Roadmap to neuromorphic computing with emerging technologies.

Autor:	Mehonic, Adnan, Ielmini, Daniele, Roy, Kaushik, Mutlu, Onur, Kvatinsky, Shahar, Serrano-Gotarredona, Teresa, Linares-Barranco, Bernabe, Spiga, Sabina, Savel'ev, Sergey, Balanov, Alexander G., Chawla, Nitin, Desoli, Giuseppe, Malavena, Gerardo, Monzio Compagnoni, Christian, Wang, Zhongrui, Yang, J. Joshua, Sarwat, Syed Ghazi, Sebastian, Abu, Mikolajick, Thomas, Slesazeck, Stefan
Předmět:	SURFACE emitting lasers ARTIFICIAL neural networks GRAPH neural networks STATIC random access memory CONVOLUTIONAL neural networks DEEP learning FLASH memory FLIP chip technology PHASE change materials
Zdroj:	APL Materials; Oct2024, Vol. 12 Issue 10, p1-59, 59p
Abstrakt:	The article explores the roadmap to neuromorphic computing with a focus on emerging technologies, challenges, and potential solutions in the field. It discusses the significance of materials engineering, various approaches to neuromorphic research, and the importance of balancing performance with sustainability. The text also delves into the potential of 2D-LMs in mimicking synapses and neurons in artificial neural networks, highlighting the stable resistive switching observed in certain materials. Efforts are ongoing to address challenges and further advance the use of 2D-LMs in neuromorphic computing, offering promising solutions to computational challenges faced by traditional digital computers. [Extracted from the article]
Databáze:	Complementary Index
Externí odkaz:	Zobrazit plný text záznamu