Descrizione del progetto
Serbatoi di nanomagneti possono rafforzare la potenza di elaborazione
La potenza di elaborazione fatica a tenere il passo con le richieste di analisi, vista la continua crescita esponenziale della generazione dei dati. La creazione di nuove piattaforme per l’elaborazione dei dati a parallelismo massivo, in cui grandi volumi di dati vengono processati «tutti in una volta» invece che pezzo per pezzo, è fondamentale per colmare questo divario. Ora, SpinENGINE combina due concetti rivoluzionari, il reservoir computing e la dinamica degli insiemi di nanomagneti, per realizzare questa visione. Il reservoir computing utilizza un serbatoio con dinamiche altamente non lineari che proietta segnali in ingresso su spazi ad alta dimensionalità e impiega tecniche di elaborazione lineari semplici per estrarre un risultato. SpinENGINE utilizza le interazioni non lineari emergenti e sintonizzabili negli insiemi di nanomagneti come serbatoio per creare un nuovo dispositivo computazionale a parallelismo massivo.
Obiettivo
The SpinENGINE project will lay the foundations for a new, massively parallel, computational platform based on emergent behaviour in large nanomagnet ensembles. The project will develop an efficient, highly scalable, and easily reproducible platform meeting the data analysis challenges in our increasingly data-rich society. We will build upon our recent discoveries and use complex, nonlinear, and highly tunable interactions in such ensembles to realize a hardware platform for “Reservoir Computing”, a biologically-inspired computational approach. Our critical hypothesis is that the synergies between the inherent properties of nanomagnet ensembles and those required for reservoir computing will enable the efficient creation of a highly adaptive computational platform for the analysis of complex, dynamic data sets. This has the potential to greatly outperform current approaches using conventional CMOS hardware.
SpinENGINE will bring together a multidisciplinary team of researchers with expertise in computer science, condensed matter physics, material science, computational modelling, and high-resolution microscopy. This will enable us to simultaneously explore the fundamental behaviours of nanomagnet ensembles and understand how these can be harnessed for useful computation. By the end of the project, we aim to fabricate a proof-of-concept device capable of solving pattern recognition and classification problems, and, in collaboration with our industrial partner, IBM, produce a roadmap to the further scaling and commercialization of our computational platform. Success in the SpinENGINE project will have vast implications for data analysis at all scales, ranging from low power computation in the simplest sensor node to accelerated data processing in the most complex supercomputer.
Campo scientifico
- natural sciencesphysical sciencescondensed matter physics
- natural sciencesphysical sciencesopticsmicroscopy
- natural sciencescomputer and information sciencesartificial intelligencepattern recognition
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwaresupercomputers
- natural sciencescomputer and information sciencesdata sciencedata processing
Parole chiave
Programma(i)
Invito a presentare proposte
Vedi altri progetti per questo bandoBando secondario
H2020-FETOPEN-2018-2019-2020-01
Meccanismo di finanziamento
RIA - Research and Innovation actionCoordinatore
7491 Trondheim
Norvegia