66 citations · 97 across the 10 of their papers we have counts for
10 papers
Kinematic Model of Magnetic Domain Wall Motion for Fast, High-Accuracy Simulations
Kristi Doleh, Leonard Humphrey, Chandler M. Linseisen +8
Domain wall (DW) devices have garnered recent interest for diverse applications including memory, logic, and neuromorphic primitives; fast, accurate device models are therefore imp…
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…
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…
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…
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…
Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning
Christopher H. Bennett, T. Patrick Xiao, Can Cui +6
Machine learning implements backpropagation via abundant training samples. We demonstrate a multi-stage learning system realized by a promising non-volatile memory device, the doma…
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…
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…
Shape-based Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron
Wesley H. Brigner, Naimul Hassan, Lucian Jiang-Wei +7
Spintronic devices based on domain wall (DW) motion through ferromagnetic nanowire tracks have received great interest as components of neuromorphic information processing systems.…
Toggle Spin-Orbit Torque MRAM with Perpendicular Magnetic Anisotropy
Naimul Hassan, Susana P. Lainez-Garcia, Felipe Garcia-Sanchez +1
Spin-orbit torque (SOT) is a promising switching mechanism for magnetic random-access memory (MRAM) as a result of the potential for improved switching speed and energy-efficiency.…