Project description
Innovative graph processing addressing societal challenges
European researchers are making important strides in graph processing and serverless computing. The EU-funded Graph-Massivizer project will develop a high-performance, scalable and sustainable platform for information processing and reasoning relying on the massive graph representation of extreme data. It will deliver five open-source software tools and FAIR graph data sets. The tools will focus on holistic usability (extreme data ingestion and massive graph creation), automated intelligence (analytics and reasoning), performance modelling and environmental sustainability trade-offs. The project will validate the innovation on four complementary use cases covering the economy, society and the environment. It expects to show a two-fold improvement in data centre energy efficiency and over 25 % lower greenhouse gas emissions for basic graph operations.
Objective
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.
Fields of science
- 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
Keywords
Programme(s)
Funding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
9020 Klagenfurt am Wörthersee
Austria