The promise of spintronics for unconventional computing
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A possible reason for less study of CMOS analog/mixed-signal circuits for neuromorphic computing is that developing a hardware platform with a standard electronic circuit for temporal time-encoded spikes processing is not considered an efficient approach.
“A possible reason could be that developing a hardware platform with a standard electronic circuit for temporal time-encoded spikes processing is not considered an efficient approach [151], which motivates neuromorphic and materials scientists to explore novel approaches and materials to mimic brain functionality in hardware.”
From Brain-inspired computing systems: a systematic literature review (2024) · cites this paper as [151]
Cites
Optimization and applications of echo state networks with leaky- integrator neurons
Jaeger, H., Lukoševičius, M., Popovici, D., & Siewert, U. (2007) · Neural Networks · doi:10.1016/j.neunet.2007.04.016 · Cited by 948 · see citing works
Neuromorphic computing with multi-memristive synapses
Boybat, I., Le Gallo, M., Nandakumar, S. R., Moraitis, T., Parnell, T., Tuma, T., Rajendran, B., Leblebici, Y., Sebastian, A., & Eleftheriou, E. (2018) · Nature Communications · doi:10.1038/s41467-018-04933-y · Cited by 903 · see citing works
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Brain-inspired computing systems: a systematic literature review
Zolfagharinejad, M., Alegre-Ibarra, U., Chen, T., Kinge, S., & van der Wiel, W. G. (2024) · The European Physical Journal B · doi:10.1140/epjb/s10051-024-00703-6 · Cited by 39 · see citing works
- Authors
- Finocchio, G., Di Ventra, M., Camsari, K. Y., Everschor-Sitte, K., Khalili Amiri, P., & Zeng, Z.
- Affiliations
- University of Messina (IT)
- Purdue University West Lafayette (US)
- Chinese Academy of Sciences (CN)
- Corresponding author
- Finocchio, Giovanni
- Venue
- Journal of Magnetism and Magnetic Materials
- Publisher
- Elsevier BV
- Published
- 2021-03
- Volume
- 521
- Pages
- 167506
- ISSN
- 0304-8853 (ISSN-L)
- OpenAlex
- W2980444885
- Cited by
- 173
- References
- 2
- Citations by year
- 2026: 19 · 2025: 22 · 2024: 39 · 2023: 34 · 2022: 37 · 2021: 16 · 2020: 6
- FWCI
- 9.46
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Magnetism and Magnetic Materials (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Defense Sciences Office, DARPA
- Ministero degli Affari Esteri e della Cooperazione Internazionale
- Topics
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Magnetic properties of thin films
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Reservoir Computing
- Keywords
- spintronics, unconventional computing, magnetic tunnel junctions, reservoir computing, probabilistic computing, memcomputing, low-power devices, hybrid computing systems, energy dissipation
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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