Description du projet
Révolutionner le stockage des données dans le cadre des supercalculateurs exaflopiques et de l’IA
Le paysage du calcul haute performance évolue sous l’impulsion des quantités massives de données générées par les instruments scientifiques, les capteurs et les simulations. Pour stocker, traiter et analyser efficacement ces données, les technologies de stockage actuelles doivent être adaptées de manière à offrir des rendements plus élevés. Le projet Sage2, financé par l’UE, qui s’appuie sur la plateforme SAGE, entend valider un système de stockage de nouvelle génération qui répond aux nouvelles exigences du domaine des supercalculateurs exaflopiques et de l’IA/apprentissage profond. Cette infrastructure de stockage avancée améliorera le débit scientifique, l’évolutivité, l’efficacité en termes de temps et d’énergie, ainsi que la productivité globale des développeurs et des utilisateurs.
Objectif
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.
Champ scientifique
- 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
Programme(s)
Régime de financement
RIA - Research and Innovation actionCoordinateur
PO9 1SA Havant
Royaume-Uni