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 aims to enhance the energy efficiency of deep learning systems by developing innovative memory devices that allow for stationary synaptic weights. By utilizing advanced materials and novel designs, it seeks to improve the performance of artificial intelligence applications.
A major challenge for deep learning inference is the high energy demand required to retrieve large amounts of synaptic weight data from memory.
One promising approach to address this is the use of conductance-based devices, such as non-volatile phase-change memory, to develop chips with stationary synaptic weights.
However, two key obstacles remain: enhancing the computational capabilities and increasing the energy efficiency of these devices. INFUSED tackles both issues through groundbreaking d…
IBM RESEARCH GMBH
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 topics.
Guests see up to 5 keywords.
