175 citations · 648 across the 29 of their papers we have counts for
29 papers
Neuromorphic Hebbian learning with magnetic tunnel junction synapses
Peng Zhou, Alexander J. Edwards, Frederick B. Mancoff +3
Neuromorphic computing aims to mimic both the function and structure of biological neural networks to provide artificial intelligence with extreme efficiency. Conventional approach…
Cascaded Logic Gates Based on High-Performance Ambipolar Dual-Gate WSe2 Thin Film Transistors
Xintong Li, Peng Zhou, Xuan Hu +6
Ambipolar dual-gate transistors based on two-dimensional (2D) materials, such as graphene, carbon nanotubes, black phosphorus, and certain transition metal dichalcogenides (TMDs),…
Near-Landauer Reversible Skyrmion Logic with Voltage-Based Propagation
Benjamin W. Walker, Alexander J. Edwards, Xuan Hu +3
Magnetic skyrmions are topological quasiparticles whose non-volatility, detectability, and mobility make them exciting candidates for low-energy computing. Previous works have demo…
Roadmap for Unconventional Computing with Nanotechnology
Giovanni Finocchio, Jean Anne C. Incorvia, Joseph S. Friedman +48
In the "Beyond Moore's Law" era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same ti…
Efficient Quantum Circuit Design with a Standard Cell Approach, with an Application to Neutral Atom Quantum Computers
Evan E. Dobbs, Joseph S. Friedman, Alexandru Paler
We design quantum circuits by using the standard cell approach borrowed from classical circuit design, which can speed-up the layout of circuits with a regular structure. Our stand…
Logical and Physical Reversibility of Conservative Skyrmion Logic
Xuan Hu, Benjamin W. Walker, Felipe García-Sánchez +6
Magnetic skyrmions are nanoscale whirls of magnetism that can be propagated with electrical currents. The repulsion between skyrmions inspires their use for reversible computing ba…
Synchronous Unsupervised STDP Learning with Stochastic STT-MRAM Switching
Peng Zhou, Julie A. Smith, Laura Deremo +2
The use of analog resistance states for storing weights in neuromorphic systems is impeded by fabrication imprecision and device stochasticity that limit the precision of synapse w…
Experimental Demonstration of Neuromorphic Network with STT MTJ Synapses
Peng Zhou, Alexander J. Edwards, Fred B. Mancoff +3
We present the first experimental demonstration of a neuromorphic network with magnetic tunnel junction (MTJ) synapses, which performs image recognition via vector-matrix multiplic…
Focused Surface Acoustic Wave induced nano-oscillator based reservoir computing
Md. Fahim F. Chowdhury, Walid Al Misba, Md Mahadi Rajib +4
We demonstrate using micromagnetic simulations that a nanomagnet array excited by Surface Acoustic Waves (SAWs) can work as a reservoir that can classify sine and square waves with…
High-Speed CMOS-Free Purely Spintronic Asynchronous Recurrent Neural Network
Pranav O. Mathews, Christian B. Duffee, Abel Thayil +8
Neuromorphic computing systems overcome the limitations of traditional von Neumann computing architectures. These computing systems can be further improved upon by using emerging t…
Fast Swapping in a Quantum Multiplier Modelled as a Queuing Network
Evan E. Dobbs, Robert Basmadjian, Alexandru Paler +1
Predicting the optimum SWAP depth of a quantum circuit is useful because it informs the compiler about the amount of necessary optimization. Fast prediction methods will prove esse…
Analog Seizure Detection for Implanted Responsive Neurostimulation
Abbas A. Zaki, Noah C. Parker, Tae-Yoon Kim +9
Epilepsy can be treated with medication, however, of epileptic patients are still drug resistive. Devices like responsive neurostimluation systems are implanted in select pa…
Skyrmion Logic Clocked via Voltage Controlled Magnetic Anisotropy
Benjamin W. Walker, Can Cui, Felipe Garcia-Sanchez +3
Magnetic skyrmions are exciting candidates for energy-efficient computing due to their non-volatility, detectability,and mobility. A recent proposal within the paradigm of reversib…
Passive frustrated nanomagnet reservoir computing
Alexander J. Edwards, Dhritiman Bhattacharya, Peng Zhou +10
Reservoir computing (RC) has received recent interest because reservoir weights do not need to be trained, enabling extremely low-resource consumption implementations, which could…
Controllable reset behavior in domain wall-magnetic tunnel junction artificial neurons for task-adaptable computation
Samuel Liu, Christopher H. Bennett, Joseph S. Friedman +3
Neuromorphic computing with spintronic devices has been of interest due to the limitations of CMOS-driven von Neumann computing. Domain wall-magnetic tunnel junction (DW-MTJ) devic…
Domain Wall Leaky Integrate-and-Fire Neurons with Shape-Based Configurable Activation Functions
Wesley H. Brigner, Naimul Hassan, Xuan Hu +7
Complementary metal oxide semiconductor (CMOS) devices display volatile characteristics, and are not well suited for analog applications such as neuromorphic computing. Spintronic…
Domain Wall-Magnetic Tunnel Junction Spin Orbit Torque Devices and Circuits for In-Memory Computing
Mahshid Alamdar, Thomas Leonard, Can Cui +8
There are pressing problems with traditional computing, especially for accomplishing data-intensive and real-time tasks, that motivate the development of in-memory computing device…
Threshold Logic with Current-Driven Magnetic Domain Walls
Xuan Hu, Brighton A. Hill, Felipe Garcia-Sanchez +1
The recent demonstration of current-driven magnetic domain wall logic [Z. Luo et al., Nature 579:214] was based on a three-input logic gate that was identified as a reconfigurable…
Unsupervised Competitive Hardware Learning Rule for Spintronic Clustering Architecture
Alvaro Velasquez, Christopher H. Bennett, Naimul Hassan +5
We propose a hardware learning rule for unsupervised clustering within a novel spintronic computing architecture. The proposed approach leverages the three-terminal structure of do…
Reservoir Computing with Planar Nanomagnet Arrays
Peng Zhou, Nathan R. McDonald, Alexander J. Edwards +3
Reservoir computing is an emerging methodology for neuromorphic computing that is especially well-suited for hardware implementations in size, weight, and power (SWaP) constrained…
CMOS-Free Multilayer Perceptron Enabled by Four-Terminal MTJ Device
Wesley H. Brigner, Naimul Hassan, Xuan Hu +5
Neuromorphic computing promises revolutionary improvements over conventional systems for applications that process unstructured information. To fully realize this potential, neurom…
Hybrid Pass Transistor Logic with Ambipolar Transistors
Xuan Hu, Amy S. Abraham, Jean Anne C. Incorvia +1
In comparison to the conventional complementary pull-up and pull-down logic structure, the pass transistor logic (PTL) family reduces the number of transistors required to perform…
Maximized Lateral Inhibition in Paired Magnetic Domain Wall Racetracks for Neuromorphic Computing
C. Cui, O. G. Akinola, N. Hassan +4
Lateral inhibition is an important functionality in neuromorphic computing, modeled after the biological neuron behavior that a firing neuron deactivates its neighbors belonging to…
Exploiting Dual-Gate Ambipolar CNFETs for Scalable Machine Learning Classification
Farid Kenarangi, Xuan Hu, Yihan Liu +3
Ambipolar carbon nanotube based field-effect transistors (AP-CNFETs) exhibit unique electrical characteristics, such as tri-state operation and bi-directionality, enabling systems…