OSCAR in the EOSC Marketplace
The AI-SPRINT partners, from Universitat Politècnica de València (UPV) and Politecnico di Milano (POLIMI), involved in the OSCAR development, and the...
Learn moreThe AI-SPRINT components include design tools, runtime framework and deployable infrastructures used to build the project's architectural infrastructure
AI-SPRINT - Unleashing the potential of Artificial Intelligence and Edge Computing in three thematic use cases
The AI-SPRINT Alliance is composed of a group of experts that adopts the AI-SPRINT components and tools with technical support from the project's partners, offering benefits from both AI and Edge European Innovations demand and supply sides.
The new EU research initiative set to drive innovation for Artificial Intelligence applications in cloud and edge environments.
The AI-SPRINT partners, from Universitat Politècnica de València (UPV) and Politecnico di Milano (POLIMI), involved in the OSCAR development, and the...
Learn moreThe Barcelona Supercomputing Center - National Supercomputing Center (BSC-CNS) is one of the main participants of the BitsxlaMarató hackathon this...
Learn moreAI-SPRINT and EGI have started a strong cooperation that allow the project to exploit the EGI services to built its tools. Read more!
Learn moreFoundation models have the potential to become the most used infrastructures on which other apps are built. However, if any shortfalls are present on...
Learn moreThe AI-SPRINT personalised healthcare use case is the first of the series of webinars that aims to present the use cases developed by our project team...
Learn moreThe goal of the FastContinuum2023 workshop is to foster discussion and collaboration among researchers from cloud/edge/fog/computing continuum and performance analysis communities, to share the relevant topics and results of the current approaches. The workshop is co-organised by the projects AI-SPRINT, PIACERE and SWForum.
ScaDL (Scalable Deep Learning over Parallel And Distributed Infrastructures) has arrived at its fifth edition. This year, the conference welcomes research papers focused on distributed deep learning aiming to achieve efficiency and scalability for deep learning jobs over distributed and parallel systems. Read more!