GRAPH-MASSIVIZER
This project has received funding from the European Union’s Horizon Research and Innovation Actions under Grant Agreement Nº 101093202.

EU Project

Graph-Massivizer

GRAPH-MASSIVIZER Read more

PRESS RELEASE

Graph-Massivizer promotes climate-neutral and sustainable economic sectors boosted by graph data processing.

This project has received funding from the European Union’s Horizon Research and Innovation Actions under Grant Agreement Nº 101093202.

EU Project

Graph Massivizer

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Neuro-Symbolic AI
and Graph Tech

AI meets complex
knowledge structures:

About the Project

Graph-Massivizer

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.

Consortium

Graph-Massivizer gathers a consortium 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.

GRAPH MASSIVIZER PROJECT

Graph-Massivizer Software Tools

GRAPH MASSIVIZER

The project delivers the Graph-Massivizer toolkit of five open-source software (OSS) tools and FAIR graph datasets covering the sustainable lifecycle of processing extreme data as MG.

The tools focus on holistic
1. Usability
2. Automated intelligence
3. Performance modelling
4. Environmental sustainability tradeoffs supported by credible data-driven evidence
5. Across HPC systems and computing continuum

Graph-Massivizer Software Tools

The project delivers the Graph-Massivizer toolkit of five open-source software (OSS) tools and FAIR graph datasets covering the sustainable lifecycle of processing extreme data as MG.

The tools focus on holistic
1. Usability
2. Automated intelligence
3. Performance modelling
4. Environmental sustainability tradeoffs supported by credible data-driven evidence
5. Across HPC systems and computing continuum

Use Cases

GRAPH MASSIVIZER Data Centre Digital Twin for Sustainable Exascale Computing
GRAPH MASSIVIZER Green AI for Sustainable Automotive Industry
GRAPH MASSIVIZER Global Foresight for Environment Protection
GRAPH MASSIVIZER Green and Sustainable Finance

News

Blog

How we implemented scalable graph summarization

How we implemented scalable graph summarization

tl;dr k-bisimulation can be used to create a condensed version of a graph. This condensed version is a graph summary, keeping specific properties of the original k-bisimulation partitions the nodes of the graph in equivalence classes which we call blocks We create the...

Synthetic Data Powered Investment and Trading

Synthetic Data Powered Investment and Trading

Author: Laurentiu Vasiliu Peracton Ltd. In the ever-evolving world of finance, Synthetic Data Driven Investment and Trading is emerging as hybrid approach, where financial algorithms are not only powered by traditional financial data (historic and live), but also by...

Trading in the Matrix

Trading in the Matrix

Author: Laurentiu Vasiliu Peracton Ltd. Imagine a scenario where extreme quantities of synthetic data are continuously generated and used to train multiple generations of AI enhanced financial algorithms. In this scenario, financial algorithms train on making...

GRAPH MASSIVIZER