Welbourne, A., Levy, A.L.R., Ellis, M.O.A. orcid.org/0000-0003-0338-8920 et al. (5 more authors) (2021) Voltage-controlled superparamagnetic ensembles for low-power reservoir computing. Applied Physics Letters, 118 (20). 202402. ISSN 0003-6951
Abstract
We propose thermally driven, voltage-controlled superparamagnetic ensembles as low-energy platforms for hardware-based reservoir computing. In the proposed devices, thermal noise is used to drive the ensembles' magnetization dynamics, while control of their net magnetization states is provided by strain-mediated voltage inputs. Using an ensemble of CoFeB nanodots as an example, we use analytical models and micromagnetic simulations to demonstrate how such a device can function as a reservoir and perform two benchmark machine learning tasks (spoken digit recognition and chaotic time series prediction) with competitive performance. Our results indicate robust performance on timescales from microseconds to milliseconds, potentially allowing such a reservoir to be tuned to perform a wide range of real-time tasks, from decision making in driverless cars (fast) to speech recognition (slow). The low energy consumption expected for such a device makes it an ideal candidate for use in edge computing applications that require low latency and power.
The authors thank the Engineering and Physical Sciences Research Council (Grant No.: EP/S009647/1 and EP/V006339/1) for financial support. The project leading to this application has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 861618 (SpinENGINE).
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2021 Author(s). This is an author-produced version of a paper subsequently published in Applied Physics Letters. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Materials Science and Engineering (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/S009647/1 ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/V006339/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 21 Jun 2021 13:44 |
Last Modified: | 22 Jun 2021 17:55 |
Status: | Published |
Publisher: | AIP Publishing |
Refereed: | Yes |
Identification Number: | 10.1063/5.0048911 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:175436 |