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Memristor-based approximated computation

Publication ,  Conference
Li, B; Shan, Y; Hu, M; Wang, Y; Chen, Y; Yang, H
Published in: Proceedings of the International Symposium on Low Power Electronics and Design
December 11, 2013

The cessation of Moore's Law has limited further improvements in power efficiency. In recent years, the physical realization of the memristor has demonstrated a promising solution to ultra-integrated hardware realization of neural networks, which can be leveraged for better performance and power efficiency gains. In this work, we introduce a power efficient framework for approximated computations by taking advantage of the memristor-based multilayer neural networks. A programmable memristor approximated computation unit (Memristor ACU) is introduced first to accelerate approximated computation and a memristor-based approximated computation framework with scalability is proposed on top of the Memristor ACU. We also introduce a parameter configuration algorithm of the Memristor ACU and a feedback state tuning circuit to program the Memristor ACU effectively. Our simulation results show that the maximum error of the Memristor ACU for 6 common complex functions is only 1.87% while the state tuning circuit can achieve 12-bit precision. The implementation of HMAX model atop our proposed memristor-based approximated computation framework demonstrates 22× power efficiency improvements than its pure digital implementation counterpart. © 2013 IEEE.

Duke Scholars

Published In

Proceedings of the International Symposium on Low Power Electronics and Design

DOI

ISSN

1533-4678

ISBN

9781479912353

Publication Date

December 11, 2013

Start / End Page

242 / 247
 

Citation

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Li, B., Shan, Y., Hu, M., Wang, Y., Chen, Y., & Yang, H. (2013). Memristor-based approximated computation. In Proceedings of the International Symposium on Low Power Electronics and Design (pp. 242–247). https://doi.org/10.1109/ISLPED.2013.6629302
Li, B., Y. Shan, M. Hu, Y. Wang, Y. Chen, and H. Yang. “Memristor-based approximated computation.” In Proceedings of the International Symposium on Low Power Electronics and Design, 242–47, 2013. https://doi.org/10.1109/ISLPED.2013.6629302.
Li B, Shan Y, Hu M, Wang Y, Chen Y, Yang H. Memristor-based approximated computation. In: Proceedings of the International Symposium on Low Power Electronics and Design. 2013. p. 242–7.
Li, B., et al. “Memristor-based approximated computation.” Proceedings of the International Symposium on Low Power Electronics and Design, 2013, pp. 242–47. Scopus, doi:10.1109/ISLPED.2013.6629302.
Li B, Shan Y, Hu M, Wang Y, Chen Y, Yang H. Memristor-based approximated computation. Proceedings of the International Symposium on Low Power Electronics and Design. 2013. p. 242–247.

Published In

Proceedings of the International Symposium on Low Power Electronics and Design

DOI

ISSN

1533-4678

ISBN

9781479912353

Publication Date

December 11, 2013

Start / End Page

242 / 247