Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Neuromorphic computing with nanoscale spintronic oscillators

Nature volume 547, pages 428–431 (2017)Cite this article

Subjects

Abstract

Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information1. Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nanoscale nonlinear oscillators. A simple estimation indicates that to fit 108 oscillators organized in a two-dimensional array inside a chip the size of a thumb, the lateral dimension of each oscillator must be smaller than one micrometre. However, nanoscale devices tend to be noisy and to lack the stability that is required to process data in a reliable way. For this reason, despite multiple theoretical proposals2,3,4,5 and several candidates, including memristive6 and superconducting7 oscillators, a proof of concept of neuromorphic computing using nanoscale oscillators has yet to be demonstrated. Here we show experimentally that a nanoscale spintronic oscillator (a magnetic tunnel junction)8,9 can be used to achieve spoken-digit recognition with an accuracy similar to that of state-of-the-art neural networks. We also determine the regime of magnetization dynamics that leads to the greatest performance. These results, combined with the ability of the spintronic oscillators to interact with each other, and their long lifetime and low energy consumption, open up a path to fast, parallel, on-chip computation based on networks of oscillators.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Spin-torque nano-oscillator for neuromorphic computing.
Figure 2: Spoken-digit recognition.
Figure 3: Conditions for optimal waveform classification and identification of important oscillator properties.

Similar content being viewed by others

References

  1. Buzsaki, G. Rhythms of the Brain (Oxford Univ. Press, 2011)

  2. Hoppensteadt, F. C. & Izhikevich, E. M. Oscillatory neurocomputers with dynamic connectivity. Phys. Rev. Lett. 82, 2983–2986 (1999)

    Article  ADS  CAS  Google Scholar 

  3. Aonishi, T., Kurata, K. & Okada, M. Statistical mechanics of an oscillator associative memory with scattered natural frequencies. Phys. Rev. Lett. 82, 2800–2803 (1998)

    Article  ADS  Google Scholar 

  4. Jaeger, H. & Haas, H. Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication. Science 304, 78–80 (2004)

    Article  ADS  CAS  Google Scholar 

  5. Maass, W., Natschläger, T. & Markram, H. Real-time computing without stable states: a new framework for neural computation based on perturbations. Neural Comput. 14, 2531–2560 (2002)

    Article  Google Scholar 

  6. Pickett, M. D., Medeiros-Ribeiro, G. & Williams, R. S. A scalable neuristor built with Mott memristors. Nat. Mater. 12, 114–117 (2013)

    Article  ADS  CAS  Google Scholar 

  7. Segall, K. et al. Synchronization dynamics on the picosecond time scale in coupled Josephson junction neurons. Phys. Rev. E 95, 032220 (2017)

    Article  ADS  CAS  Google Scholar 

  8. Kiselev, S. I. et al. Microwave oscillations of a nanomagnet driven by a spin-polarized current. Nature 425, 380–383 (2003)

    Article  ADS  CAS  Google Scholar 

  9. Rippard, W. H., Pufall, M. R., Kaka, S., Russek, S. E. & Silva, T. J. Direct-current induced dynamics in Co90Fe10/Ni80Fe20 point contacts. Phys. Rev. Lett. 92, 027201 (2004)

    Article  ADS  CAS  Google Scholar 

  10. Slonczewski, J. C. Current-driven excitation of magnetic multilayers. J. Magn. Magn. Mater. 159, L1–L7 (1996)

    Article  ADS  CAS  Google Scholar 

  11. Berger, L. Emission of spin waves by a magnetic multilayer traversed by a current. Phys. Rev. B 54, 9353–9358 (1996)

    Article  ADS  CAS  Google Scholar 

  12. Tsunegi, S., Yakushiji, K., Fukushima, A., Yuasa, S. & Kubota, H. Microwave emission power exceeding 10 μW in spin torque vortex oscillator. Appl. Phys. Lett. 109, 252402 (2016)

    Article  ADS  Google Scholar 

  13. Sato, H. et al. Properties of magnetic tunnel junctions with a MgO/CoFeB/Ta/CoFeB/MgO recording structure down to junction diameter of 11 nm. Appl. Phys. Lett. 105, 062403 (2014)

    Article  ADS  Google Scholar 

  14. Apalkov, D., Dieny, B. & Slaughter, J. M. Magnetoresistive random access memory. Proc. IEEE 104, 1796–1830 (2016)

    Article  CAS  Google Scholar 

  15. Slavin, A. & Tiberkevich, V. Nonlinear auto-oscillator theory of microwave generation by spin-polarized current. IEEE Trans. Magn. 45, 1875–1918 (2009)

    Article  ADS  CAS  Google Scholar 

  16. Houshang, A. et al. Spin-wave-beam driven synchronization of nanocontact spin-torque oscillators. Nat. Nanotechnol. 11, 280–286 (2016)

    Article  ADS  CAS  Google Scholar 

  17. Macià, F., Kent, A. D. & Hoppensteadt, F. C. Spin-wave interference patterns created by spin-torque nano-oscillators for memory and computation. Nanotechnology 22, 095301 (2011)

    Article  ADS  Google Scholar 

  18. Pufall, M. R. et al. Physical implementation of coherently coupled oscillator networks. IEEE J. Explor. Solid-State Comput. Devices Circuits 1, 76–84 (2015)

    Article  ADS  Google Scholar 

  19. Nikonov, D. E. et al. Coupled-oscillator associative memory array operation for pattern recognition. IEEE J. Explor. Solid-State Comput. Devices Circuits 1, 85–93 (2015)

    Article  ADS  Google Scholar 

  20. Yogendra, K., Fan, D. & Roy, K. Coupled spin torque nano oscillators for low power neural computation. IEEE Trans. Magn. 51, 4003909 (2015)

    Article  Google Scholar 

  21. Grollier, J., Querlioz, D. & Stiles, M. D. Spintronic nanodevices for bioinspired computing. Proc. IEEE 104, 2024–2039 (2016)

    Article  Google Scholar 

  22. Grimaldi, E. et al. Response to noise of a vortex based spin transfer nano-oscillator. Phys. Rev. B 89, 104404 (2014)

    Article  ADS  Google Scholar 

  23. Soriano, M. C. et al. Delay-based reservoir computing: noise effects in a combined analog and digital implementation. IEEE Trans. Neural Netw. Learn. Syst. 26, 388–393 (2015)

    Article  MathSciNet  Google Scholar 

  24. Appeltant, L. et al. Information processing using a single dynamical node as complex system. Nat. Commun. 2, 468 (2011)

    Article  ADS  CAS  Google Scholar 

  25. Paquot, Y. et al. Optoelectronic reservoir computing. Sci. Rep. 2, 287 (2012)

    Article  CAS  Google Scholar 

  26. Martinenghi, R., Rybalko, S., Jacquot, M., Chembo, Y. K. & Larger, L. Photonic nonlinear transient computing with multiple-delay wavelength dynamics. Phys. Rev. Lett. 108, 244101 (2012)

    Article  ADS  Google Scholar 

  27. Texas Instruments. 46-Word Speaker-Dependent Isolated Word Corpus (TI-46), NIST Speech Disc 7-1.1, https://catalog.ldc.upenn.edu/LDC93S9 (NIST, 1991)

  28. LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015)

    Article  ADS  CAS  Google Scholar 

  29. Yildiz, I. B., von Kriegstein, K. & Kiebel, S. J. From birdsong to human speech recognition: Bayesian inference on a hierarchy of nonlinear dynamical systems. PLOS Comput. Biol. 9, e1003219 (2013)

    Article  ADS  CAS  Google Scholar 

  30. Lyon, R. A computational model of filtering, detection, and compression in the cochlea. in IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP 82) Vol. 7, 1282–1285 (IEEE, 1982)

    Chapter  Google Scholar 

Download references

Acknowledgements

This work was supported by the European Research Council (ERC) under grant bioSPINspired 682955. We thank L. Larger, B. Penkovsky and F. Duport for discussions.

Author information

Author notes

  1. Guru Khalsa

    Present address: Department of Materials Science and Engineering, Cornell University, Ithaca, New York, 14853-1501, USA

Authors and Affiliations

  1. Unité Mixte de Physique, CNRS, Thales, Université Paris-Sud, Université Paris-Saclay, Palaiseau, 91767, France

    Jacob Torrejon, Mathieu Riou, Flavio Abreu Araujo, Paolo Bortolotti, Vincent Cros & Julie Grollier

  2. National Institute of Advanced Industrial Science and Technology (AIST), Spintronics Research Center, Tsukuba, 305-8568, Ibaraki, Japan

    Sumito Tsunegi, Kay Yakushiji, Akio Fukushima, Hitoshi Kubota & Shinji Yuasa

  3. Center for Nanoscale Science and Technology, National Institute of Standards and Technology, Gaithersburg, 20899-6202, Maryland, USA

    Guru Khalsa & Mark D. Stiles

  4. Centre de Nanosciences et de Nanotechnologies, CNRS, Université Paris-Sud, Université Paris-Saclay, Orsay, 91405, France

    Damien Querlioz

Authors
  1. Jacob Torrejon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mathieu Riou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Flavio Abreu Araujo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sumito Tsunegi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Guru Khalsa
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Damien Querlioz
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Paolo Bortolotti
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Vincent Cros
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Kay Yakushiji
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Akio Fukushima
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Hitoshi Kubota
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Shinji Yuasa
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Mark D. Stiles
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Julie Grollier
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The study was designed by J.G. and M.D.S., samples were optimized and fabricated by S.T. and K.Y., experiments were performed by J.T. and M.R., numerical studies were realized by F.A.A., M.R. and G.K., and all authors contributed to analysing the results and writing the paper.

Corresponding author

Correspondence to Julie Grollier.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks F. Hoppensteadt and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related audio

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Torrejon, J., Riou, M., Araujo, F. et al. Neuromorphic computing with nanoscale spintronic oscillators. Nature 547, 428–431 (2017). https://doi.org/10.1038/nature23011

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature23011

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing