Antonio Pena

This group is recently formed and organized in two teams, driven by leading experts in the fields of accelerator and memories for high-performance computing. Since 2017, the group members have publised 40+ peer-reviewed indexed articles, and have gained a Juan de la Cierva Felloswhip, a Marie Sklodowska-Curie Individual Fellowship, a Ramón y Cajal currently in place,...

Deep learning (DL) is widely used to solve classification problems previously unchallenged, such as face recognition, and presents clear use cases for privacy requirements. Homomorphic encryption (HE) enables operations upon encrypted data, at the expense of vast data size increase. RAM sizes currently limit the use of HE on DL to severely reduced use cases. Recently emerged...

EPEEC's main goal is to develop and deploy a production-ready parallel programming environment that turns upcoming overwhelmingly-heterogeneous exascale supercomputers into manageable platforms for domain application developers. The consortium will significantly advance and integrate existing state-of-the-art components based on European technology (programming models, runtime systems, and...

Heterogeneous Memory Systems; Profiling; Runtime Systems; Programming Models Supercomputers are a key tool for professionals from many disciplines to address society challenges, enabling them to perform, e.g., climate change simulations or genome analysis. EC's HPC Strategy, implemented in H2020, devises the need to bring Europe's high-performance computing technology to the...