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Non-Boolean computing with nanomagnets for computer vision applications

Nature Nanotechnology volume 11, pages 177–183 (2016)Cite this article

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Abstract

The field of nanomagnetism has recently attracted tremendous attention as it can potentially deliver low-power, high-speed and dense non-volatile memories. It is now possible to engineer the size, shape, spacing, orientation and composition of sub-100 nm magnetic structures. This has spurred the exploration of nanomagnets for unconventional computing paradigms. Here, we harness the energy-minimization nature of nanomagnetic systems to solve the quadratic optimization problems that arise in computer vision applications, which are computationally expensive. By exploiting the magnetization states of nanomagnetic disks as state representations of a vortex and single domain, we develop a magnetic Hamiltonian and implement it in a magnetic system that can identify the salient features of a given image with more than 85% true positive rate. These results show the potential of this alternative computing method to develop a magnetic coprocessor that might solve complex problems in fewer clock cycles than traditional processors.

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Figure 1: Stages in object recognition.
Figure 2: Schematic of the magnetization state abstraction model.
Figure 3: Steps involved in determining salient edges using the nanomagnetic coprocessor.
Figure 4: Perceptual organization results for an image, obtained using fabricated nanomagnetic systems.
Figure 5: Hardware schematics of envisioned magnetic coprocessor.

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Acknowledgements

The authors thank the Nanotechnology Research and Education Center at the University of South Florida and the National Science Foundation. This work was supported in part by NSF CAREER grant no. 0639624, NSF (CRI) grant no. 0551621 and NSF (EMT) grant no. 0829838. The authors thank J. Pulecio and A. Kumari for their earlier research.

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Author notes

  1. D. K. Karunaratne and Ravi Panchumarthy: These authors contributed equally to this work

Authors and Affiliations

  1. Department of Electrical Engineering, University of South Florida, Tampa, 33620, Florida, USA

    Sanjukta Bhanja, D. K. Karunaratne & Srinath Rajaram

  2. Department of Computer Science & Engineering, University of South Florida, Tampa, 33620, Florida, USA

    Ravi Panchumarthy & Sudeep Sarkar

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  1. Sanjukta Bhanja
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Contributions

S.B. and S.S. proposed and supervised the project. The entire team was involved in modelling and analytical framework. R.P. implemented software code for the analytical and mathematical modelling of the nanomagnetic system under S.S's guidance. R.P. ran experiments for speed comparisons and prepared responses for the reviews with S.B. and S.S. supervision. D.K. fabricated the nanomagnetic systems and performed fabrication experiments. D.K and S.B. analysed the results of fabrication experiments. S.R. performed micromagnetic simulation experiments and programmability of the grid, with S.B's guidance. D.K. and R.P. prepared the initial draft of the paper. All authors discussed the results and modified the manuscript.

Corresponding author

Correspondence to Sanjukta Bhanja.

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The authors declare no competing financial interests.

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Bhanja, S., Karunaratne, D., Panchumarthy, R. et al. Non-Boolean computing with nanomagnets for computer vision applications. Nature Nanotech 11, 177–183 (2016). https://doi.org/10.1038/nnano.2015.245

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