0

Your cart



TOTAL excl.
TOTAL incl.
Pay

Parallel sessions - High Performance Computing for AI

11/17/2020 | 10:15 - 12:15 | Laval Virtual

Description

- Time schedule in France & Germany :  10:15 to 12:15
- Time schedule in Japan : 18:15 to 20:15
The development of efficient AI models relies not only on a large volume of data to learn from, but also on
powerful computational resources to process those data. In this context, increasingly high-performance computers are being designed with a focus on serving AI applications, including exascale applications dedicated to weather forecasts, astronomy, petroleum prospecting and or financial market predictions.

This session will discuss how and why AI development can leverage high-performance computing as well as how high-performance computing can benefit from AI, and how international co-operation can help to optimise the development and the use of these supercomputers.

What advantages do Japan, France and Germany have in working together (i.e. scientists, companies, political decision-makers, etc.) on this subject? Why? How can we improve co-operation and what are the current brakes and deadlocks?

Speakers

  • Mr. Stéphane Requena Mr. Stéphane Requena
    Chief Technical Officer, GENCI
  • Prof. Nahid Emad Prof. Nahid Emad
    Professor, Computer Science, University of Paris Saclay/ Versailles (LI-PARAD Laboratory and Maison de la Simulation)
  • Prof. Dr. Matthias Weidemüller Prof. Dr. Matthias Weidemüller
    Professor of Physics, Department of Physics and Astronomy, Physics Institute, Heidelberg University
  • Mr. Severin Reiz Mr. Severin Reiz
    Research associate, Scientific computing in Computer Science, Technical University of Munich (TUM)
  • Dr. Prof. Satoshi Matsuoka Dr. Prof. Satoshi Matsuoka
    Director, Riken Center for Computational Science (R-CCS), RIKEN
  • Dr. Yasunori Kimura Dr. Yasunori Kimura
    Supervisory Innovation Coordinator, Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST)