{"id":3567,"date":"2026-08-15T23:49:43","date_gmt":"2026-08-15T21:49:43","guid":{"rendered":"https:\/\/numpex.org\/projets-appel-a-projets-2025\/"},"modified":"2026-08-17T14:26:27","modified_gmt":"2026-08-17T12:26:27","slug":"projets-appel-a-projets-2025","status":"publish","type":"page","link":"https:\/\/numpex.org\/fr\/projets-appel-a-projets-2025\/","title":{"rendered":"Projets \u2013 Appel \u00e0 projets 2025"},"content":{"rendered":"

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uncode_shortcode_id=\u00a0\u00bb690316″]Quatre nouveaux projets issus de l’appel \u00e0 projets 2025[\/vc_custom_heading][vc_column_text text_lead=\u00a0\u00bbyes\u00a0\u00bb uncode_shortcode_id=\u00a0\u00bb642992″]<\/p>\n

Le programme NumPEx lance son premier appel \u00e0 projets afin de soutenir les avanc\u00e9es dans les domaines du calcul haute performance (HPC), de l’analyse de donn\u00e9es haute performance (HPDA) et de l’intelligence artificielle (IA). Notre programme de recherche \u00ab France 2030 \u00bb vise \u00e0 d\u00e9velopper des logiciels capables de faire fonctionner les futures machines exascale, ainsi qu\u2019\u00e0 pr\u00e9parer les principaux codes d\u2019application scientifiques et industriels. <\/p>\n

[\/vc_column_text][vc_column_text text_lead=\u00a0\u00bbyes\u00a0\u00bb text_color=\u00a0\u00bbcolor-177487″ uncode_shortcode_id=\u00a0\u00bb103959″ text_color_type=\u00a0\u00bbuncode-palette\u00a0\u00bb]<\/p>\n

Cet appel \u00e0 projets s’articule autour de trois axes :<\/strong><\/p>\n

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empty_h=\u00a0\u00bb2″][vc_column_text uncode_shortcode_id=\u00a0\u00bb171502″]L’entra\u00eenement de mod\u00e8les d’IA \u00e0 grande \u00e9chelle pose des d\u00e9fis majeurs, notamment en termes de co\u00fbt de calcul et d’efficacit\u00e9 \u00e9nerg\u00e9tique. Ce projet s’attache \u00e0 r\u00e9soudre ces probl\u00e8mes en d\u00e9veloppant une nouvelle pile logicielle d\u00e9di\u00e9e \u00e0 l’apprentissage profond \u00e0 grande \u00e9chelle, fond\u00e9e sur une int\u00e9gration \u00e9troite des avanc\u00e9es algorithmiques, de l’optimisation au niveau des syst\u00e8mes et de cas d’utilisation concrets. Il s’inscrit directement dans les priorit\u00e9s du programme PEPR NumPEx consacr\u00e9 au calcul haute performance (HPC) pour l’IA.[\/vc_column_text][vc_empty_space 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empty_h=\u00a0\u00bb2″][vc_column_text text_lead=\u00a0\u00bbyes\u00a0\u00bb uncode_shortcode_id=\u00a0\u00bb809398″]Comment coordonner \u00e0 la fois le choix du niveau de fid\u00e9lit\u00e9, les m\u00e9thodes d’optimisation et l’allocation des ressources dans un environnement exascale ?<\/strong>[\/vc_column_text][vc_column_text uncode_shortcode_id=\u00a0\u00bb171502″]Le projet SAGE-HPC vise \u00e0 d\u00e9velopper une plateforme logicielle \u00e9volutive, ouverte et interop\u00e9rable destin\u00e9e \u00e0 l’optimisation multifid\u00e9lit\u00e9 de probl\u00e8mes physiques complexes dans des environnements de calcul haute performance (HPC) \u00e0 l’exascale. La r\u00e9solution de ces probl\u00e8mes d\u2019optimisation constitue un d\u00e9fi scientifique majeur en raison de la complexit\u00e9 des ph\u00e9nom\u00e8nes physiques en jeu et du co\u00fbt de calcul associ\u00e9 aux simulations \u00e0 haute fid\u00e9lit\u00e9. Pour relever ce d\u00e9fi, le projet s’appuie \u00e0 la fois sur l’utilisation coordonn\u00e9e de mod\u00e8les \u00e0 fid\u00e9lit\u00e9 variable \u2014 o\u00f9 des mod\u00e8les simplifi\u00e9s et peu co\u00fbteux guident l’exploration de l’espace des solutions, tandis que des mod\u00e8les \u00e0 haute fid\u00e9lit\u00e9 sont utilis\u00e9s de mani\u00e8re s\u00e9lective pour affiner les r\u00e9sultats \u2014 et sur l’exploitation massive des ressources HPC exascale, permettant ainsi un traitement parall\u00e8le \u00e0 grande \u00e9chelle de ces approches.[\/vc_column_text][vc_empty_space 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empty_h=\u00a0\u00bb2″][vc_column_text text_lead=\u00a0\u00bbyes\u00a0\u00bb uncode_shortcode_id=\u00a0\u00bb166332″]Une pile logicielle open source destin\u00e9e aux supercalculateurs exascale bas\u00e9s sur des GPU, s’appuyant sur le mod\u00e8le de programmation Kokkos.<\/strong>[\/vc_column_text][vc_column_text uncode_shortcode_id=\u00a0\u00bb171502″]Le projet KOKTAILS vise \u00e0 am\u00e9liorer la portabilit\u00e9 des logiciels de simulation sur les architectures de calcul exascale, en contribuant au d\u00e9veloppement d\u2019une pile logicielle souveraine adapt\u00e9e aux supercalculateurs bas\u00e9s sur des GPU. Il s\u2019inscrit dans la strat\u00e9gie PEPR de NumPEx et contribue \u00e0 la souverainet\u00e9 num\u00e9rique fran\u00e7aise en mati\u00e8re de calcul haute performance (HPC). Il comprend le d\u00e9veloppement d\u2019un middleware \u00e9volutif visant \u00e0 garantir la portabilit\u00e9 des performances sur diverses architectures GPU, y compris des processeurs europ\u00e9ens tels que SiPearl Rhea. Le projet contribue ainsi \u00e0 la transition des applications existantes vers le calcul exascale, gr\u00e2ce \u00e0 la cr\u00e9ation d\u2019un \u00e9cosyst\u00e8me open source conforme \u00e0 la politique europ\u00e9enne en mati\u00e8re de souverainet\u00e9.[\/vc_column_text][vc_empty_space empty_h=\u00a0\u00bb2″][vc_raw_html]<!-- ============================================================
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</style><p class="npx-c25-kok__kicker">Project structure</p><div class="npx-c25-kok"><div class="npx-c25-kok__card npx-c25-kok__card--wp1"><div class="npx-c25-kok__hd"><span aria-hidden="true" style="display:flex"><svg width="22" height="22" viewBox="0 0 24 24" fill="none"><path d="M4 7h11l-3-3M20 17H9l3 3" stroke="currentColor" stroke-width="1.8" stroke-linecap="round" stroke-linejoin="round"></path><rect x="3.2" y="12.2" width="6" height="6" rx="1.4" stroke="currentColor" stroke-width="1.7"></rect><rect x="14.8" y="5.8" width="6" height="6" rx="1.4" stroke="currentColor" stroke-width="1.7"></rect></svg></span><span class="npx-c25-kok__wp">WP1</span></div><div class="npx-c25-kok__ttl">Legacy Code Migration</div><div class="npx-c25-kok__desc">Automated translation into GPU frameworks using Kokkos</div><div class="npx-c25-kok__alt">Tooling to support the transition to GPU with Kokkos</div></div><div class="npx-c25-kok__card npx-c25-kok__card--wp2"><div class="npx-c25-kok__hd"><span aria-hidden="true" style="display:flex"><svg width="22" height="22" viewBox="0 0 24 24" fill="none"><path d="M9 6.6 4.6 12 9 17.4M15 6.6 19.4 12 15 17.4" stroke="currentColor" stroke-width="1.8" stroke-linecap="round" stroke-linejoin="round"></path><path d="m13.2 4.6-2.4 14.8" stroke="currentColor" stroke-width="1.6" stroke-linecap="round"></path></svg></span><span class="npx-c25-kok__wp">WP2</span></div><div class="npx-c25-kok__ttl">Python and AI Integration</div><div class="npx-c25-kok__desc">Tools for Python and AI integration into simulation workflows</div><div class="npx-c25-kok__alt">Leveraging AI-oriented languages & tools in Kokkos</div></div><div class="npx-c25-kok__card npx-c25-kok__card--wp3"><div class="npx-c25-kok__hd"><span aria-hidden="true" style="display:flex"><svg width="22" height="22" viewBox="0 0 24 24" fill="none"><path d="M12 3.2 21 8v8l-9 4.8L3 16V8l9-4.8z" stroke="currentColor" stroke-width="1.7" stroke-linejoin="round"></path><path d="M3 8l9 4.8L21 8M12 12.8v8M7.5 5.6l9 9M16.5 5.6l-9 9" stroke="currentColor" stroke-width="1.4" stroke-linejoin="round"></path></svg></span><span class="npx-c25-kok__wp">WP3</span></div><div class="npx-c25-kok__ttl">Mesh Optimization</div><div class="npx-c25-kok__desc">Solutions for unstructured and high-dimensional mesh for Exascale</div><div class="npx-c25-kok__alt">GPU-efficient mesh management in Kokkos</div></div><div class="npx-c25-kok__card npx-c25-kok__card--wp4"><div class="npx-c25-kok__hd"><span aria-hidden="true" style="display:flex"><svg width="22" height="22" viewBox="0 0 24 24" fill="none"><path d="M4 6.5h9M17 6.5h3M4 17.5h3M11 17.5h9" stroke="currentColor" stroke-width="1.8" stroke-linecap="round"></path><circle cx="15" cy="6.5" r="2.4" stroke="currentColor" stroke-width="1.7"></circle><circle cx="9" cy="17.5" r="2.4" stroke="currentColor" stroke-width="1.7"></circle><path d="M4 12h16" stroke="currentColor" stroke-width="1.4" stroke-dasharray="2 2.4" stroke-linecap="round"></path></svg></span><span class="npx-c25-kok__wp">WP4</span></div><div class="npx-c25-kok__ttl">Hybrid Optimization</div><div class="npx-c25-kok__desc">Combining Kokkos’ static portability with StarPU’s dynamic scheduling</div><div class="npx-c25-kok__alt">Dynamic performance portability with Kokkos</div></div></div><div class="npx-c25-kok__band"><div class="npx-c25-kok__hd"><span aria-hidden="true" style="display:flex"><svg width="22" height="22" viewBox="0 0 24 24" fill="none"><rect x="3.4" y="13.6" width="7" height="7" rx="1.4" stroke="currentColor" stroke-width="1.8"></rect><rect x="13.6" y="13.6" width="7" height="7" rx="1.4" stroke="currentColor" stroke-width="1.8"></rect><rect x="8.5" y="3.4" width="7" height="7" rx="1.4" stroke="currentColor" stroke-width="1.8"></rect></svg></span><span class="npx-c25-kok__wp">WP5</span></div><div class="npx-c25-kok__ttl">Middleware Development</div><div class="npx-c25-kok__desc">Scalable tools for optimizing code execution on GPU architectures</div><div class="npx-c25-kok__alt">Shared building blocks & demonstrator support</div></div><div class="npx-c25-kok__base"><div class="npx-c25-kok__hd"><span aria-hidden="true" style="display:flex"><svg width="22" height="22" viewBox="0 0 24 24" fill="none"><rect x="5" y="4.4" width="14" height="16.2" rx="2" stroke="currentColor" stroke-width="1.8"></rect><path d="M9 3.4h6v2.6H9zM8.6 11h6.8M8.6 15h4.4" stroke="currentColor" stroke-width="1.7" stroke-linecap="round"></path></svg></span><span class="npx-c25-kok__wp">WP0</span></div><div class="npx-c25-kok__ttl">Management, dissemination and training</div></div><h3 class="npx-c25-kok__h3">Project targeted platforms, Apps or Proxy-apps</h3><div class="npx-c25-kok__chips"><div class="npx-c25-kok__row"><span class="npx-c25-kok__chip npx-c25-kok__chip--main">Arcane</span><span class="npx-c25-kok__chip npx-c25-kok__chip--main">TRUST</span></div><div class="npx-c25-kok__row"><span class="npx-c25-kok__chip">AVBP</span><span class="npx-c25-kok__chip">Gysela-X</span><span class="npx-c25-kok__chip">ShArc</span><span class="npx-c25-kok__chip">SoNICS</span></div></div>[\/vc_raw_html][\/vc_column_inner][\/vc_row_inner][vc_row_inner limit_content=\u00a0\u00bb\u00a0\u00bb][vc_column_inner width=\u00a0\u00bb1\/1″][vc_empty_space empty_h=\u00a0\u00bb2″][vc_separator sep_color=\u00a0\u00bbcolor-nhtu\u00a0\u00bb uncode_shortcode_id=\u00a0\u00bb794634″ sep_color_type=\u00a0\u00bbuncode-palette\u00a0\u00bb][vc_empty_space empty_h=\u00a0\u00bb2″ el_id=\u00a0\u00bbnav-astra\u00a0\u00bb][\/vc_column_inner][\/vc_row_inner][vc_row_inner row_inner_height_percent=\u00a0\u00bb0″ row_padding=\u00a0\u00bb0″ overlay_alpha=\u00a0\u00bb50″ gutter_size=\u00a0\u00bb3″ shift_y=\u00a0\u00bb0″ z_index=\u00a0\u00bb0″ uncode_shortcode_id=\u00a0\u00bb187167″ limit_content=\u00a0\u00bb\u00a0\u00bb][vc_column_inner column_width_percent=\u00a0\u00bb100″ 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Ces instruments g\u00e9n\u00e8rent des ensembles de donn\u00e9es volumineux et h\u00e9t\u00e9rog\u00e8nes, r\u00e9partis sur plusieurs sites, qui ne peuvent \u00eatre trait\u00e9s efficacement \u00e0 l\u2019aide des m\u00e9thodes traditionnelles de traitement des donn\u00e9es. Le projet vise \u00e0 surmonter ces goulots d\u2019\u00e9tranglement structurels en d\u00e9veloppant une plateforme num\u00e9rique unifi\u00e9e et \u00e9volutive qui f\u00e9d\u00e8re les ressources de calcul haute performance (HPC), de cloud et de stockage d\u2019objets. Elle permettra l\u2019ex\u00e9cution de flux de travail complexes (y compris le traitement bas\u00e9 sur l\u2019IA) sur des infrastructures h\u00e9t\u00e9rog\u00e8nes gr\u00e2ce \u00e0 des technologies modernes de conteneurisation. 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