2022 roadmap on neuromorphic computing and engineering
Creators: name: Christensen, Dennis V
name: Dittmann, Regina
name: Linares-Barranco, Bernabe
name: Sebastian, Abu
name: Le Gallo, Manuel
name: Redaelli, Andrea
name: Slesazeck, Stefan
name: Mikolajick, Thomas
name: Spiga, Sabina
name: Menzel, Stephan
name: Valov, Ilia
name: Milano, Gianluca
name: Ricciardi, Carlo
name: Liang, Shi-Jun
name: Miao, Feng
name: Lanza, Mario
name: Quill, Tyler J
name: Keene, Scott
name: Salleo, Alberto
name: Grollier, Julie
name: Marković, Danijela
name: Mizrahi, Alice
name: Yao, Peng
name: Yang, J Joshua
name: Indiveri, Giacomo
name: Strachan, John Paul
name: Datta, Suman
name: Vianello, Elisa
name: Valentian, Alexandre
name: Feldmann, Johannes
name: Li, Xuan
name: Pernice, Wolfram HP
name: Bhaskaran, Harish
name: Furber, Steve
name: Neftci, Emre
name: Scherr, Franz
name: Maass, Wolfgang
name: Ramaswamy, Srikanth
name: Tapson, Jonathan
name: Panda, Priyadarshini
name: Kim, Youngeun
name: Tanaka, Gouhei
name: Thorpe, Simon
name: Bartolozzi, Chiara
name: Cleland, Thomas A
name: Posch, Christoph
name: Liu, ShihChii
name: Panuccio, Gabriella
name: Mahmud, Mufti
name: Mazumder, Arnab Neelim
name: Hosseini, Morteza
name: Mohsenin, Tinoosh
name: Donati, Elisa
name: Tolu, Silvia
name: Galeazzi, Roberto
name: Christensen, Martin Ejsing
name: Holm, Sune
name: Ielmini, Daniele
name: Pryds, N
Publisher: name: Apollo - University of Cambridge Repository
Year: 2022
Subjects: Roadmap
neuromorphic computation
spiking neural networks
robotics
memristor
convolutional neural networks
self-driving cars
deep learning

description: Funder: ETH Zürich Foundation; doi: https://doi.org/10.13039/501100012652
description: Funder: Defense Advanced Research Projects Agency; doi: https://doi.org/10.13039/100000185
description: Funder: Collaborative Innovation Center of Advanced Microstructures; doi: https://doi.org/10.13039/501100016018
description: Funder: Bundesministerium für Bildung und Forschung; doi: https://doi.org/10.13039/501100002347
description: Funder: Centre National de la Recherche Scientifique; doi: https://doi.org/10.13039/501100004794
description: Funder: Freistaat Sachsen; doi: https://doi.org/10.13039/501100014913
description: Funder: Deutsche Forschungsgemeinschaft; doi: https://doi.org/10.13039/501100001659
description: Funder: National Institute on Deafness and Other Communication Disorders; doi: https://doi.org/10.13039/100000055
description: Abstract Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 10<sup>18</sup> calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community.