IEEE Tech Talk -Network Architecture for AI/ML Workloads

#AI #ML # #tech #network #architecture #WIE
Share

 

 


Artificial Intelligence (AI) has emerged as a revolutionary technology that is transforming various industries and aspects of our daily lives. The rapid arrival of real-time gaming, virtual reality, generative AI and metaverse applications are changing the way network, compute, memory, storage and interconnect I/O interact for the next decade. As AI continues to advance at an unprecedented pace, the network needs to adapt to the humongous growth in traffic connecting hundreds of processors with trillions of transactions and gigabits of throughput. As AI moves out of labs and research projects toward wide adoption, it will demand significant computing resources. We will try to cover the probable network architectures to support AI workloads and the technology required for it.  



  Date and Time

  Location

  Hosts

  Registration



  • Date: 11 Jul 2023
  • Time: 05:30 PM to 06:50 PM
  • All times are (UTC-07:00) Pacific Time (US & Canada)
  • Add_To_Calendar_icon Add Event to Calendar
If you are not a robot, please complete the ReCAPTCHA to display virtual attendance info.
  • Seattle University
  • 824 12th Ave, Seattle, WA 98122
  • Seattle, Washington
  • United States 98122
  • Building: Admissions and Alumni building
  • Room Number: Stuart T. Rolfe Community Room

  • Contact Event Hosts
  • Co-sponsored by Seattle University Student Chapter
  • Starts 06 July 2023 10:24 PM
  • Ends 11 July 2023 06:50 PM
  • All times are (UTC-07:00) Pacific Time (US & Canada)
  • No Admission Charge


  Speakers

Urvish Panchal Urvish Panchal of Arista Networks

Topic:

Network Architecture for AI/ML Workloads

Artificial Intelligence (AI) has emerged as a revolutionary technology that is transforming various industries and aspects of our daily lives. The rapid arrival of real-time gaming, virtual reality, generative AI and metaverse applications are changing the way network, compute, memory, storage and interconnect I/O interact for the next decade. As AI continues to advance at an unprecedented pace, the network needs to adapt to the humongous growth in traffic connecting hundreds of processors with trillions of transactions and gigabits of throughput. As AI moves out of labs and research projects toward wide adoption, it will demand significant computing resources. We will try to cover the probable network architectures to support AI workloads and the technology required for it.  

Biography:

Urvish is a Tech Lead at Arista Networks, Inc. He has over 10 years of experience in architecting, deploying and supporting cloud data-center scale computer networks for the major service providers in the world such as Microsoft and AT&T.  He has multiple patents to his name in the field of networking and has been involved in many research projects in this field across multiple countries. At present he is helping design and build data centers for AI applications. He completed his undergraduate studies(Summa cum Laude) in India before pursuing Masters in Telecommunications at the University of Maryland, College Park. He is a certified Private Pilot and loves hiking in the pacific northwest.

Email:

Address:Seattle, United States





Agenda

Agenda:

  1. 5.30 PM to 6.00 PM - Networking Event with the speaker and IEEE members.
  2. 6.00 PM to  6.50 PM - Tech Talk and Question Hour.