A Silicon Photonic Accelerator for Convolutional Neural Networks with Heterogeneous Quantization-Reference-Cited by-同舟云学术

A Silicon Photonic Accelerator for Convolutional Neural Networks with Heterogeneous Quantization

Published:2022-06-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Great Lakes Symposium on VLSI 2022
language:
Short-container-title:

Author:

Sunny Febin¹,Nikdast Mahdi¹,Pasricha Sudeep¹

Affiliation:

1. Colorado State University, Fort Collins, CO, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3526241.3530364

Reference26 articles.

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2. B. Wu , " Mixed Precision Quantization of Convnets via Differentiable Neural Architecture Search," arXiv:1812.00090v1 , 2018 . B. Wu et al., "Mixed Precision Quantization of Convnets via Differentiable Neural Architecture Search," arXiv:1812.00090v1, 2018.

3. M. Nikolic , " BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization," arXiv:2002.03090v2 , 2020 . M. Nikolic et al., "BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization," arXiv:2002.03090v2, 2020.

4. "Apple describes 7nm a12 bionic chips " EENews 2018. "Apple describes 7nm a12 bionic chips " EENews 2018.

5. F. Sunny , A. Mirza , I. Thakkar , S. Pasricha , and M. Nikdast , " LORAX: Loss-aware approximations for energy-efficient silicon photonic networks-on-chip," ACM GLSVLSI , 2020 . F. Sunny, A. Mirza, I. Thakkar, S. Pasricha, and M. Nikdast, "LORAX: Loss-aware approximations for energy-efficient silicon photonic networks-on-chip," ACM GLSVLSI, 2020.

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