2022 roadmap on neuromorphic computing and engineering. Issue 2 (1st June 2022)
- Record Type:
- Journal Article
- Title:
- 2022 roadmap on neuromorphic computing and engineering. Issue 2 (1st June 2022)
- Main Title:
- 2022 roadmap on neuromorphic computing and engineering
- Authors:
- Christensen, Dennis V
Dittmann, Regina
Linares-Barranco, Bernabe
Sebastian, Abu
Le Gallo, Manuel
Redaelli, Andrea
Slesazeck, Stefan
Mikolajick, Thomas
Spiga, Sabina
Menzel, Stephan
Valov, Ilia
Milano, Gianluca
Ricciardi, Carlo
Liang, Shi-Jun
Miao, Feng
Lanza, Mario
Quill, Tyler J
Keene, Scott T
Salleo, Alberto
Grollier, Julie
Marković, Danijela
Mizrahi, Alice
Yao, Peng
Yang, J Joshua
Indiveri, Giacomo
Strachan, John Paul
Datta, Suman
Vianello, Elisa
Valentian, Alexandre
Feldmann, Johannes
Li, Xuan
Pernice, Wolfram H P
Bhaskaran, Harish
Furber, Steve
Neftci, Emre
Scherr, Franz
Maass, Wolfgang
Ramaswamy, Srikanth
Tapson, Jonathan
Panda, Priyadarshini
Kim, Youngeun
Tanaka, Gouhei
Thorpe, Simon
Bartolozzi, Chiara
Cleland, Thomas A
Posch, Christoph
Liu, ShihChii
Panuccio, Gabriella
Mahmud, Mufti
Mazumder, Arnab Neelim
Hosseini, Morteza
Mohsenin, Tinoosh
Donati, Elisa
Tolu, Silvia
Galeazzi, Roberto
Christensen, Martin Ejsing
Holm, Sune
Ielmini, Daniele
Pryds, N
… (more) - Abstract:
- 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 18 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, andAbstract: 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 18 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. … (more)
- Is Part Of:
- Neuromorphic computing and engineering. Volume 2:Issue 2(2022)
- Journal:
- Neuromorphic computing and engineering
- Issue:
- Volume 2:Issue 2(2022)
- Issue Display:
- Volume 2, Issue 2 (2022)
- Year:
- 2022
- Volume:
- 2
- Issue:
- 2
- Issue Sort Value:
- 2022-0002-0002-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-06-01
- Subjects:
- neuromorphic computation -- spiking neural networks -- robotics -- memristor -- convolutional neural networks -- self-driving cars -- deep learning
Neural networks (Computer science) -- Periodicals
Neural computers -- Periodicals
Neuromorphics -- Periodicals
006.3 - Journal URLs:
- http://www.iop.org/ ↗
https://iopscience.iop.org/journal/2634-4386 ↗ - DOI:
- 10.1088/2634-4386/ac4a83 ↗
- Languages:
- English
- ISSNs:
- 2634-4386
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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- 21929.xml