

{"id":4,"date":"2011-12-08T11:55:34","date_gmt":"2011-12-08T11:55:34","guid":{"rendered":"http:\/\/project.inria.fr\/template1\/?page_id=4"},"modified":"2019-11-19T02:35:51","modified_gmt":"2019-11-19T01:35:51","slug":"home","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/conv2019\/","title":{"rendered":"Conv&#8217;2019"},"content":{"rendered":"<p><\/p>\n<div id=\"magicdomid104\" class=\"ace-line\">\n<ul>\n<li><strong>When: <\/strong>6 and 7 of November 2019<\/li>\n<li><strong>Where:\u00a0 <\/strong>EDF Lab Paris-Saclay<\/li>\n<li><strong>Contact:<\/strong> <a href=\"mailto:conv2019@inria.fr\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">conv2019@inria.fr<\/span><\/a><\/li>\n<li><strong>Registrations:\u00a0 Closed<br \/>\n<\/strong><\/li>\n<li><strong>News:<\/strong>\n<ul>\n<li>18\/11\/19: <a href=\"https:\/\/project.inria.fr\/conv2019\/program\/#program\">Slides are now online<\/a><\/li>\n<li>7\/11\/2019:\u00a0 More than 200 registrations with a good mix of academic and industrial attendees. Great talks, great discussions, very fritfull event.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><a href=\"https:\/\/project.inria.fr\/conv2019\/files\/2019\/11\/IMG-20191106-WA0000.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-278 aligncenter\" src=\"https:\/\/project.inria.fr\/conv2019\/files\/2019\/11\/IMG-20191106-WA0000-300x114.jpg\" alt=\"\" width=\"632\" height=\"240\" srcset=\"https:\/\/project.inria.fr\/conv2019\/files\/2019\/11\/IMG-20191106-WA0000-300x114.jpg 300w, https:\/\/project.inria.fr\/conv2019\/files\/2019\/11\/IMG-20191106-WA0000-768x291.jpg 768w, https:\/\/project.inria.fr\/conv2019\/files\/2019\/11\/IMG-20191106-WA0000-1024x388.jpg 1024w, https:\/\/project.inria.fr\/conv2019\/files\/2019\/11\/IMG-20191106-WA0000-150x57.jpg 150w, https:\/\/project.inria.fr\/conv2019\/files\/2019\/11\/IMG-20191106-WA0000.jpg 1600w\" sizes=\"auto, (max-width: 632px) 100vw, 632px\" \/><\/a><\/p>\n<p>&nbsp;<\/p>\n<p>High Performance Computing (HPC), Machine Learning and Big Data are supported by distinct communities developing different scientific and technological approaches and targeting different application domains. Today a trend is emerging to converge these domains with high benefits expected from this cross-fertilization.<\/p>\n<p>Deep learning has a strong appetite for compute power, making HPC a natural target. Strong progress has been made to efficiently parallelize the training phase. As an example, ResNet-50 training evolved from 29 hours on 8 GPUS in 2016 to 224 seconds on 2176 GPUs in 2018. Numerical simulations, the first customer of supercomputers, are evolving to integrate machine learning algorithms at various level, for output analysis or get new fast numerical solvers by training for instance. Machine learning can also be used to improve supercomputer management for a better QoS and resource usage.<\/p>\n<p><strong>Conv\u20192019\u00a0 is\u00a0 intended to bring together stakeholders from the academy and industry interested in the various aspects of this emerging convergence between Artificial Intelligence, Big Data and High Performance Computing.<\/strong><\/p>\n<p>The goal of these 2 days is to create a space for discussions and reflections structured around keynote speeches, scientific presentations, panels. <a href=\"https:\/\/project.inria.fr\/conv2019\/call-for-communications\/\">Do not hesitate to propose a presentation or panel.<\/a><\/p>\n<\/div>\n<div id=\"magicdomid108\" class=\"ace-line\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">Topics covered include (not limited):<\/span><\/div>\n<ul>\n<li id=\"magicdomid109\" class=\"ace-line\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">\u00a0 Converged applications <\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">mixing simulations and analytics (e.g., data-enhanced <\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">Digital Twins<\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">)<\/span><\/li>\n<li id=\"magicdomid110\" class=\"ace-line\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">\u00a0 Numerical simulations<\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">, data analytics and<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\"> machine learning: couplin<\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">g<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\"> and integration<\/span><\/li>\n<li id=\"magicdomid111\" class=\"ace-line\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">\u00a0 Distributed and parallel machine learning<\/span><\/li>\n<li id=\"magicdomid112\" class=\"ace-line\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">\u00a0 <\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">Extreme-<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">scale learning<\/span><\/li>\n<li id=\"magicdomid113\" class=\"ace-line\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">\u00a0 <\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">Extreme-<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">scale data analy<\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">tics, High-Performance Data Analytics<\/span><\/li>\n<li id=\"magicdomid114\" class=\"ace-line\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">\u00a0 Machine <\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">l<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">earning for optimizing large digital infrastructures (supercomputers, cloud, edge)<\/span><\/li>\n<li id=\"magicdomid115\" class=\"ace-line\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">\u00a0 <\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">Innovative hardware and software a<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">rchitecture<\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">s<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\"> and <\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">smart <\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">administration of digital infrastructures <\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">in support of<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\"> heterogeneous applications (numerical simulations, data analytics, shallow and deep learning)<\/span><\/li>\n<li id=\"magicdomid116\" class=\"ace-line\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">\u00a0 Streaming, curation<\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">, processing<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\"> and\u00a0 storage of massive data for learning<\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\"> in converged scenarios<\/span><\/li>\n<li id=\"magicdomid117\" class=\"ace-line\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">\u00a0 <\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">Scalable o<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">nline <\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">l<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">earning and <\/span><span class=\"author-a-2rj3z70zlucz89zz77znz84zmz88zz67zi\">a<\/span><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">nalytics<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p>This event is supported by INRIA and EDF R&amp;D.<\/p>\n<p>Contact: <a href=\"mailto:conv2019@inria.fr\"><span class=\"author-a-u51z67z9ytz65z4z82zira4iv\">conv2019@inria.fr<\/span><\/a><\/p>","protected":false},"excerpt":{"rendered":"<p>When: 6 and 7 of November 2019 Where:\u00a0 EDF Lab Paris-Saclay Contact: conv2019@inria.fr Registrations:\u00a0 Closed News: 18\/11\/19: Slides are now online 7\/11\/2019:\u00a0 More than 200 registrations with a good mix of academic and industrial attendees. Great talks, great discussions, very fritfull event. &nbsp; High Performance Computing (HPC), Machine Learning and&#8230;<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/conv2019\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"","meta":{"footnotes":""},"class_list":["post-4","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/conv2019\/wp-json\/wp\/v2\/pages\/4","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/conv2019\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/conv2019\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/conv2019\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/conv2019\/wp-json\/wp\/v2\/comments?post=4"}],"version-history":[{"count":48,"href":"https:\/\/project.inria.fr\/conv2019\/wp-json\/wp\/v2\/pages\/4\/revisions"}],"predecessor-version":[{"id":283,"href":"https:\/\/project.inria.fr\/conv2019\/wp-json\/wp\/v2\/pages\/4\/revisions\/283"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/conv2019\/wp-json\/wp\/v2\/media?parent=4"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}