Nanoscale Room-Temperature Multilayer Skyrmionic Synapse for Deep Spiking Neural Networks
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Steve Furber | Vasilis F. Pavlidis | Christoforos Moutafis | Giacomo Indiveri | Runze Chen | Chen Li | Yu Li | James J. Miles | S. Furber | J. Miles | V. Pavlidis | C. Moutafis | G. Indiveri | Runze Chen | Yu Li | Chen Li
[1] Bin Gao,et al. Fully hardware-implemented memristor convolutional neural network , 2020, Nature.
[2] A. Locatelli,et al. Room-temperature chiral magnetic skyrmions in ultrathin magnetic nanostructures. , 2016, Nature nanotechnology.
[3] Chiara Bartolozzi,et al. Neuromorphic Electronic Circuits for Building Autonomous Cognitive Systems , 2014, Proceedings of the IEEE.
[4] J. Bland,et al. Dynamics and switching processes for magnetic bubbles in nanoelements , 2009 .
[5] P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .
[6] Xiaofei Wang,et al. Convergence of Edge Computing and Deep Learning: A Comprehensive Survey , 2019, IEEE Communications Surveys & Tutorials.
[7] C. Pfleiderer,et al. Emergent electrodynamics of skyrmions in a chiral magnet , 2012, Nature Physics.
[8] A. Fert,et al. Skyrmions on the track. , 2013, Nature nanotechnology.
[9] Tsuyoshi Murata,et al. {m , 1934, ACML.
[10] A. Khorsand,et al. Laser-induced magnetic nanostructures with tunable topological properties. , 2013, Physical review letters.
[11] G. Finocchio,et al. A strategy for the design of skyrmion racetrack memories , 2014, Scientific Reports.
[12] Steve B. Furber,et al. Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms , 2015, Front. Neurosci..
[13] Damien Querlioz,et al. Neuromorphic computing with nanoscale spintronic oscillators , 2017, Nature.
[14] Danna Zhou,et al. d. , 1934, Microbial pathogenesis.
[15] A. Fert,et al. Hybrid chiral domain walls and skyrmions in magnetic multilayers , 2017, Science Advances.
[16] Carver A. Mead,et al. Neuromorphic electronic systems , 1990, Proc. IEEE.
[17] Yan Zhou,et al. Magnetic skyrmion-based synaptic devices , 2016, Nanotechnology.
[18] Walter Senn,et al. Learning Real-World Stimuli in a Neural Network with Spike-Driven Synaptic Dynamics , 2007, Neural Computation.
[19] Xing Chen,et al. A compact skyrmionic leaky-integrate-fire spiking neuron device. , 2018, Nanoscale.
[20] Timothée Masquelier,et al. Deep Learning in Spiking Neural Networks , 2018, Neural Networks.
[21] Deliang Fan,et al. A tunable magnetic skyrmion neuron cluster for energy efficient artificial neural network , 2017, Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017.
[22] Dharmendra S. Modha,et al. The cat is out of the bag: cortical simulations with 109 neurons, 1013 synapses , 2009, Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis.
[23] F. García-Sánchez,et al. The design and verification of MuMax3 , 2014, 1406.7635.
[24] S. Sarma,et al. Spintronics: Fundamentals and applications , 2004, cond-mat/0405528.
[25] A. Fert,et al. Nucleation, stability and current-induced motion of isolated magnetic skyrmions in nanostructures. , 2013, Nature nanotechnology.
[26] Andrew S. Cassidy,et al. A million spiking-neuron integrated circuit with a scalable communication network and interface , 2014, Science.
[27] D. Ralph,et al. Spin Torque Study of the Spin Hall Conductivity and Spin Diffusion Length in Platinum Thin Films with Varying Resistivity. , 2015, Physical review letters.
[28] A. Tulapurkar,et al. Large voltage-induced magnetic anisotropy change in a few atomic layers of iron. , 2009, Nature nanotechnology.
[29] A. Fert,et al. Additive interfacial chiral interaction in multilayers for stabilization of small individual skyrmions at room temperature. , 2016, Nature nanotechnology.
[30] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[31] Hesham Mostafa,et al. Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-based optimization to spiking neural networks , 2019, IEEE Signal Processing Magazine.
[32] M. Stiles,et al. Neuromorphic spintronics , 2020, Nature Electronics.
[33] Osvaldo Simeone,et al. Federated Neuromorphic Learning of Spiking Neural Networks for Low-Power Edge Intelligence , 2019, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[34] Romain Brette,et al. Neuroinformatics Original Research Article Brian: a Simulator for Spiking Neural Networks in Python , 2022 .
[35] Motohiko Ezawa,et al. Skyrmion-electronics: writing, deleting, reading and processing magnetic skyrmions toward spintronic applications , 2019, Journal of physics. Condensed matter : an Institute of Physics journal.
[36] Massimiliano Di Ventra,et al. Experimental demonstration of associative memory with memristive neural networks , 2009, Neural Networks.
[37] G. Schütz,et al. The role of temperature and drive current in skyrmion dynamics , 2020 .
[38] Giacomo Indiveri,et al. A neuromorphic systems approach to in-memory computing with non-ideal memristive devices: From mitigation to exploitation , 2018, Faraday discussions.
[39] Indranil Chakraborty,et al. Technology Aware Training in Memristive Neuromorphic Systems for Nonideal Synaptic Crossbars , 2017, IEEE Transactions on Emerging Topics in Computational Intelligence.
[40] J. W. Brown. Thermal Fluctuations of a Single-Domain Particle , 1963 .
[41] Benjamin Krueger,et al. Observation of room-temperature magnetic skyrmions and their current-driven dynamics in ultrathin metallic ferromagnets. , 2015, Nature materials.
[42] I. Dzyaloshinsky. A thermodynamic theory of “weak” ferromagnetism of antiferromagnetics , 1958 .
[43] PHARMACOLOGY AND NERVE ENDINGS , 1934 .
[45] Simone Finizio,et al. Magnetic skyrmion artificial synapse for neuromorphic computing , 2019, ArXiv.
[46] G. Beach,et al. Twisted domain walls and skyrmions in perpendicularly magnetized multilayers , 2018, Physical Review B.
[47] Yusuf Leblebici,et al. Neuromorphic computing with multi-memristive synapses , 2017, Nature Communications.
[48] Weisheng Zhao,et al. Low-Power (1T1N) Skyrmionic Synapses for Spiking Neuromorphic Systems , 2018, IEEE Access.
[49] A. Umerski,et al. Theory of tunneling magnetoresistance of an epitaxial Fe/MgO/Fe(001) junction , 2001 .
[50] Xing Chen,et al. Emerging Neuromorphic Computing Paradigms Exploring Magnetic Skyrmions , 2018, 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI).
[51] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[52] A. Fert,et al. Room-Temperature Current-Induced Generation and Motion of sub-100 nm Skyrmions. , 2017, Nano letters.
[53] P. Böni,et al. Spin Transfer Torques in MnSi at Ultralow Current Densities , 2010, Science.
[54] J. Miltat,et al. Path to collapse for an isolated Néel skyrmion , 2016, 1601.02875.
[55] Benjamin Krueger,et al. Magnetic Skyrmion as a Nonlinear Resistive Element: A Potential Building Block for Reservoir Computing , 2017, 1702.04298.
[56] Matthew Cook,et al. Unsupervised learning of digit recognition using spike-timing-dependent plasticity , 2015, Front. Comput. Neurosci..
[57] T. Serrano-Gotarredona,et al. STDP and STDP variations with memristors for spiking neuromorphic learning systems , 2013, Front. Neurosci..
[58] Kaiming He,et al. Exploring the Limits of Weakly Supervised Pretraining , 2018, ECCV.
[59] Mathias Kläui,et al. Perspective: Magnetic skyrmions—Overview of recent progress in an active research field , 2018, Journal of Applied Physics.
[60] J. Xia,et al. An Improved Racetrack Structure for Transporting a Skyrmion , 2017, Scientific Reports.
[61] Steve B. Furber,et al. The SpiNNaker Project , 2014, Proceedings of the IEEE.
[62] Johannes Schemmel,et al. A wafer-scale neuromorphic hardware system for large-scale neural modeling , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.
[63] H. Dale. Pharmacology and Nerve-Endings , 1935 .
[64] Y. Tokura,et al. Skyrmion flow near room temperature in an ultralow current density , 2012, Nature Communications.
[65] J. Nývlt. Nucleation , 1991 .
[66] A. Panchula,et al. Giant tunnelling magnetoresistance at room temperature with MgO (100) tunnel barriers , 2004, Nature materials.
[67] Masahiro Sato,et al. Ultrafast generation of skyrmionic defects with vortex beams: Printing laser profiles on magnets , 2016, 1609.06816.
[68] N. Kiselev,et al. Chiral magnetic skyrmions with arbitrary topological charge , 2018, Physical Review B.
[69] T. Devolder,et al. Planar patterned magnetic media obtained by ion irradiation , 1998, Science.
[70] Jennifer Hasler,et al. Finding a roadmap to achieve large neuromorphic hardware systems , 2013, Front. Neurosci..
[71] Yan Zhou,et al. Skyrmions in Magnetic Tunnel Junctions. , 2018, ACS applied materials & interfaces.
[72] Matthew Cook,et al. Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing , 2015, 2015 International Joint Conference on Neural Networks (IJCNN).
[73] Kaushik Roy,et al. Hybrid Spintronic-CMOS Spiking Neural Network With On-Chip Learning: Devices, Circuits and Systems , 2015, ArXiv.
[74] S. Le,et al. Perpendicular spin transfer torque magnetic random access memories with high spin torque efficiency and thermal stability for embedded applications (invited) , 2014 .
[75] Farnood Merrikh-Bayat,et al. Training and operation of an integrated neuromorphic network based on metal-oxide memristors , 2014, Nature.
[76] A. Locatelli,et al. Current-Driven Skyrmion Dynamics and Drive-Dependent Skyrmion Hall Effect in an Ultrathin Film , 2019, Physical Review Applied.