Ultra-low Power Domain Wall Device for Spin-based Neuromorphic Computing

Abstract

Neuromorphic computing (NC) is gaining wide acceptance as a potential technology to achieve low-power intelligent devices. To realize NC, researchers investigate various types of synthetic neurons and synaptic devices such as memristors and spintronic domain wall (DW) devices. In comparison, DW-based neurons and synapses have potentially higher endurance. However, for realizing low-power devices, DW motion at low energies - typically below pJ/bit - are needed. Here, we demonstrate domain wall motion at current densities as low as 1E6 A/m2 by tailoring the beta-W spin Hall material. With our design, we achieve ultra-low pinning fields and current density reduction by a factor of 10000. The energy required to move the domain wall by a distance of about 20 micrometers is 0.4 fJ, which translates into energy consumption of 0.4 aJ/bit for a bit-length of 20 nm. With a meander domain wall device configuration, we have established a controlled DW motion for synapse applications and have shown the direction to make ultra-low energy spin-based neuromorphic elements.

17 pages, 4 figures

References in corpus (6)

• Current-driven dynamics of chiral ferromagnetic domain walls
• A ferroelectric memristor
• Proposal for an All-Spin Artificial Neural Network: Emulating Neural and Synaptic Functionalities Through Domain Wall Motion in Ferromagnets
• Giant Enhancement of Intrinsic Spin Hall Conductivity in $\beta$ Tungsten via Substitutional Doping
• On-chip learning for domain wall synapse based Fully Connected Neural Network
• Domain wall-based spin-Hall nano-oscillators