Graph-Massivizer

Massive Graph Processing of Extreme Data for a Sustainable Economy, Society, and Environment

Abstract

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 roperties 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 world-leading roles of European researchers in graph processing and serverless computing and uses leadership-class European infrastructure in the computing continuum.

Project details

Unibo Team Leader: Andrea Bartolini

Unibo involved Department/s:
Dipartimento di Ingegneria dell'Energia Elettrica e dell'Informazione "Guglielmo Marconi"

Coordinator:
Universitaet Klagenfurt(Austria)

Other Participants:
ALMA MATER STUDIORUM - Università di Bologna (Italy)

Total Eu Contribution: Euro (EUR) 4.998.062,50
Project Duration in months: 36
Start Date: 01/01/2023
End Date: 31/12/2025

Cordis webpage

This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101093202 This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101093202