EUPEX

EUROPEAN PILOT FOR EXASCALE

Grant period2022-01-01 - 2025-12-31
Funding bodyEuropean Union
Call numberH2020-JTI-EuroHPC-2020-1
Grant number101033975
Further information: CORDIS Homepage
IdentifierG:(EU-Grant)101033975

Note: The EUPEX consortium aims to design, build, and validate the first EU platform for HPC, covering end-to-end the spectrum of required technologies with European assets: from the architecture, processor, system software, development tools to the applications. The EUPEX prototype will be designed to be open, scalable and flexible, including the modular OpenSequana-compliant platform and the corresponding HPC software ecosystem for the Modular Supercomputing Architecture. Scientifically, EUPEX is a vehicle to prepare HPC, AI, and Big Data processing communities for upcoming European Exascale systems and technologies. The hardware platform is sized to be large enough for relevant application preparation and scalability forecast, and a proof of concept for a modular architecture relying on European technologies in general and on European Processor Technology (EPI) in particular. In this context, a strong emphasis is put on the system software stack and the applications. Being the first of its kind, EUPEX sets the ambitious challenge of gathering, distilling and integrating European technologies that the scientific and industrial partners use to build a production-grade prototype. EUPEX will lay the foundations for Europe's future digital sovereignty. It has the potential for the creation of a sustainable European scientific and industrial HPC ecosystem and should stimulate science and technology more than any national strategy (for numerical simulation, machine learning and AI, Big Data processing). The EUPEX consortium – constituted of key actors on the European HPC scene – has the capacity and the will to provide a fundamental contribution to the consolidation of European supercomputing ecosystem. EUPEX aims to directly support an emerging and vibrant European entrepreneurial ecosystem in AI and Big Data processing that will leverage HPC as a main enabling technology.
   

Recent Publications

All known publications ...
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http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Software  ;  ;
JURI (v2.3.1)
[10.5281/ZENODO.12706831] BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Conference Presentation (Other)
European System Architecture Advancements
EuroHPC Summit 2024, AntwerpAntwerp, Belgium, 18 Mar 2024 - 21 Mar 20242024-03-182024-03-21 [10.34734/FZJ-2025-00116] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Poster (After Call)  ;  ;
Mastering HPC Monitoring Data: From Zero to Hero with LLview
ISC High Performance 2024, ISC24, HamburgHamburg, Germany, 12 May 2024 - 16 May 20242024-05-122024-05-16 [10.34734/FZJ-2024-06906] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;  ;  ;  ;  ;  ;
Vectorized Highly Parallel Density-Based Clustering for Applications With Noise
IEEE access 12, 181679 - 181692 () [10.1109/ACCESS.2024.3507193] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Software  ;  ;  ;
LLview (v2.3.0-base)
[10.5281/ZENODO.10221407] BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Master Thesis  ;  ;  ;
Distributed memory parallelization of CubeLib library using MPI
86 pp. () [10.34734/FZJ-2024-02140] = Masterarbeit, Bergische Universität Wuppertal, 2024 OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Software  ;  ;
JURI (v2.2.1)
[10.5281/ZENODO.10232592]   Download fulltextFulltext BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Software  ;  ;
JURI (v2.2.0)
[10.5281/ZENODO.10232353]   Download fulltextFulltext BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Software  ;  ;  ;
LLview (v2.2.0-base)
[10.5281/ZENODO.10221408]   Download fulltextFulltext BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Contribution to a conference proceedings/Contribution to a book  ;  ;  ;  ;
Challenges and Opportunities in the Adoption of High Performance Computing for Earth Observation in the Exascale Era
Proceedings of the 2023 Conference on Big Data from Space (BiDS’23) - From foresight to impact
Conference on Big Data from Space 2023, BiDS’23, ViennaVienna, Austria, 6 Nov 2023 - 9 Nov 20232023-11-062023-11-09
Publications Office of the European Union 25-28 () [10.2760/46796]  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

All known publications ...
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 Record created 2022-04-19, last modified 2023-02-13


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