EDS/SSC DLL - 2024 - Efficient Computing for AI and Robotics: From Hardware Accelerators to Algorithm Design

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Invitation

IEEE Joint Chapter No. 3 (EDS/SCC) of the Argentina Section invites you to the conference "PEfficient Computing for AI and Robotics: From Hardware Accelerators to Algorithm Design" given by the distinguished SSC IEEE speaker phd. Vivienne Sze from the Electrical Engineering and Computer Science Department at MIT.

Please note that the talk is sponsored under the IEEE Electron Devices Society Distinguished Lecturers Program.

 

 

Abstract

The compute demands of AI and robotics continue to rise due to the rapidly growing volume of data to be processed; the increasingly complex algorithms for higher quality of results; and the demands for energy efficiency and real-time performance. In this talk, we will discuss the design of efficient hardware accelerators and the co-design of algorithms and hardware that reduce the energy consumption while delivering real-time and robust performance for applications including deep neural networks, data analytics with sparse tensor algebra, and autonomous navigation.  We will also discuss our recent work that balances flexibility and efficiency for domain-specific accelerators and reduces the cost of analog-to-digital converters for processing-in-memory accelerators. Throughout the talk, we will highlight important design principles, methodologies, and tools that can facilitate an effective design process.






  Date and Time

  Location

  Hosts

  Registration



  • Date: 01 Jul 2024
  • Time: 04:00 PM to 05:30 PM
  • All times are (UTC-03:00) Buenos Aires
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  • Universidad Tecnológica Nacional Facultad Regional Buenos Aires
  • Medrano 951
  • CABA, Distrito Federal
  • Argentina
  • Room Number: Departamento de Electrónica

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  • Co-sponsored by Universidad Tecnológica Nacional Facultad Regional Buenos aires - Departamento de Ingeniería Electrónica
  • Starts 14 June 2024 12:00 AM
  • Ends 01 July 2024 12:00 AM
  • All times are (UTC-03:00) Buenos Aires
  • No Admission Charge


  Speakers

phd. Vivienne Sze

Biography:

 

Vivienne Sze is Professor in the Electrical Engineering and Computer Science Department at MIT. She works on computing systems that enable energy-efficient machine learning, computer vision, and video compression/processing for a wide range of applications, including autonomous navigation, digital health, and the internet of things. 

She is widely recognized for her leading work in these areas and has received awards, including faculty awards from Google, Facebook, and Qualcomm, the Symposium on VLSI Circuits Best Student Paper Award, the IEEE Custom Integrated Circuits Conference Outstanding Invited Paper Award, and the IEEE Micro Top Picks Award.

As a member of the Joint Collaborative Team on Video Coding, she received the Primetime Engineering Emmy Award for the development of the High-Efficiency Video Coding video compression standard.  

She is a co-editor of High Efficiency Video Coding (HEVC): Algorithms and Architectures (Springer, 2014) and co-author of Efficient Processing of Deep Neural Networks (Synthesis Lectures on Computer Architecture, Morgan Claypool, 2020). 

For more information about Prof. Sze’s research, please visit http://sze.mit.edu