Events

Kickoff Meeting, Paris, 16-17 May 2018

  • 16 May:
    • 9h45: The HPC-BigData Challenge: overview. Bruno Raffin
    • 10h45: HPC Infrastructures for AI. Olivier Richard & Benoit Pelletier
    • 11h: Feedback on using CINES machine. Alexis Joly.
    • 11h15: The Gricad/G5K HPDA machine for HPC/BigData processing. Pierre Neyron.
    • 11h30: Discussions
    • 12h: Talk from ESI-group. Argiris Kamoulakos
    • 12h20: (PhD IPL 2018) Bridging in situ/in transit processing with Big Data analytics. Gabriel Antoniu & Patrick Valduriez
    • 12h40: (PhD IPL 2018) Scheduling Strategies for High Performance Deep Learning. Olivier Beaumont & Alexis Joly
    • 13h30 Lunch
    • 15h IPL) Parallel Scikit-Learn with Dask/StarPU. Samuel Thibault & Gael Varoquaux
    • 15h20: (PhD IPL 2019) Analysis of Massive Molecular Trajectories through Deep Learning. Guillaume Charpiat & Jérome Henin
    • 15h40: (Postdoc IPL 2019) High Performance Deep Reinforcement Learning. Bruno Raffin & Philippe Preux.
    • 16h: Algorithmic Challenges: Linear Algebra and Tensors. Olivier Coulaud & Francis Bach
    • 16h20: Automatic Differentiation, Backpropagation and Adjoint. Guillaume Aupy
  • 17 May: Free discussions and sub-group meetings.

Plenary Meeting, 17 & 18 October 2018, Lyon

  • 17 October
    • 9h30-10h15: Coffee
    • 10h15:
      • State of Progress, Bruno Raffin
      • Didactic presentation for the HPC community of data integration and BL/DL crossover. Gael Varoquaux
      • Deep or Shallow Learning: use cases. Guillaume Charpia
    • 12h30: lunch
    • 14h: Sub-group Discussions
    • 16h: Coffee
    • 16h30:
      • Use cases / Middleware for data management/ FPGAs. Stéphane Pralet.
      • PlantNet experiments on HPC platforms. Alexis Joly
    • 17h30: Open Discussions
  • Jeudi 18 Octobre:
    • 8h30: Sub-group Discussions
    • 9h30: State of the Art on AI for Molecular Dynammics.Jérôme Hénin.
    • 10h Coffee
    • 10h30:
      • Compute Infrastructures for HPC-AI. Pierre Neyron
      • Parallel polyglot query processing on heterogeneous could data stores with leanxale. Boyan Kolev
      • HPC Storage. Emmanuel Jeannot
    • 12h30: Lunch
    • 14h: Open Discussion
    • 16h: Coffee
    • 16h30: Summary.

Plenary Meeting, 2-3 April 2019, Paris

  • 2 April
    • 9h: Welcome Coffee
    • 10h: News. Bruno Raffin
    • 10h30: Talk: Decentralized Data Processing for the PlantNet Workflow. Pedro Silva (KerData)
    • 11h: Discussion: NVRAM impact on BigData and AI. Emmanuel Jeannot
    • 11h30: Coffee
    • 12h Talk: Decreasing memory consumption while training neural networks with the help of
      checkpointing strategies. Alena Shilova
    • 12h30: Discussion: Smart data center & supercomputer: how to use ML for managing machine resources. Stéphane Pralet
    • 15h15: Talk: Asynchronous Gradient Descent. Hadrien Hendrikx (SIERRA)
    • 15h45: Discussion: How to leverage the probabilist nature of learning algorithms for asynchronism. Francis Bach
    • 16h15: Coffee
    • 16h45: Talk: Scikit-Learn – Dask & StarPU. Pierre Glaser
    • 17h15: Day Summary. Bruno Raffin
  • 3 April
    • 9h: Coffee
    • 9h15: Talk: Deep Learning for Molecular Dynamics.Loris Felardos
    • 9h45: Feedback on the Jean-Zay machine from GENCI. Guillaume Charpiat, Bruno Raffin, Alexis Joly
    • 10h: Talk: On-line Learning for Meta-models. Bruno Raffin
    • 10h30: Coffee
    • 11h: Discussion: Numerical Simulation and AI. Guillaume Charpiat
    • 11h30: Discussion: Data and model parallelism for DL. Olivier Beaumont
    • 12h15: Lunch
    • 14h15: Talk: Deep Reinforcement Learning at Scale: early experiments. Yannis Flet-Berliac (Sequel)
    • 14h45: Discussion: Applications of Reinforcement Learning. Philippe Preux
    • 15h15: Conv’2019 Workshop (organization, program)
    • 15h30: Coffee
    • 16h: Summary and Closing Remarks.

Conv’2019, EDF Lab Paris-Saclay – 6 and 7 of November 2019

Plenary Meeting, 22-23 January 2020, Paris

  • 22/01
    • 9:15 Coffee
    • 9:45 Opening and Activity Report. Bruno Raffin
    • 10:30 Overview – MILA perspective on the HPC/IA convergence. Sacha Leprêtre (MILA)
    • 10:45 Spike Networks. Loris Felardos
    • 11:30 Physics-Inspired Neural Networks. Alessandro Bucci
    • 12:15 Deep Reinforcement Learning Infrastructures. Essam Morsi
    • 13:30 Lunch
    • 15:00 Open discussion: the Jean Zay machine (lead: Loic Esteve)
      • Each Jean Zay user should sort-out his/her experience to bring elements to the discussion
      • Idris representative will be present (Sylvie Therond, Myriam Peyrounette, Pierre-Francois Lavallée)
    • 16:00 Expectations for a day-to-day productive resarch environment, Loic Esteve
    • 16:30 IPL: Next actions (lead: Bruno Raffin)
    • 17:00:Free group discussions
  • 23/01
    • 9:00 Cloud and Edge Intelligent Analytics. Daniel Rosendo
    • 9:45 Molecular Dynamics & Deep Learning. Jérôme Hénin
    • 10:30 Coffee break
    • 11:00 Scikit Learn. Olivier Grisel
    • 11:30 Open Discussion – Trends
      • Suggested topics: auto-deep learning, physics-inspired NN, differential programming.
    • 12:00 Keynote – MILA perspective on the HPC/IA convergence. Sacha Leprêtre
    • 13:30 Lunch break
    • 15:30 MILA Technical Talk – Frederic Costera (visio from MILA)
    • 16:00 GENCI. Stéphane Requena
    • 16:30 Discussion on potential collaborations INRIA/MILA and Wrap-up.

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