Embedded Devices for Neuromorphic Time-Series Assessment Article Swipe
Dennis Valbjørn Christensen
,
Regina Dittmann
,
B. Linares-Barranco
,
Abu Sebastian
,
Manuel Le Gallo
,
Andrea Redaelli
,
Stefan Slesazeck
,
Thomas Mikolajick
,
Sabina Spiga
,
Stephan Menzel
,
Ilia Valov
,
Gianluca Milano
,
Carlo Ricciardi
,
Shi‐Jun Liang
,
Feng Miao
,
Mario Lanza
,
Tyler J. Quill
,
Scott T. Keene
,
Alberto Salleo
,
Julie Grollier
,
Danijela Marković
,
Alice Mizrahi
,
Peng Yao
,
J. Joshua Yang
,
Giacomo Indiveri
,
John Paul Strachan
,
Suman Datta
,
Elisa Vianello
,
Alexandre Valentian
,
Johannes Feldmann
,
Xuan Li
,
Wolfram H. P. Pernice
,
Harish Bhaskaran
,
Steve Furber
,
Emre Neftci
,
Franz Scherr
,
Wolfgang Maass
,
Srikanth Ramaswamy
,
Jonathan Tapson
,
Priyadarshini Panda
,
Youngeun Kim
,
Gouhei Tanaka
,
Simon J. Thorpe
,
Chiara Bartolozzi
,
Thomas A. Cleland
,
C. Posch
,
Shih‐Chii Liu
,
Gabriella Panuccio
,
Mufti Mahmud
,
Arnab Neelim Mazumder
,
Morteza Hosseini
,
Tinoosh Mohsenin
,
Elisa Donati
,
Silvia Tolu
,
Roberto Galeazzi
,
Martin Ejsing Christensen
,
Sune Holm
,
Daniele Ielmini
,
Nini Pryds
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.13016/m2ksy0-wxr3
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.13016/m2ksy0-wxr3
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 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.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- http://hdl.handle.net/11603/24113
- OA Status
- green
- Cited By
- 569
- References
- 524
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4206609022
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4206609022Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.13016/m2ksy0-wxr3Digital Object Identifier
- Title
-
Embedded Devices for Neuromorphic Time-Series AssessmentWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-01-12Full publication date if available
- Authors
-
Dennis Valbjørn Christensen, Regina Dittmann, B. Linares-Barranco, Abu Sebastian, Manuel Le Gallo, Andrea Redaelli, Stefan Slesazeck, Thomas Mikolajick, Sabina Spiga, Stephan Menzel, Ilia Valov, Gianluca Milano, Carlo Ricciardi, Shi‐Jun Liang, Feng Miao, Mario Lanza, Tyler J. Quill, Scott T. Keene, Alberto Salleo, Julie Grollier, Danijela Marković, Alice Mizrahi, Peng Yao, J. Joshua Yang, Giacomo Indiveri, John Paul Strachan, Suman Datta, Elisa Vianello, Alexandre Valentian, Johannes Feldmann, Xuan Li, Wolfram H. P. Pernice, Harish Bhaskaran, Steve Furber, Emre Neftci, Franz Scherr, Wolfgang Maass, Srikanth Ramaswamy, Jonathan Tapson, Priyadarshini Panda, Youngeun Kim, Gouhei Tanaka, Simon J. Thorpe, Chiara Bartolozzi, Thomas A. Cleland, C. Posch, Shih‐Chii Liu, Gabriella Panuccio, Mufti Mahmud, Arnab Neelim Mazumder, Morteza Hosseini, Tinoosh Mohsenin, Elisa Donati, Silvia Tolu, Roberto Galeazzi, Martin Ejsing Christensen, Sune Holm, Daniele Ielmini, Nini PrydsList of authors in order
- Landing page
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https://hdl.handle.net/11603/24113Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://hdl.handle.net/11603/24113Direct OA link when available
- Concepts
-
Neuromorphic engineering, Computer science, Computer architecture, Artificial intelligence, Artificial neural networkTop concepts (fields/topics) attached by OpenAlex
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569Total citation count in OpenAlex
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2025: 132, 2024: 194, 2023: 167, 2022: 69, 2021: 7Per-year citation counts (last 5 years)
- References (count)
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524Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.We | 256 |
| abstract_inverted_index.an | 166, 198 |
| abstract_inverted_index.as | 25, 107, 286, 288 |
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| abstract_inverted_index.be | 70, 114, 140, 262 |
| abstract_inverted_index.by | 116, 123, 266 |
| abstract_inverted_index.if | 73 |
| abstract_inverted_index.in | 209, 236, 298 |
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| abstract_inverted_index.of | 42, 90, 127, 134, 147, 150, 181, 189, 193, 213, 231 |
| abstract_inverted_index.on | 3, 77, 200 |
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| abstract_inverted_index.to | 53, 100, 139, 176, 185, 273 |
| abstract_inverted_index.The | 46, 179, 226 |
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| abstract_inverted_index.aim | 180 |
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| abstract_inverted_index.the | 4, 15, 43, 57, 124, 128, 137, 143, 171, 190, 201, 206, 210, 237, 245, 249, 284, 299 |
| abstract_inverted_index.von | 5, 78 |
| abstract_inverted_index.who | 280, 294 |
| abstract_inverted_index.yet | 270 |
| abstract_inverted_index.1018 | 60 |
| abstract_inverted_index.Even | 64 |
| abstract_inverted_index.This | 33, 131 |
| abstract_inverted_index.data | 29, 34, 106, 174 |
| abstract_inverted_index.deal | 103 |
| abstract_inverted_index.each | 62, 253 |
| abstract_inverted_index.edge | 177 |
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| abstract_inverted_index.hope | 257 |
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| abstract_inverted_index.part | 41 |
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| abstract_inverted_index.they | 74, 82 |
| abstract_inverted_index.this | 182, 259, 276 |
| abstract_inverted_index.type | 80 |
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| abstract_inverted_index.view | 243 |
| abstract_inverted_index.well | 287, 296 |
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| abstract_inverted_index.large | 40, 148 |
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| abstract_inverted_index.those | 279, 293 |
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| abstract_inverted_index.Modern | 0 |
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| abstract_inverted_index.brain. | 130 |
| abstract_inverted_index.field, | 277, 285 |
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| abstract_inverted_index.Roadmap | 183, 227, 260 |
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| abstract_inverted_index.centers | 175 |
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| abstract_inverted_index.consume | 84 |
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| abstract_inverted_index.digital | 151 |
| abstract_inverted_index.ethics. | 225 |
| abstract_inverted_index.leading | 234 |
| abstract_inverted_index.opinion | 199 |
| abstract_inverted_index.outside | 275 |
| abstract_inverted_index.present | 186, 191 |
| abstract_inverted_index.provide | 197, 240 |
| abstract_inverted_index.readers | 274 |
| abstract_inverted_index.second. | 63 |
| abstract_inverted_index.storage | 144 |
| abstract_inverted_index.systems | 119 |
| abstract_inverted_index.built-in | 98 |
| abstract_inverted_index.computer | 49 |
| abstract_inverted_index.concepts | 126 |
| abstract_inverted_index.devices, | 218 |
| abstract_inverted_index.devices. | 178 |
| abstract_inverted_index.entering | 283 |
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| abstract_inverted_index.snapshot | 188 |
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| abstract_inverted_index.addressed | 115 |
| abstract_inverted_index.circuits, | 220 |
| abstract_inverted_index.community | 239 |
| abstract_inverted_index.computers | 68, 135 |
| abstract_inverted_index.computing | 118, 301 |
| abstract_inverted_index.important | 167 |
| abstract_inverted_index.intrinsic | 96 |
| abstract_inverted_index.megawatts | 89 |
| abstract_inverted_index.potential | 138, 163 |
| abstract_inverted_index.powerful, | 72 |
| abstract_inverted_index.providing | 267, 289 |
| abstract_inverted_index.biological | 125 |
| abstract_inverted_index.challenges | 202, 251 |
| abstract_inverted_index.collection | 230 |
| abstract_inverted_index.community. | 302 |
| abstract_inverted_index.generation | 48, 133 |
| abstract_inverted_index.incredibly | 71 |
| abstract_inverted_index.materials, | 217 |
| abstract_inverted_index.physically | 97 |
| abstract_inverted_index.processing | 19, 146 |
| abstract_inverted_index.technology | 50, 195 |
| abstract_inverted_index.algorithms, | 222 |
| abstract_inverted_index.computation | 1 |
| abstract_inverted_index.consumption | 157 |
| abstract_inverted_index.established | 297 |
| abstract_inverted_index.implemented | 24 |
| abstract_inverted_index.information | 152 |
| abstract_inverted_index.intensively | 30 |
| abstract_inverted_index.processors. | 160 |
| abstract_inverted_index.researchers | 235 |
| abstract_inverted_index.responsible | 37 |
| abstract_inverted_index.technology, | 215 |
| abstract_inverted_index.architecture | 7 |
| abstract_inverted_index.calculations | 61 |
| abstract_inverted_index.capabilities | 99 |
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| abstract_inverted_index.conventional | 159 |
| abstract_inverted_index.cutting-edge | 12 |
| abstract_inverted_index.introduction | 272 |
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| abstract_inverted_index.perspectives | 232, 291 |
| abstract_inverted_index.applications, | 165, 223 |
| abstract_inverted_index.architecture, | 18 |
| abstract_inverted_index.comprehensive | 271 |
| abstract_inverted_index.continuously. | 32 |
| abstract_inverted_index.interchanging | 28 |
| abstract_inverted_index.opportunities | 204 |
| abstract_inverted_index.architectures, | 81 |
| cited_by_percentile_year | |
| countries_distinct_count | 13 |
| institutions_distinct_count | 59 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.7799999713897705 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile |