{"id":98,"date":"2020-09-09T15:37:00","date_gmt":"2020-09-09T13:37:00","guid":{"rendered":"https:\/\/project.inria.fr\/hpcbigdata\/?page_id=98"},"modified":"2022-05-31T11:23:51","modified_gmt":"2022-05-31T09:23:51","slug":"events","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/hpcbigdata\/events\/","title":{"rendered":"Events"},"content":{"rendered":"<h3>Kickoff Meeting, Paris, 16-17 May 2018<\/h3>\n<ul>\n<li>16 May:\n<ul>\n<li>9h45: The HPC-BigData Challenge: overview. Bruno Raffin<\/li>\n<li>10h45: HPC Infrastructures for AI. Olivier Richard &amp; Benoit Pelletier<\/li>\n<li>11h: Feedback on using CINES machine. Alexis Joly.<\/li>\n<li>11h15: The Gricad\/G5K HPDA machine for HPC\/BigData processing. Pierre Neyron.<\/li>\n<li>11h30: Discussions<\/li>\n<li>12h: Talk from ESI-group. Argiris Kamoulakos<\/li>\n<li>12h20: (PhD IPL 2018) Bridging in situ\/in transit processing with Big Data analytics. Gabriel Antoniu &amp; Patrick Valduriez<\/li>\n<li>12h40: (PhD IPL 2018) Scheduling Strategies for High Performance Deep Learning. Olivier Beaumont &amp; Alexis Joly<\/li>\n<li>13h30 Lunch<\/li>\n<li>15h IPL) Parallel Scikit-Learn with Dask\/StarPU. Samuel Thibault &amp; Gael Varoquaux<\/li>\n<li>15h20: (PhD IPL 2019) Analysis of Massive Molecular Trajectories through Deep Learning. Guillaume Charpiat &amp; J\u00e9rome Henin<\/li>\n<li>15h40: (Postdoc IPL 2019) High Performance Deep Reinforcement Learning. Bruno Raffin &amp; Philippe Preux.<\/li>\n<li>16h: Algorithmic Challenges: Linear Algebra and Tensors. Olivier Coulaud &amp; Francis Bach<\/li>\n<li>16h20: Automatic Differentiation, Backpropagation and Adjoint. Guillaume Aupy<\/li>\n<\/ul>\n<\/li>\n<li>17 May: Free discussions and sub-group meetings.<\/li>\n<\/ul>\n<h3>Plenary Meeting, 17 &amp; 18 October 2018, Lyon<\/h3>\n<ul>\n<li>17 October\n<ul>\n<li>9h30-10h15: Coffee<\/li>\n<li>10h15:\n<ul>\n<li>State of Progress, Bruno Raffin<\/li>\n<li>Didactic presentation for the HPC community of data integration and BL\/DL crossover. Gael Varoquaux<\/li>\n<li>Deep or Shallow Learning: use cases. Guillaume Charpia<\/li>\n<\/ul>\n<\/li>\n<li>12h30: lunch<\/li>\n<li>14h: Sub-group Discussions<\/li>\n<li>16h: Coffee<\/li>\n<li>16h30:\n<ul>\n<li>Use cases \/ Middleware for data management\/ FPGAs. St\u00e9phane Pralet.<\/li>\n<li>PlantNet experiments on HPC platforms. Alexis Joly<\/li>\n<\/ul>\n<\/li>\n<li>17h30: Open Discussions<\/li>\n<\/ul>\n<\/li>\n<li>Jeudi 18 Octobre:\n<ul>\n<li>8h30: Sub-group Discussions<\/li>\n<li>9h30: State of the Art on AI for Molecular Dynammics.J\u00e9r\u00f4me H\u00e9nin.<\/li>\n<li>10h Coffee<\/li>\n<li>10h30:\n<ul>\n<li>Compute Infrastructures for HPC-AI. Pierre Neyron<\/li>\n<li>Parallel polyglot query processing on heterogeneous could data stores with leanxale. Boyan Kolev<\/li>\n<li>HPC Storage. Emmanuel Jeannot<\/li>\n<\/ul>\n<\/li>\n<li>12h30: Lunch<\/li>\n<li>14h: Open Discussion<\/li>\n<li>16h: Coffee<\/li>\n<li>16h30: Summary.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3>Plenary Meeting, 2-3 April 2019, Paris<\/h3>\n<ul>\n<li>2 April\n<ul>\n<li>9h: Welcome Coffee<\/li>\n<li>10h: News. Bruno Raffin<\/li>\n<li>10h30: Talk: Decentralized Data Processing for the PlantNet Workflow. Pedro Silva (KerData)<\/li>\n<li>11h: Discussion: NVRAM impact on BigData and AI. Emmanuel Jeannot<\/li>\n<li>11h30: Coffee<\/li>\n<li>12h Talk: Decreasing memory consumption while training neural networks with the help of<br \/>\ncheckpointing strategies. Alena Shilova<\/li>\n<li>12h30: Discussion: Smart data center &amp; supercomputer: how to use ML for managing machine resources. St\u00e9phane Pralet<\/li>\n<li>15h15: Talk: Asynchronous Gradient Descent. Hadrien Hendrikx (SIERRA)<\/li>\n<li>15h45: Discussion: How to leverage the probabilist nature of learning algorithms for asynchronism. Francis Bach<\/li>\n<li>16h15: Coffee<\/li>\n<li>16h45: Talk: Scikit-Learn &#8211; Dask &amp; StarPU. Pierre Glaser<\/li>\n<li>17h15: Day Summary. Bruno Raffin<\/li>\n<\/ul>\n<\/li>\n<li>3 April\n<ul>\n<li>9h: Coffee<\/li>\n<li>9h15: Talk: Deep Learning for Molecular Dynamics.Loris Felardos<\/li>\n<li>9h45: Feedback on the Jean-Zay machine from GENCI. Guillaume Charpiat, Bruno Raffin, Alexis Joly<\/li>\n<li>10h: Talk: On-line Learning for Meta-models. Bruno Raffin<\/li>\n<li>10h30: Coffee<\/li>\n<li>11h: Discussion: Numerical Simulation and AI. Guillaume Charpiat<\/li>\n<li>11h30: Discussion: Data and model parallelism for DL. Olivier Beaumont<\/li>\n<li>12h15: Lunch<\/li>\n<li>14h15: Talk: Deep Reinforcement Learning at Scale: early experiments. Yannis Flet-Berliac (Sequel)<\/li>\n<li>14h45: Discussion: Applications of Reinforcement Learning. Philippe Preux<\/li>\n<li>15h15: Conv&#8217;2019 Workshop (organization, program)<\/li>\n<li>15h30: Coffee<\/li>\n<li>16h: Summary and Closing Remarks.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3>Conv&#8217;2019, EDF Lab Paris-Saclay &#8211; 6 and 7 of November 2019<\/h3>\n<ul>\n<li>We organized with EDF Lab the <a href=\"https:\/\/project.inria.fr\/conv2019\/\"> HPC &#8211; AI &#8211; BigData Convergence Days (Conv&#8217;2019)<\/a>.\u00a0 Go to\u00a0<a href=\"https:\/\/project.inria.fr\/conv2019\/program\/\"> the program and slides<\/a>.<\/li>\n<\/ul>\n<h3>Plenary Meeting, 22-23 January 2020, Paris<\/h3>\n<ul>\n<li>22\/01\n<ul>\n<li>9:15 Coffee<\/li>\n<li>9:45 Opening and Activity Report. Bruno Raffin<\/li>\n<li>10:30 Overview &#8211; MILA perspective on the HPC\/IA convergence. Sacha Lepr\u00eatre (MILA)<\/li>\n<li>10:45 Spike Networks. Loris Felardos<\/li>\n<li>11:30 Physics-Inspired Neural Networks. Alessandro Bucci<\/li>\n<li>12:15 Deep Reinforcement Learning Infrastructures. Essam Morsi<\/li>\n<li>13:30 Lunch<\/li>\n<li>15:00 Open discussion: the Jean Zay machine (lead: Loic Esteve)\n<ul>\n<li>Each Jean Zay user should sort-out his\/her experience to bring elements to the discussion<\/li>\n<li>Idris representative will be present (Sylvie Therond, Myriam Peyrounette, Pierre-Francois Lavall\u00e9e)<\/li>\n<\/ul>\n<\/li>\n<li>16:00 Expectations for a day-to-day productive resarch environment, Loic Esteve<\/li>\n<li>16:30 IPL: Next actions (lead: Bruno Raffin)<\/li>\n<li>17:00:Free group discussions<\/li>\n<\/ul>\n<\/li>\n<li>23\/01\n<ul>\n<li>9:00 Cloud and Edge Intelligent Analytics. Daniel Rosendo<\/li>\n<li>9:45 Molecular Dynamics &amp; Deep Learning. J\u00e9r\u00f4me H\u00e9nin<\/li>\n<li>10:30 Coffee break<\/li>\n<li>11:00 Scikit Learn. Olivier Grisel<\/li>\n<li>11:30 Open Discussion &#8211; Trends\n<ul>\n<li>Suggested topics: auto-deep learning, physics-inspired NN, differential programming.<\/li>\n<\/ul>\n<\/li>\n<li>12:00 Keynote &#8211; MILA perspective on the HPC\/IA convergence. Sacha Lepr\u00eatre<\/li>\n<li>13:30 Lunch break<\/li>\n<li>15:30 MILA Technical Talk &#8211; Frederic Costera (visio from MILA)<\/li>\n<li>16:00 GENCI. St\u00e9phane Requena<\/li>\n<li>16:30 Discussion on potential collaborations INRIA\/MILA and Wrap-up.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3>Plenary Meeting, 30-31 May 2022, Paris<\/h3>\n<ul>\n<li>Monday 30th\n<ul>\n<li>9:30-10:00 Morning Coffee<\/li>\n<li>10:00-10:15 Activity Summary &#8211; Bruno Raffin<\/li>\n<li>10:15-11:00 External talk: <a href=\"https:\/\/deephyper.readthedocs.io\">DeepHyper.<\/a> Romain Negele<\/li>\n<li>11:00:-12:30 (20 minutes each)\n<ul>\n<li>Rotor &#8211; Lionel Eyraud-Dubois<\/li>\n<li>Model Based RL &#8211; Alena Shilova<\/li>\n<li>AI on Jean-Zay &#8211; Loic Esteve<\/li>\n<\/ul>\n<\/li>\n<li>13:30 Lunch<\/li>\n<li>15:00-15:45 &#8211; External Talk: <a href=\"https:\/\/huggingface.co\">Hugging Face<\/a> &#8211;\u00a0 Lucile Saulnier &#8211; Thomas Wang<\/li>\n<li>15:45 Break<\/li>\n<li>16:15-17:15 (20 minutes each)\n<ul>\n<li>Learning probability distributions for molecular dynamics &#8211; Jerome Henin<\/li>\n<li>AI in the MD community &#8211; Marc Baaden<\/li>\n<li>Ray &#8211; Bruno Raffin<\/li>\n<\/ul>\n<\/li>\n<li>17:15: Discussion PEPR IA &#8211; PEPR NUMPEX \/ EU calls \/ projects<\/li>\n<\/ul>\n<\/li>\n<li>Tuesday 31th\n<ul>\n<li>8:45-9:15 Morning Coffee<\/li>\n<li>9:15-10:00 &#8211; External Talk: <a href=\"https:\/\/onnx.ai\/\">ONNX<\/a>\u00a0 &#8211; Xavier Dupr\u00e9<\/li>\n<li>10:00-10:30 Coffee<\/li>\n<li>10:30-12:00 (20 minutes each)\n<ul>\n<li>CPU Offloading for GPU NN training\u00a0 &#8211; Xunyi Zhao<\/li>\n<li>AI for physics &#8211; Guillaume Charpiat<\/li>\n<li>Deep Surrogate for CFD &#8211; Lucas Meyer<\/li>\n<li>E2Clab &#8211; Daniel Rosendo<\/li>\n<\/ul>\n<\/li>\n<li>12:30 Lunch<\/li>\n<li>14:30-15:15 External Talk: <a href=\"https:\/\/sinclair-lab.com\">SINCLAIR Lab<\/a>\u00a0 &#8211; Nicolas Bousquet<\/li>\n<li>15:15-15:30 Short coffee break<\/li>\n<li>15:30-16:30 (20 minutes each)\n<ul>\n<li>HPC et Data Science: Inria et LATAM &#8211; Patrick Valduriez<\/li>\n<li>Scikit-learn at Scale &#8211; Gael Varoauaux<\/li>\n<li>Simulation based inference &#8211; Sofya Dymchenko<\/li>\n<\/ul>\n<\/li>\n<li>16:30 Final discussions<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Kickoff Meeting, Paris, 16-17 May 2018 16 May: 9h45: The HPC-BigData Challenge: overview. Bruno Raffin 10h45: HPC Infrastructures for AI. Olivier Richard &amp; 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\u2026<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/hpcbigdata\/events\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":1416,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-98","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/hpcbigdata\/wp-json\/wp\/v2\/pages\/98","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/hpcbigdata\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/hpcbigdata\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/hpcbigdata\/wp-json\/wp\/v2\/users\/1416"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/hpcbigdata\/wp-json\/wp\/v2\/comments?post=98"}],"version-history":[{"count":4,"href":"https:\/\/project.inria.fr\/hpcbigdata\/wp-json\/wp\/v2\/pages\/98\/revisions"}],"predecessor-version":[{"id":141,"href":"https:\/\/project.inria.fr\/hpcbigdata\/wp-json\/wp\/v2\/pages\/98\/revisions\/141"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/hpcbigdata\/wp-json\/wp\/v2\/media?parent=98"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}