The Xilinx AI Engine: High Performance with Future-proof Architecture Adaptability


Where: Exhibit Hall ET 1

Date:  Day 2

Start Time: 4:55 pm

End Time: 5:25 pm

AI inference demands orders of magnitude more compute capacity than what today’s SoCs offer. At the same time, neural network topologies are changing too quickly to be addressed by ASICs that take years to go from architecture to production. In this talk, we introduce the Xilinx AI Engine, which complements the dynamically-programmable FPGA fabric to enable ASIC-like performance via custom data flows and a flexible memory hierarchy. This combination provides an orders-of-magnitude boost in AI performance along with the hardware architecture flexibility needed to quickly adapt to rapidly evolving neural network topologies.

Track

Session Speakers

  • Vinod Kathail is a Xilinx Fellow and the Chief Architect for the SDx Development Environment. He is also leading the company-wide focus on embedded vision including machine learning usage in edge and endpoint applications. He initiated the software programmability effort for the Zynq family, and developed and drove the adoption of SDSoC earlier on. Prior to joining Xilinx, Vinod was the founding CEO and later CTO of Synfora, a high-level synthesis startup. Vinod brings over 25 years of experience in heterogeneous programming environments, high-performance parallel and VLIW architectures, parallelizing compilers and high-level synthesis, working in both research labs (HP Labs) and startups. Vinod received a B. Tech in Electrical Engineering from MANIT, Bhopal, a M. Tech in Computer Science from IIT, Kanpur and an ScD in Electrical Engineering and Computer Science from MIT. He holds over 25 patents, and he has authored numerous research publications.


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The Xilinx AI Engine: High Performance with Future-proof Architecture Adaptability