A Reconfigurable Spatial Architecture for Energy-Efficient Inception Neural Networks-Reference-Cited by-同舟云学术

A Reconfigurable Spatial Architecture for Energy-Efficient Inception Neural Networks

Published:2023-03 Issue:1 Volume:13 Page:7-20
ISSN:2156-3357
Container-title:IEEE Journal on Emerging and Selected Topics in Circuits and Systems
language:
Short-container-title:IEEE J. Emerg. Sel. Topics Circuits Syst.

Author:

Luo Lichuan¹^ORCID,Kang Wang²^ORCID,Liu Junzhan²,Zhang He²^ORCID,Zhang Youguang¹,Liu Dijun¹,Ouyang Peng³

Affiliation:

1. School of Electronic and Information Engineering, Beihang University, Beijing, China

2. School of Integrated Circuit Science and Engineering, Fert Beijing Institute, Beihang University, Beijing, China

3. Tsingmicro Intelligent Technology Company Ltd., Beijing, China

Funder

Beijing Municipal Science and Technology Commission (MSTC) Nova Program

Beijing Natural Science Foundation

Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

Reference53 articles.

1. Computing’s energy problem (and what we can do about it);horowitz;IEEE Int Solid-State Circuits Conf (ISSCC) Dig Tech Papers,2014

4. Power, programmability, and granularity: The challenges of ExaScale computing;dally;Proc IEEE Int Test Conf,2011

5. BRECQ: Pushing the limit of post-training quantization by block reconstruction;li;arXiv 2102 05426,2021

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