Roadmap for unconventional computing with nanotechnology Article Swipe
Giovanni Finocchio
,
Jean Anne C. Incorvia
,
Joseph S. Friedman
,
Yang Qu
,
Anna Giordano
,
Julie Grollier
,
Hyunsoo Yang
,
Florin Ciubotaru
,
Andrii V. Chumak
,
Azad Naeemi
,
Sorin Cotöfană
,
Riccardo Tomasello
,
C. Panagopoulos
,
Mario Carpentieri
,
Peng Lin
,
Gang Pan
,
J. Joshua Yang
,
Aida Todri‐Sanial
,
Gabriele Boschetto
,
Kremena Makasheva
,
Vinod K. Sangwan
,
Amit Ranjan Trivedi
,
Mark C. Hersam
,
Kerem Y. Çamsarı
,
Peter L. McMahon
,
Supriyo Datta
,
Belita Koiller
,
G. H. Aguilar
,
Guilherme P. Temporão
,
Davi R. Rodrigues
,
Satoshi Sunada
,
Karin Everschor‐Sitte
,
Kosuke Tatsumura
,
Hayato Goto
,
Vito Puliafito
,
Johan Åkerman
,
Hiroki Takesue
,
Massimiliano Di Ventra
,
Yuriy V. Pershin
,
Saibal Mukhopadhyay
,
Kaushik Roy
,
I‐Ting Wang
,
Wang Kang
,
Zhu Yao
,
Brajesh Kumar Kaushik
,
Jennifer Hasler
,
Samiran Ganguly
,
Avik W. Ghosh
,
William B. Levy
,
Vwani Roychowdhury
,
Supriyo Bandyopadhyay
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1088/2399-1984/ad299a
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1088/2399-1984/ad299a
In the ‘Beyond Moore’s Law’ era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same time, adopting a variety of nanotechnologies will offer benefits in energy cost, computational speed, reduced footprint, cyber resilience, and processing power. The time is ripe for a roadmap for unconventional computing with nanotechnologies to guide future research, and this collection aims to fill that need. The authors provide a comprehensive roadmap for neuromorphic computing using electron spins, memristive devices, two-dimensional nanomaterials, nanomagnets, and various dynamical systems. They also address other paradigms such as Ising machines, Bayesian inference engines, probabilistic computing with p-bits, processing in memory, quantum memories and algorithms, computing with skyrmions and spin waves, and brain-inspired computing for incremental learning and problem-solving in severely resource-constrained environments. These approaches have advantages over traditional Boolean computing based on von Neumann architecture. As the computational requirements for artificial intelligence grow 50 times faster than Moore’s Law for electronics, more unconventional approaches to computing and signal processing will appear on the horizon, and this roadmap will help identify future needs and challenges. In a very fertile field, experts in the field aim to present some of the dominant and most promising technologies for unconventional computing that will be around for some time to come. Within a holistic approach, the goal is to provide pathways for solidifying the field and guiding future impactful discoveries.
Related Topics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/2399-1984/ad299a
- https://iopscience.iop.org/article/10.1088/2399-1984/ad299a/pdf
- OA Status
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- Cited By
- 52
- References
- 203
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4391836388Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/2399-1984/ad299aDigital Object Identifier
- Title
-
Roadmap for unconventional computing with nanotechnologyWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-15Full publication date if available
- Authors
-
Giovanni Finocchio, Jean Anne C. Incorvia, Joseph S. Friedman, Yang Qu, Anna Giordano, Julie Grollier, Hyunsoo Yang, Florin Ciubotaru, Andrii V. Chumak, Azad Naeemi, Sorin Cotöfană, Riccardo Tomasello, C. Panagopoulos, Mario Carpentieri, Peng Lin, Gang Pan, J. Joshua Yang, Aida Todri‐Sanial, Gabriele Boschetto, Kremena Makasheva, Vinod K. Sangwan, Amit Ranjan Trivedi, Mark C. Hersam, Kerem Y. Çamsarı, Peter L. McMahon, Supriyo Datta, Belita Koiller, G. H. Aguilar, Guilherme P. Temporão, Davi R. Rodrigues, Satoshi Sunada, Karin Everschor‐Sitte, Kosuke Tatsumura, Hayato Goto, Vito Puliafito, Johan Åkerman, Hiroki Takesue, Massimiliano Di Ventra, Yuriy V. Pershin, Saibal Mukhopadhyay, Kaushik Roy, I‐Ting Wang, Wang Kang, Zhu Yao, Brajesh Kumar Kaushik, Jennifer Hasler, Samiran Ganguly, Avik W. Ghosh, William B. Levy, Vwani Roychowdhury, Supriyo BandyopadhyayList of authors in order
- Landing page
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https://doi.org/10.1088/2399-1984/ad299aPublisher landing page
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https://iopscience.iop.org/article/10.1088/2399-1984/ad299a/pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://iopscience.iop.org/article/10.1088/2399-1984/ad299a/pdfDirect OA link when available
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Nanotechnology, Data science, Computer science, Materials scienceTop concepts (fields/topics) attached by OpenAlex
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52Total citation count in OpenAlex
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2025: 37, 2024: 13, 2023: 2Per-year citation counts (last 5 years)
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203Number of works referenced by this work
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-
10Other works algorithmically related by OpenAlex
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