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LAO-NCS: Laser Assisted Spin Torque Nano Oscillator-Based Neuromorphic Computing System.

Hooman Farkhani1, Tim Böhnert2, Mohammad Tarequzzaman2

  • 1Integrated Circuits and Electronics Laboratory, Department of Engineering, Aarhus University, Aarhus, Denmark.

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Summary

This study introduces a laser-assisted neuromorphic computing system (NCS) that significantly reduces power consumption in spintronic devices. By using laser pulses to aid spin torque nano-oscillators (STNOs), researchers achieved substantial energy savings for brain-inspired computing.

Keywords:
COMSOL multiphysicslaserneuromorphic computing systempower efficientspin torque nano-oscillators

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Area of Science:

  • Neuromorphic Computing Systems (NCS)
  • Spintronics
  • Advanced Materials Science

Background:

  • Conventional Von Neumann architectures struggle with big data processing, unlike the human brain's parallel processing capabilities.
  • Neuromorphic computing systems (NCS) offer a brain-inspired parallel processing solution.
  • Spintronic-based NCS, utilizing magnetic tunnel junctions (MTJs) and spin torque nano-oscillators (STNOs), show promise for low-power, high-density computing but face high power consumption challenges.

Purpose of the Study:

  • To propose and demonstrate a novel spintronic-based NCS that significantly reduces power consumption.
  • To investigate the efficacy of using laser pulses to assist STNO oscillations and lower energy demands.
  • To quantify the power and energy consumption improvements in a laser-assisted neuromorphic computing system (LAO-NCS).

Main Methods:

  • Developed a proof-of-concept spintronic-based NCS (196 × 10) incorporating STNOs and memristors.
  • Assisted STNO oscillation by applying microwatt nanosecond laser pulses.
  • Experimentally measured power consumption of STNOs and the spintronic layer at elevated temperatures (100°C) compared to room temperature.

Main Results:

  • STNO power consumption decreased by 55.3% at 100°C due to laser-assisted oscillation.
  • Average power consumption of the spintronic layer (STNOs and memristor array) reduced by 54.9% at 100°C.
  • The proposed laser-assisted STNO-based NCS (LAO-NCS) demonstrated a 40% improvement in total power consumption at 100°C compared to conventional STNO-based NCS at room temperature.

Conclusions:

  • Laser assistance is an effective method for reducing the power consumption of spintronic neurons (STNOs) in NCS.
  • The LAO-NCS offers significant energy efficiency improvements, with an expected 86% reduction compared to conventional systems.
  • This approach paves the way for more energy-efficient and high-density brain-inspired computing systems.