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Journal article · Preprint article

2022 Roadmap on Neuromorphic Computing and Engineering

From

Department of Energy Conversion and Storage, Technical University of Denmark1

Polytechnic University of Turin2

Nanjing University3

King Abdullah University of Science and Technology4

Stanford University5

University of Cambridge6

Université Paris-Saclay7

University of Southern California8

University of Zurich9

Hewlett Packard Enterprise10

University of Notre Dame11

Functional Oxides, Department of Energy Conversion and Storage, Technical University of Denmark12

Université Grenoble Alpes13

University of Oxford14

University of Münster15

University of Manchester16

University of California at Irvine17

Graz University of Technology18

Swiss Federal Institute of Technology Lausanne19

University of Technology Sydney20

Yale University21

The University of Tokyo22

Forschungszentrum Jülich GmbH23

Université Toulouse Jean Jaurès24

Italian Institute of Technology25

Cornell University26

Prophesee27

Istituto Italiano di Tecnologia28

Nottingham Trent University29

University of Maryland, Baltimore30

Department of Electrical Engineering, Technical University of Denmark31

Automation and Control, Department of Electrical Engineering, Technical University of Denmark32

Danish Council on Ethics33

University of Seville34

University of Copenhagen35

Politecnico di Milano36

IBM Zurich Research Laboratory37

STMicroelectronics38

NaMLab gGmbH39

Istituto per la Microelettronica e i Microsistemi40

Istituto Nazionale di Ricerca Metrologica41

...and 31 more

Modern computation based on the von Neumann architecture is today 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 1018 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. We hope that this Roadmap will be a useful resource 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.

Language: English
Year: 2022
Pages: 022501
ISSN: 26344386
Types: Journal article and Preprint article
DOI: 10.1088/2634-4386/ac4a83
ORCIDs: Christensen, Dennis V. , 0000-0001-5603-5243 , 0000-0003-1600-6151 , 0000-0002-0414-0321 , 0000-0003-3814-0378 , 0000-0001-7293-7503 , 0000-0002-0728-7214 , 0000-0002-1983-6516 , 0000-0002-4703-7949 , 0000-0002-3466-8063 , 0000-0002-0962-5424 , 0000-0003-4756-8632 , 0000-0002-6635-670X , 0000-0003-2043-049X , 0000-0001-8242-7531 , 0000-0002-7109-1689 , Pryds, N. , 0000-0002-8868-9951 , 0000-0001-6642-7136 , 0000-0002-4059-7193 , 0000-0002-2037-8348 , 0000-0002-8091-1298 , Tolu, Silvia , 0000-0002-1853-1614 , 0000-0002-3812-7942 and Galeazzi, Roberto

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