Descripción del proyecto
Un procesamiento gráfico innovador para afrontar retos sociales
Los investigadores europeos están dando pasos importantes en el procesamiento de gráficos y la informática sin servidor. El equipo del proyecto Graph-Massivizer, financiado con fondos europeos, creará una plataforma de alto rendimiento, escalable y sostenible para el tratamiento de la información y el razonamiento basado en la representación gráfica masiva de datos extremos. Creará cinco herramientas informáticas de código abierto y conjuntos de datos gráficos localizables, accesibles, interoperables y reutilizables (FAIR, por sus siglas en inglés). Las herramientas se centrarán en la usabilidad integral (ingestión extrema de datos y creación masiva de gráficos), la inteligencia automatizada (análisis y razonamiento), la modelización del rendimiento y las compensaciones en materia de sostenibilidad ambiental. En el proyecto se validará la innovación en cuatro casos de uso complementarios que abarcan la economía, la sociedad y el medio ambiente. Se espera duplicar la eficiencia energética de los centros de datos y reducir en más de un 25 % las emisiones de gases de efecto invernadero de las operaciones gráficas básicas.
Objetivo
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.
Ámbito científico
- 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
Palabras clave
Programa(s)
Régimen de financiación
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinador
9020 Klagenfurt am Wörthersee
Austria