Country: Italy

Recent successes have established the potential of parallel-in-time integration as a powerful algorithmic paradigm to unlock the performance of Exascale systems

To achieve high performance and high energy efficiency on near-future exascale computing systems, a technology gap needs to be bridged.

In order to enable Exascale computing, next generation interconnection networks must scale to hundreds of thousands of nodes, and must provide features to also allow the HPC, HPDA, and AI applications to reach Exascale

With climate change being described as the greatest threat facing modern humans ever, it’s necessary to develop the tools needed to prepare for its potential future effects. Machine learning can help improve weather and climate modelling.

The eProcessor ecosystem combines open source software (SW) and hardware (HW) to deliver the first completely open source European full stack ecosystem

The growing need to process extremely large data sets is one of the main drivers for building exascale HPC systems today.