel Networks in Canada. His interests include AI, embedded vision, video processing, multi-processor systems, and system-level design.

He obtained a Ph.D. from Carleton University, Ottawa, and B.Sc. and M.Sc. degrees from Laval University, Quebec. He won the best paper award at ISSS-Codes in 2004. He is a member of the IEEE.