Related papers: Voltage Gated Domain Wall Magnetic Tunnel Junction…
Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to…
Nanomagnets driven by spin currents provide a natural implementation for a neuron and a synapse: currents allow convenient summation of multiple inputs, while the magnet provides the threshold function. The objective of this paper is to…
In crossbar array structures, which serves as an "In-Memory" compute engine for Artificial Intelligence hardware, write sneak path problem causes undesired switching of devices that degrades network accuracy. While custom crossbar…
Over the past few years, Spiking Neural Networks (SNNs) have become popular as a possible pathway to enable low-power event-driven neuromorphic hardware. However, their application in machine learning have largely been limited to very…
We demonstrate for the first time that functionally complete digital logic can be created by using three terminal devices each consisting of a magnetic tunnel junction (MTJ) and spin transfer torque (STT) element with a shared free magnetic…
The electrically readable complex dynamics of robust and scalable magnetic tunnel junctions (MTJs) offer promising opportunities for advancing neuromorphic computing. In this work, we present an MTJ design with a free layer and two…
Spin-orbit torque provides an efficient pathway to manipulate the magnetic state and magnetization dynamics of magnetic materials, which is crucial for energy-efficient operation of a variety of spintronic devices such as magnetic memory,…
Large spiking neural networks (SNNs) require ultra-low power and low variability hardware for neuromorphic computing applications. Recently, a band-to-band tunneling-based (BTBT) integrator, enabling sub-kHz operation of neurons with area…
Recently, it was demonstrated that field-free switching could be achieved by combining spin-orbit torque (SOT) and Dzyaloshinskii-Moriya interaction (DMI). However, this mechanism only occurs under certain conditions which have not been…
With the wide application of 3D object detection in some fields such as autonomous driving, its energy consumption is constantly increasing, making the research on low-power consumption alternatives a key research area. The spiking neural…
Physical devices exhibiting stochastic functions with low energy consumption and high device density have the potential to enable complex probability-based computing algorithms, accelerate machine learning tasks, and enhance hardware…
The human brain comprises about a hundred billion neurons connected through quadrillion synapses. Spiking Neural Networks (SNNs) take inspiration from the brain to model complex cognitive and learning tasks. Neuromorphic engineering…
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 NAND/NOR function. We reinterpret this logic gate as a…
Future applications of spin-orbit torque will require new mechanisms to improve the efficiency for switching nanoscale magnetic tunnel junctions (MTJs), while also controlling the magnetic dynamics to achieve fast, nanosecond scale…
We propose an electrically driven spin injector into normal metals and semiconductors, which is based on a magnetic tunnel junction (MTJ) subjected to a microwave voltage. Efficient functioning of such an injector is provided by…
We predict a fast domain wall (DW) motion induced by a thermal gradient across a nanoscopic ferromagnetic stripe of MnBi. The driving mechanism is an exchange torque fueled by magnon accumulation at the DWs. Depending on the thickness of…
Spiking Neural Networks are a recent and new neural network design approach that promises tremendous improvements in power efficiency, computation efficiency, and processing latency. They do so by using asynchronous spike-based data flow,…
Current-driven magnetic domain wall motion is demonstrated in the quaternary ferromagnetic semiconductor (Ga,Mn)(As,P) at temperatures well below the ferromagnetic transition temperature, with critical currents of the order 10^5Acm^-2. This…
Using type-x spin-orbit torque (SOT) switching scheme, in which the easy axis (EA) of the ferromagnetic (FM) layer and the charge current flow direction are collinear, is possible to realize a lower-power-consumption, higher-density, and…
Conventional neural structures tend to communicate through analog quantities such as currents or voltages, however, as CMOS devices shrink and supply voltages decrease, the dynamic range of voltage/current-domain analog circuits becomes…