The Challenge HPC-BigData is a four year project (2018-2022) funded by INRIA.


HPC and Big Data evolved with their own infrastructures (supercomputers versus clouds), applications (scientific simulations versus data analytics) and software tools (MPI and OpenMP versus Map/Reduce or Deep Learning frameworks). But Big Data analytics is becoming more compute-intensive (thanks to deep learning), while data handling is becoming a major concern for scientific computing. The Challenge HPC-BigData gathers teams from the HPC, Big Data and Machine Learning (ML) areas to work at the intersection between these domains. Research is organized along three main axes:

  • HPC acceleration for AI and Big Data
  • AI & Big Data analytics for large scale scientific simulations
  • Infrastructure and resource management

Full Initial Proposal  (Feb 2018)


INRIA Teams:

  • DataMove, Grenoble: Bruno Raffin (PI), Olivier Richard
  • KerData, Rennes: Gabriel Antoniu, Alexandru Costan
  • SequeL, Lille: Philippe Preux
  • Sierra, Paris: Francis Bach, Loic Esteve
  • Tau, Saclay: Guillaume Charpiat
  • Zenith, Montpellier: Patrick Valduriez, Alexis Joly
  • Parietal, Saclay: Gael Varoquaux
  • TADaaM, Bordeaux: Emmanuel Jeannot, Guillaume Aupy
  • HiePACS, Bordeaux: Olivier Coulaud
  • Storm, Bordeaux: Samuel Thibault
  • RealOpt, Bordeaux: Olivier Beaumont

Scientists Funded by the Challenge/IPL:

  • PhD: Alena Shilova. Advisers:  Olivier Beaumont, Alexis Joly
  • PhD: Loris Felardos. Advisers:  Guillaume Charpiat, Jerome Henin, Bruno Raffin
  • PhD: Daniel Rosendo. Advisers: Gabriel Antoniu, Patrick Valduriez
  • Postdoc: Essam Morsi (Sequel, DataMove)
  • Engineer: Pierre Glaser (Parietal, Storm)
  • Engineer: Kun He (Storm, Parietal)

External Participants:

  • Laboratoire de Biochimie Théorique (LBT), CNRS, Paris: Marc Baaden, Jérôme Hénin
  • Grid’5000: Pierre Neyron
  • Atos/Bull
  • Esi-Group
  • Argonne National Labs,  Mathematics & Computer Science Division


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