SAGE

SAGE

CoordinatorTechnology Strategy Board ; Royal Institute of Technology ; BULL SAS ; German Research Centre for Artificial Intelligence ; SCIENCE AND TECHNOLOGY FACILITIES COUNCIL ; SEAGATE SYSTEMS UK LIMITED ; Atomic Energy and Alternative Energies Commission ; Allinea Software (United Kingdom) ; Diamond Light Source ; ARM LIMITED ; United Kingdom Space Agency ; Forschungszentrum Jülich
Grant period2015-09-01 - 2018-08-31
Funding bodyEuropean Union
Call numberH2020-FETHPC-2014
Grant number671500
IdentifierG:(EU-Grant)671500

Note: Worldwide data volumes are exploding and islands of storage remote from compute will not scale. We will demonstrate the first instance of intelligent data storage, uniting data processing and storage as two sides of the same rich computational model. This will enable sophisticated, intention-aware data processing to be integrated within a storage systems infrastructure, combined with the potential for Exabyte scale deployment in future generations of extreme scale HPC systems. Enabling only the salient data to flow in and out of compute nodes, from a sea of devices spanning next generation solid state to low performance disc we enable a vision of a new model of highly efficient and effective HPC and Big Data demonstrated through the SAGE project. Objectives - Provide a next-generation multi-tiered object-based data storage system (hardware and enabling software) supporting future-generation multi-tier persistent storage media supporting integral computational capability, within a hierarchy. - Significantly improve overall scientific output through advancements in systemic data access performance and drastically reduced data movements. - Provides a roadmap of technologies supporting data access for both Exascale/Exabyte and High Performance Data Analytics. - Provide programming models, access methods and support tools validating their usability, including ‘Big-Data’ access and analysis methods - Co-Designing and validating on a smaller representative system with earth sciences, meteorology, clean energy, and physics communities - Projecting suitability for extreme scaling through simulation based on evaluation results. Call Alignment: We address storage data access with optimised systems for converged Big Data and HPC use, in a co-design process with scientific partners and applications from many domains. System effectiveness and power efficiency are dramatically improved through minimized data transfer, with extreme scaling and resilience.
     

Recent Publications

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http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Conference Presentation (Plenary/Keynote)
HPC Systems in the Next Decade - What to Expect, When, Where
24th International Conference on Computing in High Energy and Nuclear Physics, CHEP 2019, AdelaideAdelaide, Australia, 4 Nov 2019 - 8 Nov 20192019-11-042019-11-08 OpenAccess  Download fulltext Files  Download fulltextFulltext by OpenAccess repository BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;  ;  ;  ;  ;  ;  ;  ;
SAGE: Percipient Storage for Exascale Data Centric Computing
Parallel computing 83, 22-33 () [10.1016/j.parco.2018.03.002] OpenAccess  Download fulltext Files  Download fulltextFulltext by OpenAccess repository BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article
JSCs Horizon 2020
Innovatives Supercomputing in Deutschland 13(2), 64 () OpenAccess  Download fulltext Files  Download fulltextFulltext Download fulltextFulltext by OpenAccess repository BibTeX | EndNote: XML, Text | RIS

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 Record created 2015-09-13, last modified 2023-02-07



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