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Spintronic neural systems

Nature Reviews Electrical Engineering volume 1, pages 714–729 (2024)Cite this article

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Abstract

Neural computing, guided by brain-inspired computational frameworks, promises to realize various cognitive and perception-related tasks. Complementary metal–oxide–semiconductor-based computing machines use orders-of-magnitude more computational resources than the brain on cognitive tasks that humans efficiently perform every day. As a result, we are witnessing a seismic shift in the field of computation. Research efforts are being directed to develop artificial intelligence (AI) hardware that mimics the human brain from a bottom-up perspective — through devices that are more naturally suited to neural computation — and thereby improves the efficiency of performing cognitive tasks. In the attempt to bridge the gap between neuroscience and electronics, here we report on developments in the field of spintronic devices for AI hardware. The dynamics of spintronic devices that can be used for the realization of neural and synaptic functionalities are discussed. A cross-layer perspective extending from the device to the circuit and system levels as a pathway towards efficient neural computing systems is also presented.

Key points

  • Neural computing, guided by brain-like computational frameworks, promises to realize various cognitive and perception-related tasks.

  • Complementary metal–oxide–semiconductor (CMOS) transistors, being on/off switches, are ideally suited for Boolean functions. CMOS-based neural computing on von Neumann architectures consumes orders-of-magnitude higher energy than biological brains.

  • Spin-transfer-torque-based device dynamics can efficiently mimic neuronal and synaptic functionalities.

  • A cross-layer co-design approach extending from the device to the circuit and system levels can lead to efficient neural computing systems.

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Fig. 1: System and technology co-design for spintronic neural systems.
Fig. 2: Behaviours and driving mechanisms of magnetic tunnel junction (MTJ)-based devices.
Fig. 3: Comparison between biological neuronal dynamics and magnetic tunnel junction (MTJ)-based spiking neuron.
Fig. 4: Crossbar array implementation of magnetic tunnel junction-based spiking neural network.
Fig. 5: Examples of reduction in energy consumption using spintronic memory devices.
Fig. 6: Neural computing based on stochastic magnetic tunnel junction.

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Authors and Affiliations

  1. Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA

    Kaushik Roy, Sourjya Roy & Anand Raghunathan

  2. Electrical and Computer Engineering, Iowa State University, Ames, IA, USA

    Cheng Wang

  3. Microelectronics Thrust, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

    Kezhou Yang

  4. School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, PA, USA

    Abhronil Sengupta

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  1. Kaushik Roy
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  2. Cheng Wang
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  3. Sourjya Roy
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  4. Anand Raghunathan
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K.R., C.W., S.R. and A.S. substantially contributed to discussion of content and writing. All authors researched data for the Review and contributed to reviewing and/or editing the manuscript before submission.

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Glossary

Bloch walls

Domain-wall magnetization rotates in the plane of the wall.

Dzyaloshinskii–Moriya interaction

A type of exchange interaction observed in magnetic heterostructures.

Ising model

A statistical model of interacting spins on a lattice, where the energy depends on neighbouring spin alignment and an external field.

Magnetoelectric effect

This effect occurs when a material’s magnetization changes due to applied electric fields.

Néel walls

Domain-wall magnetization rotates in a plane perpendicular to the plane of the wall.

Non-deterministic polynomial-time hard problems

Computational problems for which no efficient solution algorithm is known, and solving or verifying a solution is as hard as the most challenging problems in NP (non-deterministic polynomial time).

Telegraphic switching

Subnanosecond switching regime of magnets where the magnetization undergoes volatile state transitions for low-barrier-height magnets.

Travelling salesman problem

A mathematical problem that asks to search for the shortest possible route that traverses a given list of cities in a map exactly once and returns to the origin.

Voltage-controlled magnetic anisotropy

A physical phenomenon that enables modulation of magnetic anisotropy by applying an electric voltage.

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Roy, K., Wang, C., Roy, S. et al. Spintronic neural systems. Nat Rev Electr Eng 1, 714–729 (2024). https://doi.org/10.1038/s44287-024-00107-9

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