Projektbeschreibung
Revolutionäre Datenspeicherung in den Bereichen Extreme-Scale-Computing und KI
Die Landschaft des Hochleistungsrechnens entwickelt sich aufgrund der riesigen Datenmengen immer weiter, die von wissenschaftlichen Instrumenten, Sensoren und Simulationen erzeugt werden. Um diese Daten effizient zu speichern, zu verarbeiten und zu analysieren, müssen die bestehenden Speichertechnologien angepasst werden, um höhere Effizienzen zu erreichen. Das Ziel des EU-finanzierten Projekts Sage2, das auf der SAGE-Plattform aufbaut, besteht in der Validierung eines Speichersystems der nächsten Generation, das den neuen Anforderungen des Extreme-Scale-Computing und von KI/Deep Learning gerecht wird. Diese moderne Speicherinfrastruktur wird den wissenschaftlichen Durchsatz, die Skalierbarkeit, die Zeit- und Energieeffizienz sowie die Gesamtproduktivität im Zusammenhang mit Entwicklung und Nutzung verbessern.
Ziel
The landscape for High Performance Computing is changing with the proliferation of enormous volumes of data created by scientific instruments and sensors, in addition to data from simulations. This data needs to be stored, processed and analysed, and existing storage system technologies in the realm of extreme computing need to be adapted to achieve reasonable efficiency in achieving higher scientific throughput. We started on the journey to address this problem with the SAGE project. The HPC use cases and the technology ecosystem is now further evolving and there are new requirements and innovations that are brought to the forefront. It is extremely critical to address them today without “reinventing the wheel” leveraging existing initiatives and know-how to build the pieces of the Exascale puzzle as quickly and efficiently as we can.
The SAGE paradigm already provides a basic framework to address the extreme scale data aspects of High Performance Computing on the path to Exascale. Sage2 (Percipient StorAGe for Exascale Data Centric Computing 2) intends to validate a next generation storage system building on top of the already existing SAGE platform to address new use case requirements in the areas of extreme scale computing scientific workflows and AI/deep learning leveraging the latest developments in storage infrastructure software and storage technology ecosystem.
Sage2 aims to provide significantly enhanced scientific throughput, improved scalability, and, time & energy to solution for the use cases at scale. Sage2 will also dramatically increase the productivity of developers and users of these systems.
This proposal is aligned to FETHPC-02 - 2017:part (c). Sage2 provides a highly performant and resilient, QoS capable multi tiered storage system, with data layouts across the tiers managed by the Mero Object Store, which is capable of handling in-transit/in-situ processing of data within the storage system, accessible through the Clovis API.
Wissenschaftliches Gebiet
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencesbiological sciencesecologyecosystems
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwaresupercomputers
Programm/Programme
Thema/Themen
Aufforderung zur Vorschlagseinreichung
Andere Projekte für diesen Aufruf anzeigenUnterauftrag
H2020-FETHPC-2017
Finanzierungsplan
RIA - Research and Innovation actionKoordinator
PO9 1SA Havant
Vereinigtes Königreich