CORDIS Project
Funding breakdown and partner intelligence are Premium
Sign in and upgrade to Premium for EU contribution totals, consortium analytics, OpenAlex research context, and AI summaries. · 0 consortium intelligence fields visible of 1
Start free • Cancel anytime • 14-day refund guarantee
This project focuses on developing new system architectures that leverage persistent memory technology to enable deep learning with homomorphic encryption. By addressing performance limitations, it aims to facilitate the execution of large encrypted models and datasets, enhancing privacy in machine learning application…
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 persistent memory technology (PMEM) offers larger-than-ever RAM spaces, but its performance is far from that of customary…
BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACION
Partner organizations (coordinator is shown above), with normalized type and CORDIS activity type. Guests see up to 4 partners.
Similar projects, consortium collaboration history, frequent partners, and OpenAlex research context.
Guests see up to 5 EuroSciVoc fields.
Guests see up to 5 topics.
Guests see up to 5 keywords.
