KIT | KIT-Bibliothek | Impressum | Datenschutz

Highly-Bespoke Robust Printed Neuromorphic Circuits

Zhao, Haibin ORCID iD icon 1,2; Sapui, Brojogopal 2,3; Hefenbrock, Michael; Yang, Zhidong; Beigl, Michael 1,2; Tahoori, Mehdi B. 2,3
1 Institut für Telematik (TM), Karlsruher Institut für Technologie (KIT)
2 Fakultät für Informatik (INFORMATIK), Karlsruher Institut für Technologie (KIT)
3 Institut für Technische Informatik (ITEC), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

With the rapid growth of the Internet of Things, smart fast-moving consumer products, and wearable devices, requirements such as flexibility, non-toxicity, and low cost are desperately required. However, these requirements are usually beyond the reach of conventional rigid silicon technologies. In this regard, printed electronics offers a promising alternative. Combined with neuromorphic computing, printed neuromorphic circuits offer not only the aforementioned properties, but also compensate for some of the weaknesses of printed electronics, such as manufacturing variations, low device count, and high latency. Generally, (printed) neuromorphic circuits express their functionality through printed resistor crossbars to emulate matrix multiplication, and nonlinear circuitry to express activation functions. The values of the former are usually learned, while the latter is designed beforehand and considered fixed in training for all tasks. The additive manufacturing feature of printed electronics allows the design of highly-bespoke designs. In the case of printed neuromorphic circuits, the circuit is optimized to a particular dataset. Moreover, we explore an approach to learn not only the values of the crossbar resistances, but also the parameterization of the nonlinear components for a bespoke implementation. ... mehr

Preprint §
DOI: 10.5445/IR/1000156490
Veröffentlicht am 06.03.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Technische Informatik (ITEC)
Institut für Telematik (TM)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 19.04.2023
Sprache Englisch
Identifikator KITopen-ID: 1000156490
Erschienen in 2023 Design, Automation and Test in Europe Conference & Exhibition (DATE)
Veranstaltung Design, Automation & Test in Europe Conference & Exhibition (DATE 2023), Antwerpen, Belgien, 17.04.2023 – 19.04.2023
Verlag Institute of Electrical and Electronics Engineers (IEEE)
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page