UTDSIDSIEventsDSI Meet Up: Seminar Series on Embedded AI
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DSI Meet Up: Seminar Series on Embedded AI October edition

This Dedicated DSI Meet Up will be the second of a series on Embedded AI, co-organized by the CAES and DMB groups.

The “Embedded AI” seminar series is designed to bring together students and researchers passionate about embedded artificial intelligence. Our goal is to showcase the latest research and innovative applications in this field while creating a space for networking and collaboration. By attending these talks, you’ll have the opportunity to learn from experts, share your work, and connect with others who are working on similar projects. Whether you’re just starting out or already have experience in embedded AI, this seminar series is a great way to expand your knowledge and be part of a growing community. Join us at our first seminar to learn more about embedded AI's exciting possibilities and how you can contribute to intelligent systems' future.

Abstract

Join us for an engaging 30-minute lunch seminar into the captivating world of Embedded AI. During this session, we will cover the following topic:

AMD XDNA Architecture from Client to Datacenters

In this presentation, I will start by describing the AMD product portfolio for AI, covering both hardware and software. I will follow by introducing the AMD University Program and the academic solutions available for the academic community. Then, I will introduce the AMD Ryzen AI which is the first in a new class of Neural Processing Units (NPU) designed for x86 computers. Built on the AMD XDNA™ spatial dataflow computer architecture, the NPU consists of a tiled array of AI Engine processors, a set of VLIW vector processors with adaptable interconnect, designed to offer lower latency and better energy efficiency. Finally, I will present a set of platforms enabled by the AMD XDNA™ and the software stacks available.

Speakers

Dr. Mario Ruiz
Member of technical staff in the AMD University Program at AMD

Mario is a member of technical staff in the AMD University Program at AMD. As part of this role he delivers training workshops for academics on the latest AMD tools and technologies. He is responsible for managing the Heterogenous Accelerated Compute Cluster globally. Recently he has been working on VNx integrating an open source 100 GbE network stack on Alveo platforms for the Vitis flow. He is also part of the PYNQ project – a Python-based open-source productivity environment for Zynq, Zynq MPSoC and Alveo, where he contributed with the Composable Overlays. Before joining AMD, Mario completed his PhD in the Autonomous University of Madrid, which was focused on exploring High Level Synthesis tools in the context of networking. Mario has a background on electronics and digital design.

Registration

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