Memristive, Spintronic, and 2D-Materials-Based Devices to Improve and Complement Computing Hardware
Authors
Joksas, Dovydas
AlMutairi, AbdulAziz
Lee, Oscar
Cubukcu, Murat
Kurebayashi, Hidekazu
Kenyon, Anthony J
Mehonic, Adnan
Publication Date
2022Journal Title
ADVANCED INTELLIGENT SYSTEMS
ISSN
2640-4567
Publisher
Wiley
Language
en
Type
Article
This Version
AO
VoR
Metadata
Show full item recordCitation
Joksas, D., AlMutairi, A., Lee, O., Cubukcu, M., Lombardo, A., Kurebayashi, H., Kenyon, A. J., & et al. (2022). Memristive, Spintronic, and 2D-Materials-Based Devices to Improve and Complement Computing Hardware. ADVANCED INTELLIGENT SYSTEMS https://doi.org/10.1002/aisy.202200068
Description
Funder: Royal Academy of Engineering; Id: http://dx.doi.org/10.13039/501100000287
Funder: Ministry of Education—Kingdom of Saudi Arabia
Abstract
In a data-driven economy, virtually all industries benefit from advances in
information technology -- powerful computing systems are critically important
for rapid technological progress. However, this progress might be at risk of
slowing down if we do not address the discrepancy between our current computing
power demands and what the existing technologies can offer. Key limitations to
improving energy efficiency are the excessive growth of data transfer costs
associated with the von Neumann architecture and the fundamental limits of
complementary metal-oxide-semiconductor (CMOS) technologies, such as
transistors. In this perspective article, we discuss three technologies that
will likely play an essential role in future computing systems: memristive
electronics, spintronics, and electronics based on 2D materials. We present how
these may transform conventional digital computers and contribute to the
adoption of new paradigms, like neuromorphic computing.
Keywords
machine learning, memristors, spintronics, neuromorphic computing, 2D materials
Sponsorship
Engineering and Physical Sciences Research Council (2094654, EP/P013503/1)
Leverhulme Trust ((RPG-2016-135)
Identifiers
aisy202200068
External DOI: https://doi.org/10.1002/aisy.202200068
This record's URL: https://www.repository.cam.ac.uk/handle/1810/338655
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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