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Webinar: FPGAs for AI and AI for FPGAs
August 17, 2022 @ 10:00 AM - 11:00 AM
Artificial Intelligence (especially Deep Learning) is rapidly becoming the cornerstone of numerous applications, creating an ever-increasing demand for efficient Deep Learning (DL) processing. FPGAs provide massive parallelism, while being flexible and easily configurable, and also fast and power efficient. These unique properties make them appealing for DL acceleration in both data center and edge use cases.
The emergence of Deep Learning as an omnipresent workload has driven FPGA architecture evolution as well. Academic researchers have proposed optimizing the architecture of FPGAs to better fit the needs of DL workloads and FPGA companies now have AI-optimized FPGAs in their product portfolios.
FPGAs are very well-suited for prototyping and accelerating the rapidly changing algorithms and novel network architectures in the field of DL. In addition, DL is being used to assist in chip design processes such as power prediction, floorplanning, etc. including for FPGAs.
What you will learn:
In this webinar, we will discuss recent innovations in DL-optimized FPGA architecture, using AI to estimate things such as power consumption on (new or existing) FPGAs and new types of neural network accelerators using existing FPGAs.
Dr. Lizy Kurian John holds the Cullen Trust for Higher Education Endowed Professorship in Electrical Engineering in the Department of Electrical & Computer Engineering at The University of Texas at Austin. She received her Ph.D. in computer engineering from The Pennsylvania State University. She joined The University of Texas Austin faculty in 1996. Her research is in the areas of computer architecture, multicore processors, memory systems, performance evaluation and benchmarking, workload characterization, and reconfigurable computing.
Professor John holds 15 U. S. patents, has coauthored 4 books, 16 book chapters, and approximately 300 journal/ conferences/workshop papers. She is a Fellow of IEEE, Fellow of ACM and a Fellow of the National Academy of Inventors (NAI).
Aug 17, 2022
10:00 AM in Pacific Time (US and Canada)