Ferroelectric-enhanced analog accelerators for robust, ultra-low power edge intelligence

Bidragets beskrivning

A future driven by artificial intelligence (AI)-enhanced systems is expected to make our life easier, safer, or simply more entertaining. Yet, achieving these expectations in the realm of smart and interconnected devices (internet of things, 6G wireless communication, smart health monitoring, etc.) requires solving crucial challenges in the computation of AI models. Most importantly, computing these models on classical processors requires excessive computing power. In this project, we propose to investigate extremely energy-efficient neuromorphic computing, i.e., computing systems inspired by our brain, based on novel ferroelectric devices that are able to mimic biological computing mechanisms. We will create a library of these devices, fabricated and modelled, and ready to be integrated into typical computer-aided design tools used to design microelectronic systems. This also paves the way to building unique, multi-faceted neuromorphic expertise in Finland.
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Startår

2024

Slutår

2026

Beviljade finansiering



Sayani Majumdar Orcid -palvelun logo
399 664 €


Rollen i Finlands Akademis konsortium

Övriga parter i konsortiet

Partner
Aalto-universitetet (359046)
444 082 €
Partner
Aalto-universitetet (359046)
444 082 €
Leader
Uleåborgs universitet (359042)
304 328 €

Finansiär

Finlands Akademi

Typ av finansiering

Akademiprojekt med särskild inriktning

Övriga uppgifter

Finansieringsbeslutets nummer

359047

Vetenskapsområden

El-, automations- och telekommunikationsteknik, elektronik

Forskningsområden

Sähkötekniikka ja elektroniikka