000205234 001__ 205234
000205234 005__ 20230207130313.0
000205234 0247_ $$2CORDIS$$aG:(EU-Grant)671500$$d671500
000205234 0247_ $$2CORDIS$$aG:(EU-Call)H2020-FETHPC-2014$$dH2020-FETHPC-2014
000205234 0247_ $$2originalID$$acorda__h2020::671500
000205234 035__ $$aG:(EU-Grant)671500
000205234 150__ $$aSAGE$$y2015-09-01 - 2018-08-31
000205234 371__ $$aTechnology Strategy Board$$bUKRI$$dUnited Kingdom$$ehttps://www.ukri.org/$$vCORDIS
000205234 371__ $$aRoyal Institute of Technology$$bKTH$$dSweden$$ehttp://www.kth.se/en$$vCORDIS
000205234 371__ $$aBULL SAS$$bBULL$$dFrance$$ehttp://www.bull.com$$vCORDIS
000205234 371__ $$aGerman Research Centre for Artificial Intelligence$$bDFKI$$dGermany$$ehttps://www.dfki.de/web$$vCORDIS
000205234 371__ $$aSCIENCE AND TECHNOLOGY FACILITIES COUNCIL$$bSTFC$$dUnited Kingdom$$ehttp://www.scitech.ac.uk$$vCORDIS
000205234 371__ $$aSEAGATE SYSTEMS UK LIMITED$$bSEAGATE SYSTEMS$$dUnited Kingdom$$vCORDIS
000205234 371__ $$aAtomic Energy and Alternative Energies Commission$$bCEA$$dFrance$$ehttp://www.cea.fr/$$vCORDIS
000205234 371__ $$aAllinea Software (United Kingdom)$$bAllinea Software (United Kingdom)$$dUnited Kingdom$$ehttp://www.allinea.com/$$vCORDIS
000205234 371__ $$aDiamond Light Source$$bDiamond Light Source$$dUnited Kingdom$$ehttp://www.diamond.ac.uk/Home.html$$vCORDIS
000205234 371__ $$aARM LIMITED$$bARM$$dUnited Kingdom$$vCORDIS
000205234 371__ $$aUnited Kingdom Space Agency$$bUKSA$$dUnited Kingdom$$ehttps://www.gov.uk/government/organisations/uk-space-agency$$vCORDIS
000205234 371__ $$aForschungszentrum Jülich$$bForschungszentrum Jülich$$dGermany$$ehttps://www.ptj.de/$$vCORDIS
000205234 372__ $$aH2020-FETHPC-2014$$s2015-09-01$$t2018-08-31
000205234 450__ $$aSAGE$$wd$$y2015-09-01 - 2018-08-31
000205234 5101_ $$0I:(DE-588b)5098525-5$$2CORDIS$$aEuropean Union
000205234 680__ $$aWorldwide 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.
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000205234 970__ $$aoai:dnet:corda__h2020::4755a7ad01d82ddd998fc5f2cad5994b
000205234 980__ $$aG
000205234 980__ $$aCORDIS
000205234 980__ $$aAUTHORITY