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Cross-layer efforts for energy-efficient computing: towards peta operations per second per watt

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Abstract

As Moore’s law based device scaling and accompanying performance scaling trends are slowing down, there is increasing interest in new technologies and computational models for fast and more energy-efficient information processing. Meanwhile, there is growing evidence that, with respect to traditional Boolean circuits and von Neumann processors, it will be challenging for beyond-CMOS devices to compete with the CMOS technology. Exploiting unique characteristics of emerging devices, especially in the context of alternative circuit and architectural paradigms, has the potential to offer orders of magnitude improvement in terms of power, performance, and capability. To take full advantage of beyond-CMOS devices, cross-layer efforts spanning from devices to circuits to architectures to algorithms are indispensable. This study examines energy-efficient neural network accelerators for embedded applications in this context. Several deep neural network accelerator designs based on cross-layer efforts spanning from alternative device technologies, circuit styles, to architectures are highlighted. Application-level benchmarking studies are presented. The discussions demonstrate that cross-layer efforts indeed can lead to orders of magnitude gain towards achieving extreme-scale energy-efficient processing.

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Acknowledgements

The authors would like to thank Mr. Qiu-wen LOU and Dr. Robert PERRICONE who have contributed several graphs and experimental data used in this study.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA

    Xiaobo Sharon Hu & Michael Niemier

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  1. Xiaobo Sharon Hu
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  2. Michael Niemier
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Correspondence to Xiaobo Sharon Hu.

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Project supported by the Center for Low Energy Systems Technology (LEAST), one of the six centers of STARnet, a Semiconductor Research Corporation Program sponsored by MARCO and DARPA

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Hu, X.S., Niemier, M. Cross-layer efforts for energy-efficient computing: towards peta operations per second per watt. Frontiers Inf Technol Electronic Eng 19, 1209–1223 (2018). https://doi.org/10.1631/FITEE.1800466

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  • DOI: https://doi.org/10.1631/FITEE.1800466

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