Description du projet
Un traitement innovant des graphes pour relever les défis sociétaux
Les chercheurs européens réalisent des avancées importantes dans le traitement des graphes et l’informatique sans serveur. Le projet Graph-Massivizer, financé par l’UE, développera une plateforme performante, évolutive et durable pour le traitement de l’information et le raisonnement s’appuyant sur la représentation graphique massive de données extrêmes. Il fournira cinq outils logiciels libres et des ensembles de données graphiques FAIR. Les outils se concentreront sur la facilité d’utilisation globale (ingestion de données extrêmes et création de graphes massifs), l’intelligence automatisée (analyse et raisonnement), la modélisation des performances et les compromis de durabilité environnementale. Le projet validera l’innovation sur quatre cas d’utilisation complémentaires couvrant l’économie, la société et l’environnement. Il devrait permettre de doubler l’efficacité énergétique des centres de données et de réduire de plus de 25 % les émissions de gaz à effet de serre pour les opérations de base sur les graphes.
Objectif
Graph-Massivizer researches and develops a high-performance, scalable, and sustainable platform for information processing and reasoning based on the massive graph representation of extreme data. It delivers a toolkit of five open-source software tools and FAIR graph datasets covering the sustainable lifecycle of processing extreme data as massive graphs. The tools focus on holistic usability (from extreme data ingestion and massive graph creation), automated intelligence (through analytics and reasoning), performance modelling, and environmental sustainability tradeoffs, supported by credible data-driven evidence across the computing continuum. The automated operation based on the emerging serverless computing paradigm supports experienced and novice stakeholders from a broad group of large and small organisations to capitalise on extreme data through massive graph programming and processing.
Graph Massivizer validates its innovation on four complementary use cases considering their extreme data properties and coverage of the three sustainability pillars (economy, society, and environment): sustainable green finance, global environment protection foresight, green AI for the sustainable automotive industry, and data centre digital twin for exascale computing. Graph Massivizer promises 70% more efficient analytics than AliGraph, and 30% improved energy awareness for ETL storage operations than Amazon Redshift. Furthermore, it aims to demonstrate a possible two-fold improvement in data centre energy efficiency and over 25% lower GHG emissions for basic graph operations.
Graph-Massivizer gathers an interdisciplinary group of twelve partners from eight countries, covering four academic universities, two applied research centres, one HPC centre, two SMEs and two large enterprises. It leverages the world-leading roles of European researchers in graph processing and serverless computing and uses leadership-class European infrastructure in the computing continuum.
Champ scientifique
- natural sciencescomputer and information sciencessoftware
- engineering and technologymechanical engineeringvehicle engineeringautomotive engineering
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwaresupercomputers
- natural sciencescomputer and information sciencesdata sciencedata processing
Mots‑clés
Programme(s)
Régime de financement
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinateur
9020 Klagenfurt am Wörthersee
Autriche