E-ERA: An energy-efficient reconfigurable architecture for RNNs using dynamically adaptive approximate computing-Reference-Cited by-同舟云学术

E-ERA: An energy-efficient reconfigurable architecture for RNNs using dynamically adaptive approximate computing

Author:

Liu Bo¹,Dong Wei¹,Xu Tingting¹,Gong Yu¹,Ge Wei¹,Yang Jinjiang¹,Shi Longxing¹

Affiliation:

1. National ASIC System Engineering Technology Research Center, Southeast University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Electronic, Optical and Magnetic Materials

Link

Reference19 articles.

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5. [5] A. X. M. Chang, et al.: “Recurrent neural networks hardware implementation on FPGA,” arXiv preprint (2015) (arXiv:1511.05552).

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