• DocumentCode
    3602928
  • Title

    Coupled Spin Torque Nano Oscillators for Low Power Neural Computation

  • Author

    Yogendra, Karthik ; Deliang Fan ; Roy, Kaushik

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
  • Volume
    51
  • Issue
    10
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    We present coupled spin torque nano oscillators (STNOs) as electronic neurons for efficient brain-inspired computation. The coupled STNOs show two distinct outputs, depending on whether the frequencies are locked or not. The locking mechanisms are based on magnetic coupling or injection locking. The neuron firing threshold can be set by tuning the locking range of the coupled STNOs. We employ a crossbar array of programmable memory devices like memristors to implement electronic synapses that work seamlessly with the coupled STNOs for hardware implementation of neural networks. Results show that injection locking-based neuron model can be attractive from scaling point of view and computation like character recognition can be performed with energy consumption per neuron of ~1.8× and ~ 3× lower than the digital and the analog CMOS counterpart, respectively.
  • Keywords
    magnetoelectronics; nanoelectronics; neural nets; oscillators; brain inspired computation; character recognition; coupled spin torque nanooscillators; crossbar array; electronic neurons; electronic synapse; injection locking; low power neural computation; magnetic coupling; memristors; neuron firing threshold; programmable memory device; Couplings; Magnetization; Mathematical model; Neurons; Noise; Oscillators; Torque; Coupled spin torque nano oscillators (STNOs); coupled spin torque nano-oscillators; frequency locking; injection locking; low power; neural networks; programmable resistive crossbar;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/TMAG.2015.2443042
  • Filename
    7120163