Descrizione del progetto
Rivoluzionare l’archiviazione dei dati nell’elaborazione su scala estrema e nell’intelligenza artificiale
Il panorama del calcolo ad alte prestazioni si sta evolvendo per via delle enormi quantità di dati generati da strumenti scientifici, sensori e simulazioni. Per archiviare, elaborare e analizzare questi dati in modo efficiente, è necessario adattare le esistenti tecnologie di archiviazione per ottenere una maggiore efficienza. Il progetto Sage2, finanziato dall’UE e basato sulla piattaforma SAGE, intende convalidare un sistema di archiviazione di nuova generazione che risponda ai nuovi requisiti dei casi d’uso nell’elaborazione su scala estrema e nell’IA/apprendimento profondo. Questa infrastruttura di archiviazione avanzata migliorerà il volume di produzione scientifico, la scalabilità, l’efficienza energetica e temporale e la produttività complessiva di sviluppatori e utenti.
Obiettivo
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.
Campo scientifico
- 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
Programma(i)
Argomento(i)
Invito a presentare proposte
Vedi altri progetti per questo bandoBando secondario
H2020-FETHPC-2017
Meccanismo di finanziamento
RIA - Research and Innovation actionCoordinatore
PO9 1SA Havant
Regno Unito