Shape‐Dependent Multi‐Weight Magnetic Artificial Synapses for Neuromorphic Computing

Leonard, Thomas; Liu, Samuel; Alamdar, Mahshid; Jin, Harrison; Cui, Can; Akinola, Otitoaleke G.; Xue, Lin; Xiao, T. Patrick; Friedman, Joseph S.; Marinella, Matthew J.; Bennett, Christopher H.; Incorvia, Jean Anne C.

doi:10.1002/aelm.202200563

Title: Shape‐Dependent Multi‐Weight Magnetic Artificial Synapses for Neuromorphic Computing

Abstract

Abstract In neuromorphic computing, artificial synapses provide a multi‐weight (MW) conductance state that is set based on inputs from neurons, analogous to the brain. Herein, artificial synapses based on magnetic materials that use a magnetic tunnel junction (MTJ) and a magnetic domain wall (DW) are explored. By fabricating lithographic notches in a DW track underneath a single MTJ, 3–5 stable resistance states that can be repeatably controlled electrically using spin‐orbit torque are achieved. The effect of geometry on the synapse behavior is explored, showing that a trapezoidal device has asymmetric weight updates with high controllability, while a rectangular device has higher stochasticity, but with stable resistance levels. The device data is input into neuromorphic computing simulators to show the usefulness of application‐specific synaptic functions. Implementing an artificial neural network (NN) applied to streamed Fashion‐MNIST data, the trapezoidal magnetic synapse can be used as a metaplastic function for efficient online learning. Implementing a convolutional NN for CIFAR‐100 image recognition, the rectangular magnetic synapse achieves near‐ideal inference accuracy, due to the stability of its resistance levels. This work shows MW magnetic synapses are a feasible technology for neuromorphic computing and provides design guidelines for emerging artificial synapse technologies.

Authors:

Leonard, Thomas ^[1]; Liu, Samuel ^[1]; Alamdar, Mahshid ^[1];

^[1]; Cui, Can ^[1]; Akinola, Otitoaleke G. ^[1]; Xue, Lin ^[2]; Xiao, T. Patrick ^[3]; Friedman, Joseph S. ^[4]; Marinella, Matthew J. ^[3]; Bennett, Christopher H. ^[3];

^[1]

Electrical and Computer Engineering Department University of Texas at Austin Austin TX 78712 USA
Applied Materials Santa Clara CA 95054 USA
Sandia National Laboratories Albuquerque NM 87123 USA
Electrical and Computer Engineering Department University of Texas at Dallas Richardson TX 75080 USA

Publication Date:: Sun Sep 11 00:00:00 EDT 2022

Sponsoring Org.:: USDOE

OSTI Identifier:: 1995870

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: Advanced Electronic Materials

Additional Journal Information:: Journal Name: Advanced Electronic Materials Journal Volume: 8 Journal Issue: 12; Journal ID: ISSN 2199-160X

Publisher:: Wiley Blackwell (John Wiley & Sons)

Country of Publication:: United States

Language:: English

Citation Formats


                    Leonard, Thomas, Liu, Samuel, Alamdar, Mahshid, Jin, Harrison, Cui, Can, Akinola, Otitoaleke G., Xue, Lin, Xiao, T. Patrick, Friedman, Joseph S., Marinella, Matthew J., Bennett, Christopher H., and Incorvia, Jean Anne C. Shape‐Dependent Multi‐Weight Magnetic Artificial Synapses for Neuromorphic Computing.  United States: N. p., 2022. 
Web.  doi:10.1002/aelm.202200563.

Copy to clipboard


                    Leonard, Thomas, Liu, Samuel, Alamdar, Mahshid, Jin, Harrison, Cui, Can, Akinola, Otitoaleke G., Xue, Lin, Xiao, T. Patrick, Friedman, Joseph S., Marinella, Matthew J., Bennett, Christopher H., & Incorvia, Jean Anne C. Shape‐Dependent Multi‐Weight Magnetic Artificial Synapses for Neuromorphic Computing.  United States.  https://doi.org/10.1002/aelm.202200563

Copy to clipboard


                    Leonard, Thomas, Liu, Samuel, Alamdar, Mahshid, Jin, Harrison, Cui, Can, Akinola, Otitoaleke G., Xue, Lin, Xiao, T. Patrick, Friedman, Joseph S., Marinella, Matthew J., Bennett, Christopher H., and Incorvia, Jean Anne C. Sun .  
"Shape‐Dependent Multi‐Weight Magnetic Artificial Synapses for Neuromorphic Computing".  United States.  https://doi.org/10.1002/aelm.202200563.

Copy to clipboard


                    
@article{osti_1995870,

  title        = {Shape‐Dependent Multi‐Weight Magnetic Artificial Synapses for Neuromorphic Computing},

  author       = {Leonard, Thomas and Liu, Samuel and Alamdar, Mahshid and Jin, Harrison and Cui, Can and Akinola, Otitoaleke G. and Xue, Lin and Xiao, T. Patrick and Friedman, Joseph S. and Marinella, Matthew J. and Bennett, Christopher H. and Incorvia, Jean Anne C.},

  abstractNote = {Abstract In neuromorphic computing, artificial synapses provide a multi‐weight (MW) conductance state that is set based on inputs from neurons, analogous to the brain. Herein, artificial synapses based on magnetic materials that use a magnetic tunnel junction (MTJ) and a magnetic domain wall (DW) are explored. By fabricating lithographic notches in a DW track underneath a single MTJ, 3–5 stable resistance states that can be repeatably controlled electrically using spin‐orbit torque are achieved. The effect of geometry on the synapse behavior is explored, showing that a trapezoidal device has asymmetric weight updates with high controllability, while a rectangular device has higher stochasticity, but with stable resistance levels. The device data is input into neuromorphic computing simulators to show the usefulness of application‐specific synaptic functions. Implementing an artificial neural network (NN) applied to streamed Fashion‐MNIST data, the trapezoidal magnetic synapse can be used as a metaplastic function for efficient online learning. Implementing a convolutional NN for CIFAR‐100 image recognition, the rectangular magnetic synapse achieves near‐ideal inference accuracy, due to the stability of its resistance levels. This work shows MW magnetic synapses are a feasible technology for neuromorphic computing and provides design guidelines for emerging artificial synapse technologies.},

  doi          = {10.1002/aelm.202200563},

  journal      = {Advanced Electronic Materials},

  number       = 12,

  volume       = 8,

  place        = {United States},

  year         = {Sun Sep 11 00:00:00 EDT 2022},

  month        = {Sun Sep 11 00:00:00 EDT 2022}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (Publisher)

Publisher's Version of Record
https://doi.org/10.1002/aelm.202200563

Other availability

Search WorldCat to find libraries that may hold this journal

Save / Share:

Export Metadata

Save to My Library

Works referenced in this record:

Spin-dependent tunneling conductance of $Fe | MgO | Fe$ sandwiches
journal, January 2001

Butler, W. H.; Zhang, X. -G.; Schulthess, T. C.
Physical Review B, Vol. 63, Issue 5
DOI: 10.1103/PhysRevB.63.054416

The multifarious hippocampal mossy fiber pathway: a review
journal, June 2000

Henze, D. A.; Urban, N. N.; Barrionuevo, G.
Neuroscience, Vol. 98, Issue 3
DOI: 10.1016/S0306-4522(00)00146-9

Nanoscale domain wall devices with magnetic tunnel junction read and write
journal, June 2021

Raymenants, E.; Bultynck, O.; Wan, D.
Nature Electronics, Vol. 4, Issue 6
DOI: 10.1038/s41928-021-00593-x

Magnetic Domain Wall Based Synaptic and Activation Function Generator for Neuromorphic Accelerators
journal, December 2019

Siddiqui, Saima A.; Dutta, Sumit; Tang, Astera
Nano Letters, Vol. 20, Issue 2
DOI: 10.1021/acs.nanolett.9b04200

Domain wall-magnetic tunnel junction spin–orbit torque devices and circuits for in-memory computing
journal, March 2021

Alamdar, Mahshid; Leonard, Thomas; Cui, Can
Applied Physics Letters, Vol. 118, Issue 11
DOI: 10.1063/5.0038521

Spin-torque-driven MTJs with extended free layer for logic applications
journal, June 2018

Raymenants, Eline; Vaysset, Adrien; Wan, Danny
Journal of Physics D: Applied Physics, Vol. 51, Issue 27
DOI: 10.1088/1361-6463/aac609

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons
journal, December 2011

Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang
PLoS Computational Biology, Vol. 7, Issue 12
DOI: 10.1371/journal.pcbi.1002294

Area and Energy Efficient Joint 2T SOT-MRAM-Based on Diffusion Region Sharing With Adjacent Cells
journal, March 2022

Jang, Yunho; Park, Jongsun
IEEE Transactions on Circuits and Systems II: Express Briefs, Vol. 69, Issue 3
DOI: 10.1109/TCSII.2021.3126638

Magnetic Tunnel Junction Based Long-Term Short-Term Stochastic Synapse for a Spiking Neural Network with On-Chip STDP Learning
journal, July 2016

Srinivasan, Gopalakrishnan; Sengupta, Abhronil; Roy, Kaushik
Scientific Reports, Vol. 6, Issue 1
DOI: 10.1038/srep29545

Active particle feedback control with a single-shot detection convolutional neural network
journal, July 2020

Fränzl, Martin; Cichos, Frank
Scientific Reports, Vol. 10, Issue 1
DOI: 10.1038/s41598-020-69055-2

Impact of Non-Ideal Characteristics of Resistive Synaptic Devices on Implementing Convolutional Neural Networks
journal, September 2019

Sun, Xiaoyu; Yu, Shimeng
IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Vol. 9, Issue 3
DOI: 10.1109/JETCAS.2019.2933148

Hippocampal Reactivation of Random Trajectories Resembling Brownian Diffusion
journal, April 2019

Stella, Federico; Baracskay, Peter; O’Neill, Joseph
Neuron, Vol. 102, Issue 2
DOI: 10.1016/j.neuron.2019.01.052

Three-terminal magnetic tunnel junction synapse circuits showing spike-timing-dependent plasticity
journal, September 2019

Akinola, Otitoaleke; Hu, Xuan; Bennett, Christopher H.
Journal of Physics D: Applied Physics, Vol. 52, Issue 49
DOI: 10.1088/1361-6463/ab4157

Bioinspired Programming of Memory Devices for Implementing an Inference Engine
journal, August 2015

Querlioz, Damien; Bichler, Olivier; Vincent, Adrien Francis
Proceedings of the IEEE, Vol. 103, Issue 8
DOI: 10.1109/JPROC.2015.2437616

Synaptic metaplasticity in binarized neural networks
journal, May 2021

Laborieux, Axel; Ernoult, Maxence; Hirtzlin, Tifenn
Nature Communications, Vol. 12, Issue 1
DOI: 10.1038/s41467-021-22768-y

Neural algorithms and computing beyond Moore's law
journal, March 2019

Aimone, James B.
Communications of the ACM, Vol. 62, Issue 4
DOI: 10.1145/3231589

Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference
journal, October 2017

Shim, Yong; Chen, Shuhan; Sengupta, Abhronil
Scientific Reports, Vol. 7, Issue 1
DOI: 10.1038/s41598-017-14240-z

Elementary depinning processes of magnetic domain walls under fields and currents
journal, October 2014

Nguyen, V. D.; Torres, W. Savero; Laczkowski, P.
Scientific Reports, Vol. 4, Issue 1
DOI: 10.1038/srep06509

Magnetic domain wall neuron with lateral inhibition
journal, October 2018

Hassan, Naimul; Hu, Xuan; Jiang-Wei, Lucian
Journal of Applied Physics, Vol. 124, Issue 15
DOI: 10.1063/1.5042452

Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator
journal, March 2018

Marinella, Matthew J.; Agarwal, Sapan; Hsia, Alexander
IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Vol. 8, Issue 1
DOI: 10.1109/JETCAS.2018.2796379

Area-Efficient SOT-MRAM With a Schottky Diode
journal, August 2016

Seo, Yeongkyo; Kwon, Kon-Woo; Roy, Kaushik
IEEE Electron Device Letters, Vol. 37, Issue 8
DOI: 10.1109/LED.2016.2578959

Efficacy and Stability of Quantal GABA Release at a Hippocampal Interneuron–Principal Neuron Synapse
journal, August 2000

Kraushaar, Udo; Jonas, Peter
The Journal of Neuroscience, Vol. 20, Issue 15
DOI: 10.1523/JNEUROSCI.20-15-05594.2000

Maximized lateral inhibition in paired magnetic domain wall racetracks for neuromorphic computing
journal, May 2020

Cui, Can; Akinola, Otitoaleke G.; Hassan, Naimul
Nanotechnology, Vol. 31, Issue 29
DOI: 10.1088/1361-6528/ab86e8

Spin-Transfer Torque Magnetic Memory as a Stochastic Memristive Synapse for Neuromorphic Systems
journal, April 2015

Vincent, Adrien F.; Larroque, Jerome; Locatelli, Nicolas
IEEE Transactions on Biomedical Circuits and Systems, Vol. 9, Issue 2
DOI: 10.1109/TBCAS.2015.2414423

Proposal for an All-Spin Artificial Neural Network: Emulating Neural and Synaptic Functionalities Through Domain Wall Motion in Ferromagnets
journal, December 2016

Sengupta, Abhronil; Shim, Yong; Roy, Kaushik
IEEE Transactions on Biomedical Circuits and Systems, Vol. 10, Issue 6
DOI: 10.1109/TBCAS.2016.2525823

Graded-Anisotropy-Induced Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron
journal, June 2019

Brigner, Wesley H.; Hu, Xuan; Hassan, Naimul
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, Vol. 5, Issue 1
DOI: 10.1109/JXCDC.2019.2904191

Magnetic Tunnel Junction Mimics Stochastic Cortical Spiking Neurons
journal, July 2016

Sengupta, Abhronil; Panda, Priyadarshini; Wijesinghe, Parami
Scientific Reports, Vol. 6, Issue 1
DOI: 10.1038/srep30039

A domain wall-magnetic tunnel junction artificial synapse with notched geometry for accurate and efficient training of deep neural networks
journal, May 2021

Liu, Samuel; Xiao, T. Patrick; Cui, Can
Applied Physics Letters, Vol. 118, Issue 20
DOI: 10.1063/5.0046032

Intrinsic optimization using stochastic nanomagnets
journal, March 2017

Sutton, Brian; Camsari, Kerem Yunus; Behin-Aein, Behtash
Scientific Reports, Vol. 7, Issue 1
DOI: 10.1038/srep44370

Asymmetric ground state spin configuration of transverse domain wall on symmetrically notched ferromagnetic nanowires
journal, July 2010

Djuhana, Dede; Piao, Hong-Guang; Lee, Sang-Hyuk
Applied Physics Letters, Vol. 97, Issue 2
DOI: 10.1063/1.3459965

Research progress on solutions to the sneak path issue in memristor crossbar arrays
journal, January 2020

Shi, Lingyun; Zheng, Guohao; Tian, Bobo
Nanoscale Advances, Vol. 2, Issue 5
DOI: 10.1039/D0NA00100G

Similar Records in DOE PAGES and OSTI.GOV collections:

A domain wall-magnetic tunnel junction artificial synapse with notched geometry for accurate and efficient training of deep neural networks

Journal Article Liu, Samuel ; Xiao, T. Patrick ; Cui, Can ; ... - Applied Physics Letters

Inspired by the parallelism and efficiency of the brain, several candidates for artificial synapse devices have been developed for neuromorphic computing, yet a nonlinear and asymmetric synaptic response curve precludes their use for backpropagation, the foundation of modern supervised learning. Spintronic devices—which benefit from high endurance, low power consumption, low latency, and CMOS compatibility—are a promising technology for memory, and domain-wall magnetic tunnel junction (DW-MTJ) devices have been shown to implement synaptic functions such as long-term potentiation and spike-timing dependent plasticity. In this work, we propose a notched DW-MTJ synapse as a candidate for supervised learning. Using micromagnetic simulations atmore »« less
https://doi.org/10.1063/5.0046032

Full Text Available
An Interface–Type Memristive Device for Artificial Synapse and Neuromorphic Computing

Journal Article Kunwar, Sundar ; Jernigan, Zachary ; Hughes, Zach ; ... - Advanced Intelligent Systems

Interface-type (IT) metal/oxide Schottky memristive devices have attracted considerable attention over filament-type (FT) devices for neuromorphic computing because of their uniform, filament-free, and analog resistive switching (RS) characteristics. The most recent IT devices are based on oxygen ions and vacancies movement to alter interfacial Schottky barrier parameters and thereby control RS properties. However, the reliability and stability of these devices have been significantly affected by the undesired diffusion of ionic species. Herein, a reliable interface-dominated memristive device is demonstrated using a simple Au/Nb-doped SrTiO₃ (Nb:STO) Schottky structure. The Au/Nb:STO Schottky barrier modulation by charge trapping and detrapping is responsible formore »« less
https://doi.org/10.1002/aisy.202300035

Full Text Available
Three-terminal magnetic tunnel junction synapse circuits showing spike-timing-dependent plasticity

Journal Article Akinola, Otitoaleke ; Hu, Xuan ; Bennett, Christopher H. ; ... - Journal of Physics. D, Applied Physics

There have been recent efforts towards the development of biologically-inspired neuromorphic devices and architecture. In this work, we demonstrate a synapse circuit that is designed to perform spike-timing-dependent plasticity which works with the leaky, integrate, and fire neuron in a neuromorphic computing architecture. The circuit consists of a three-terminal magnetic tunnel junction with a mobile domain wall between two low-pass filters and has been modeled in SPICE. The findings show that the current flowing through the synapse is highly correlated to the timing delay between the pre-synaptic and post-synaptic neurons. Using micromagnetic simulations, we show that introducing notches along themore »« less
Cited by 21
https://doi.org/10.1088/1361-6463/ab4157

Full Text Available
Biomimetic, Soft-Material Synapse for Neuromorphic Computing: from Device to Network

Conference Sakib hasan, Md ; Schuman, Catherine ; Najem, Joseph S. ; ...

Neuromorphic computing refers to a variety of brain-inspired computers, devices, and models inspired by the interconnectivity, performance, and energy efficiency of the human brain. Unlike the ubiquitous von Neumann computer architectures with complex processor cores and sequential computation, biological neurons and synapses operate by storing and processing information simultaneously with the capacity of flexible adaptation resulting in massive computational capability with much less power consumption. The search for a synaptic material which can closely imitate bio-synapse has led to an alamethicin-doped, synthetic biomembrane which can emulate key synaptic functions due to generic memristive property enabling learning and computation. This two-terminal,more »« less
Full Text Available
Spin orbit torque based electronic neuron

Journal Article Sengupta, Abhronil ; Choday, Sri Harsha ; Kim, Yusung ; ... - Applied Physics Letters

A device based on current-induced spin-orbit torque (SOT) that functions as an electronic neuron is proposed in this work. The SOT device implements an artificial neuron's thresholding (transfer) function. In the first step of a two-step switching scheme, a charge current places the magnetization of a nano-magnet along the hard-axis, i.e., an unstable point for the magnet. In the second step, the SOT device (neuron) receives a current (from the synapses) which moves the magnetization from the unstable point to one of the two stable states. The polarity of the synaptic current encodes the excitatory and inhibitory nature of themore »« less
https://doi.org/10.1063/1.4917011

Similar Records

Title: Shape‐Dependent Multi‐Weight Magnetic Artificial Synapses for Neuromorphic Computing

Abstract

Citation Formats

Spin-dependent tunneling conductance of Fe | MgO | Fe sandwiches journal, January 2001

The multifarious hippocampal mossy fiber pathway: a review journal, June 2000

Nanoscale domain wall devices with magnetic tunnel junction read and write journal, June 2021

Magnetic Domain Wall Based Synaptic and Activation Function Generator for Neuromorphic Accelerators journal, December 2019

Domain wall-magnetic tunnel junction spin–orbit torque devices and circuits for in-memory computing journal, March 2021

Spin-torque-driven MTJs with extended free layer for logic applications journal, June 2018

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons journal, December 2011

Area and Energy Efficient Joint 2T SOT-MRAM-Based on Diffusion Region Sharing With Adjacent Cells journal, March 2022

Magnetic Tunnel Junction Based Long-Term Short-Term Stochastic Synapse for a Spiking Neural Network with On-Chip STDP Learning journal, July 2016

Active particle feedback control with a single-shot detection convolutional neural network journal, July 2020

Impact of Non-Ideal Characteristics of Resistive Synaptic Devices on Implementing Convolutional Neural Networks journal, September 2019

Hippocampal Reactivation of Random Trajectories Resembling Brownian Diffusion journal, April 2019

Three-terminal magnetic tunnel junction synapse circuits showing spike-timing-dependent plasticity journal, September 2019

Bioinspired Programming of Memory Devices for Implementing an Inference Engine journal, August 2015

Synaptic metaplasticity in binarized neural networks journal, May 2021

Neural algorithms and computing beyond Moore's law journal, March 2019

Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference journal, October 2017

Elementary depinning processes of magnetic domain walls under fields and currents journal, October 2014

Magnetic domain wall neuron with lateral inhibition journal, October 2018

Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator journal, March 2018

Area-Efficient SOT-MRAM With a Schottky Diode journal, August 2016

Efficacy and Stability of Quantal GABA Release at a Hippocampal Interneuron–Principal Neuron Synapse journal, August 2000

Maximized lateral inhibition in paired magnetic domain wall racetracks for neuromorphic computing journal, May 2020

Spin-Transfer Torque Magnetic Memory as a Stochastic Memristive Synapse for Neuromorphic Systems journal, April 2015

Proposal for an All-Spin Artificial Neural Network: Emulating Neural and Synaptic Functionalities Through Domain Wall Motion in Ferromagnets journal, December 2016

Graded-Anisotropy-Induced Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron journal, June 2019

Magnetic Tunnel Junction Mimics Stochastic Cortical Spiking Neurons journal, July 2016

A domain wall-magnetic tunnel junction artificial synapse with notched geometry for accurate and efficient training of deep neural networks journal, May 2021

Intrinsic optimization using stochastic nanomagnets journal, March 2017

Asymmetric ground state spin configuration of transverse domain wall on symmetrically notched ferromagnetic nanowires journal, July 2010

Research progress on solutions to the sneak path issue in memristor crossbar arrays journal, January 2020

Spin-dependent tunneling conductance of $Fe | MgO | Fe$ sandwiches
journal, January 2001

The multifarious hippocampal mossy fiber pathway: a review
journal, June 2000

Nanoscale domain wall devices with magnetic tunnel junction read and write
journal, June 2021

Magnetic Domain Wall Based Synaptic and Activation Function Generator for Neuromorphic Accelerators
journal, December 2019

Domain wall-magnetic tunnel junction spin–orbit torque devices and circuits for in-memory computing
journal, March 2021

Spin-torque-driven MTJs with extended free layer for logic applications
journal, June 2018

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons
journal, December 2011

Area and Energy Efficient Joint 2T SOT-MRAM-Based on Diffusion Region Sharing With Adjacent Cells
journal, March 2022

Magnetic Tunnel Junction Based Long-Term Short-Term Stochastic Synapse for a Spiking Neural Network with On-Chip STDP Learning
journal, July 2016

Active particle feedback control with a single-shot detection convolutional neural network
journal, July 2020

Impact of Non-Ideal Characteristics of Resistive Synaptic Devices on Implementing Convolutional Neural Networks
journal, September 2019

Hippocampal Reactivation of Random Trajectories Resembling Brownian Diffusion
journal, April 2019

Three-terminal magnetic tunnel junction synapse circuits showing spike-timing-dependent plasticity
journal, September 2019

Bioinspired Programming of Memory Devices for Implementing an Inference Engine
journal, August 2015

Synaptic metaplasticity in binarized neural networks
journal, May 2021

Neural algorithms and computing beyond Moore's law
journal, March 2019

Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference
journal, October 2017

Elementary depinning processes of magnetic domain walls under fields and currents
journal, October 2014

Magnetic domain wall neuron with lateral inhibition
journal, October 2018

Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator
journal, March 2018

Area-Efficient SOT-MRAM With a Schottky Diode
journal, August 2016

Efficacy and Stability of Quantal GABA Release at a Hippocampal Interneuron–Principal Neuron Synapse
journal, August 2000

Maximized lateral inhibition in paired magnetic domain wall racetracks for neuromorphic computing
journal, May 2020

Spin-Transfer Torque Magnetic Memory as a Stochastic Memristive Synapse for Neuromorphic Systems
journal, April 2015

Proposal for an All-Spin Artificial Neural Network: Emulating Neural and Synaptic Functionalities Through Domain Wall Motion in Ferromagnets
journal, December 2016

Graded-Anisotropy-Induced Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron
journal, June 2019

Magnetic Tunnel Junction Mimics Stochastic Cortical Spiking Neurons
journal, July 2016

A domain wall-magnetic tunnel junction artificial synapse with notched geometry for accurate and efficient training of deep neural networks
journal, May 2021

Intrinsic optimization using stochastic nanomagnets
journal, March 2017

Asymmetric ground state spin configuration of transverse domain wall on symmetrically notched ferromagnetic nanowires
journal, July 2010

Research progress on solutions to the sneak path issue in memristor crossbar arrays
journal, January 2020