THETA: A High-Efficiency Training Accelerator for DNNs With Triple-Side Sparsity Exploration-Reference-Cited by-同舟云学术

THETA: A High-Efficiency Training Accelerator for DNNs With Triple-Side Sparsity Exploration

Published:2022-08 Issue:8 Volume:30 Page:1034-1046
ISSN:1063-8210
Container-title:IEEE Transactions on Very Large Scale Integration (VLSI) Systems
language:
Short-container-title:IEEE Trans. VLSI Syst.

Author:

Lu Jinming¹^ORCID,Huang Jian¹,Wang Zhongfeng¹^ORCID

Affiliation:

1. School of Electronic Science and Engineering, Nanjing University, Nanjing, China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Key Research Plan of Jiangsu Province of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Software

Link

Reference55 articles.

1. The lottery ticket hypothesis: Finding sparse, trainable neural networks;frankle;Proc 7th Int Conf Learn Represent (ICLR),2019

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