Towards complex and intelligent workflow programming for Distributed Computing

With present computational capabilities and data volumes entering the Exascale Era, digital twins of the Earth system will be able to mimic the different system components (atmosphere, ocean, land, lithosphere) with unrivalled precision, providing analyses, forecasts, and what-if scenarios for natural hazards and resources from their genesis phases and across their temporal...

For Artificial Intelligence (AI) to become fully pervasive it needs resources at the edge of the network. The cloud can provide the processing power needed for big data, but edge computing is located close to where data are produced and is therefore crucial to their timely, flexible, and secure management.

AI-SPRINT will define a framework for...

Today developers lack tools that enable the development of complex workflows involving HPC simulation and modelling with data analytics (DA) and machine learning (ML). The eFlows4HPC project aims to deliver a workflow software stack and an additional set of services to enable the integration of HPC simulation and modelling with big data analytics and machinelearning in...

Fog computing brings cloud computing capabilities closer to the end-device and users, while enabling location-dependent resource allocation, low latency services, and extending significantly the IoT services portfolio as well as market and business opportunities in the cloud sector. With the number of devices exponentially growing globally, new cloud and fog models are...