Country: Switzerland

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.

DEEP-SEA (“DEEP – Software for Exascale Architectures”) will deliver the programming environment for future European exascale systems, adapting all levels of the software (SW) stack – including low-level drivers, computation

DCoMEX will fuse physics-constrained machine learning (ML), statistical methods and large scale linear algebra solvers to address extremely demanding computational mechanics problems. It will develop an open source, user friendly and customisable computational mechanics framework that harnesses the capabilities of next generation European Exascale systems.