{"id":2234,"date":"2025-01-22T11:07:45","date_gmt":"2025-01-22T10:07:45","guid":{"rendered":"https:\/\/numpex.org\/le-troisieme-atelier-de-co-conception-et-de-co-developpement-dexa-di-sur-lintelligence-artificielle-pour-hpcexscale\/"},"modified":"2025-03-04T08:57:16","modified_gmt":"2025-03-04T07:57:16","slug":"le-troisieme-atelier-de-co-conception-et-de-co-developpement-dexa-di-sur-lintelligence-artificielle-pour-hpcexscale","status":"publish","type":"post","link":"https:\/\/numpex.org\/fr\/le-troisieme-atelier-de-co-conception-et-de-co-developpement-dexa-di-sur-lintelligence-artificielle-pour-hpcexscale\/","title":{"rendered":"Le troisi\u00e8me atelier de co-conception et de co-d\u00e9veloppement d’Exa-DI sur \u00ab\u00a0l’intelligence artificielle pour HPC@Exscale\u00a0\u00bb."},"content":{"rendered":"

[vc_row][vc_column width=\u00a0\u00bb1\/1″][vc_column_text uncode_shortcode_id=\u00a0\u00bb583731″]Le troisi\u00e8me atelier de co-conception\/co-d\u00e9veloppement du projet Exa-DI<\/a> (D\u00e9veloppement et Int\u00e9gration) du PEPR NumPEx<\/a> \u00e9tait d\u00e9di\u00e9 \u00e0 \u00ab\u00a0l’Intelligence Artificielle pour HPC@Exscale\u00a0\u00bb en ciblant les deux sujets \u00ab\u00a0Image analysis @ exascale\u00a0\u00bb et \u00ab\u00a0Data analysis and robust inference @ exascale\u00a0\u00bb. Il s’est d\u00e9roul\u00e9 les 2 et 3 octobre 2024 \u00e0 l’Espace La Bruy\u00e8re, Du C\u00f4t\u00e9 de la Trinit\u00e9<\/em> (DCT)<\/em> \u00e0 Paris. <\/strong><\/p>\n

<\/strong>[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text uncode_shortcode_id=\u00a0\u00bb130128″]This face-to-face workshop brought together, for two days, Exa-DI members, members of the other NumPEx projects (Exa-MA: Methods and Algorithms for Exascale, Exa-SofT: HPC Software and Tools, Exa-DoST: Data-oriented Software and Tools for the Exascale and Exa-AToW: Architectures and Tools for Large-Scale Workflows), Application demonstrators (ADs) from various research and industry sectors and Experts to discuss advancements and future directions for integration of Artificial Intelligence into HPC\/HPDA workflows at exascale targeting the two topics, \u201cLarge image analysis\u201d and \u201cData analysis and robust inference\u201d.<\/p>\n

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This workshop is the third co-design\/co-development workshops in the series whose main objective is to promote software stack co-development strategies to accelerate exascale development and performance portability of computational science and engineering applications. This workshop is a little different from the previous two in that it has a prospective character targeting the increasing importance of rapidly evolving AI-driven and AI-coupled HPC\/HPDA workflows in \u201cLarge images analysis @ exascale\u201d and \u201cData analysis (simulation, experiments, observation) & robust inference @ exascale\u201d. Its main objectives are first to co-develop a shared understanding of the different modes of coupling AI into HPC\/HPDA workflows, second to co-identify execution motifs most commonly found\u00a0 in scientific applications in order to drive the co-development of collaborative specific benchmarks or proxy apps allowing to evaluate\/measure end-to-end performance of AI-coupled HPC\/HPDA workflows and finally, to co-identify \u00a0software components (libraries, frameworks, data communication, workflow tools, abstraction layers, programming and execution environments) to be co-developed and integrated to improve critical components and accelerate them.[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column width=\u00a0\u00bb1\/1″][vc_custom_heading uncode_shortcode_id=\u00a0\u00bb183310″]Principales sessions[\/vc_custom_heading][vc_column_text uncode_shortcode_id=\u00a0\u00bb519209″]<\/p>\n