A 21mW low-power recurrent neural network accelerator with quantization tables for embedded deep learning applications

Jinmook Lee, Dongjoo Shin, Hoi-Jun Yoo. A 21mW low-power recurrent neural network accelerator with quantization tables for embedded deep learning applications. In IEEE Asian Solid-State Circuits Conference, A-SSCC 2017, Seoul, Korea (South), November 6-8, 2017. pages 237-240, IEEE, 2017. [doi]

Abstract

Abstract is missing.