2020 Plenary Meeting
Covid disrupted our pace of plenary meetings for a while. We are happy to be back together, face-to-face, the 30&31 of May 2022 for a new fruitful plenary meeting at INRIA Paris
Category: Uncategorized
Inria-Skoltech Moliere Associated Team
Molière (Memory Optimization for paraLlel traIning of dEep neuRal nEtworks) is an Inria Associated Team between Hiepacs project team and the Center for Computational and Data-Intensive Science and Engineering at Skoltech The main goal concerns the development of algorithms to better manage memory constraints and increase the scalability of DNN training algorithms,…
Keynote: Ray Summit 2020
Gaël Varoquaux is Keynote Speaker at the Ray Summit 2020: Easier Machine Learning Thoughts From Scikit-Learn – Gaël Varoquaux, Research Director, Inria
Publication: Cluster 2020
Daniel Rosendo, Pedro Silva, Matthieu Simonin, Alexandru Costan, Gabriel Antoniu. E2Clab: Exploring the Computing Continuum through Repeatable, Replicable and Reproducible Edge-to-Cloud Experiments. Cluster 2020 – IEEE International Conference on Cluster Computing, Sep 2020, Kobe, Japan. ⟨https://hal.archives-ouvertes.fr/hal-02916032⟩
Publication: Europar 2020
Olivier Beaumont, Lionel Eyraud-Dubois, Alena Shilova. Optimal GPU-CPU Offloading Strategies for Deep Neural Network Training. EuroPar 2020, Aug 2020, Warsaw, Poland. https://hal.archives-ouvertes.fr/hal-02316266/
Publication: Philosophical Transactions of the Royal Society A -2020
Olivier Beaumont, Julien Herrmann, Guillaume Aupy, Alena Shilova. Optimal Memory-aware Backpropagation of Deep Join Networks. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Royal Society 2020. https://hal.archives-ouvertes.fr/hal-02401105
INSU Défi 17 – January 2020
Bruno Raffin gave a talk on the AI/HPC convergence at the INSU (Institut national des sciences de l’Univers) prospective workshop (Défi 17 : Vers l’exascale : convergence HPC et HPDA). January 2020, Paris.
Publication: NIPS2019
Input Similarity from the Neural Network Perspective. Charpiat, Guillaume and Girard, Nicolas and Felardos, Loris and Tarabalka, Yuliya. NIPS 2019. https://papers.nips.cc/paper/8775-input-similarity-from-the-neural-network-perspective
Keynote SparkAISummit 2019
Gaël Varoquaux is Keynote Speaker at the Spark + AI Summit Europe 2019: Democratizing Machine Learning: Perspective from a scikit-learn Creator
Conv2019
The IPL is teaming with EDF Lab to organize the HPC – AI – BigData Convergence Days (Conv’2019), at Saclay 6&7 of November 2019.
Inria-Skoltech Moliere Associated Team
Molière (Memory Optimization for paraLlel traIning of dEep neuRal nEtworks) is an Inria Associated Team between Hiepacs project team and the Center for Computational and Data-Intensive Science and Engineering at Skoltech The main goal concerns the development of algorithms to better manage memory constraints and increase the scalability of DNN training algorithms,…
Keynote: Ray Summit 2020
Gaël Varoquaux is Keynote Speaker at the Ray Summit 2020: Easier Machine Learning Thoughts From Scikit-Learn – Gaël Varoquaux, Research Director, Inria
Publication: Cluster 2020
Daniel Rosendo, Pedro Silva, Matthieu Simonin, Alexandru Costan, Gabriel Antoniu. E2Clab: Exploring the Computing Continuum through Repeatable, Replicable and Reproducible Edge-to-Cloud Experiments. Cluster 2020 – IEEE International Conference on Cluster Computing, Sep 2020, Kobe, Japan. ⟨https://hal.archives-ouvertes.fr/hal-02916032⟩
Publication: Europar 2020
Olivier Beaumont, Lionel Eyraud-Dubois, Alena Shilova. Optimal GPU-CPU Offloading Strategies for Deep Neural Network Training. EuroPar 2020, Aug 2020, Warsaw, Poland. https://hal.archives-ouvertes.fr/hal-02316266/
Publication: Philosophical Transactions of the Royal Society A -2020
Olivier Beaumont, Julien Herrmann, Guillaume Aupy, Alena Shilova. Optimal Memory-aware Backpropagation of Deep Join Networks. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Royal Society 2020. https://hal.archives-ouvertes.fr/hal-02401105
INSU Défi 17 – January 2020
Bruno Raffin gave a talk on the AI/HPC convergence at the INSU (Institut national des sciences de l’Univers) prospective workshop (Défi 17 : Vers l’exascale : convergence HPC et HPDA). January 2020, Paris.
Publication: NIPS2019
Input Similarity from the Neural Network Perspective. Charpiat, Guillaume and Girard, Nicolas and Felardos, Loris and Tarabalka, Yuliya. NIPS 2019. https://papers.nips.cc/paper/8775-input-similarity-from-the-neural-network-perspective
Keynote SparkAISummit 2019
Gaël Varoquaux is Keynote Speaker at the Spark + AI Summit Europe 2019: Democratizing Machine Learning: Perspective from a scikit-learn Creator
Conv2019
The IPL is teaming with EDF Lab to organize the HPC – AI – BigData Convergence Days (Conv’2019), at Saclay 6&7 of November 2019.
