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Hardware design and the competency awareness of a neural network

Nature Electronics volume 3, pages 514–523 (2020)Cite this article

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Abstract

The ability to estimate the uncertainty of predictions made by a neural network is essential when applying neural networks to tasks such as medical diagnosis and autonomous vehicles. The approach is of particular relevance when deploying the networks on devices with limited hardware resources, but existing competency-aware neural networks largely ignore any resource constraints. Here we examine the relationship between hardware platforms and the competency awareness of a neural network. We highlight the impact of two key areas of hardware development — increasing memory size of accelerator architectures and device-to-device variation in the emerging devices typically used in in-memory computing — on uncertainty estimation quality. We also consider the challenges that developments in uncertainty estimation methods impose on hardware designs. Finally, we explore the innovations required in terms of hardware, software, and hardware–software co-design in order to build future competency-aware neural networks.

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Fig. 1: Competency awareness of neural networks.
Fig. 2: Trends in memory capacity and memory window.
Fig. 3: Uncertainty-related performance with respect to memory footprint, quantization and device-to-device variation.
Fig. 4: Timeline of developments in uncertainty estimation methods.

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Data availability

The data that support the findings of this study are available from the corresponding author upon request.

Code availability

The code that support the findings of this study are available from the corresponding author upon request.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA

    Yukun Ding, Weiwen Jiang, Qiuwen Lou, Jinglan Liu, Xiaobo Sharon Hu & Yiyu Shi

  2. IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA

    Jinjun Xiong

  3. Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China

    Xiaowei Xu

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Y.D. contributed to all aspects of the project. X.X., and W.J. contributed to data collection and discussion. J.L., Q.L., J.X., and X.H. contributed to discussion and writing. Y.S. contributed to project planning, development, discussion, and writing.

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Ding, Y., Jiang, W., Lou, Q. et al. Hardware design and the competency awareness of a neural network. Nat Electron 3, 514–523 (2020). https://doi.org/10.1038/s41928-020-00476-7

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