Accelerating Graph Convolutional Networks Using Crossbar-based Processing-In-Memory Architectures-Reference-Cited by-同舟云学术

Accelerating Graph Convolutional Networks Using Crossbar-based Processing-In-Memory Architectures

Published:2022-04 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA)
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Author:

Huang Yu¹,Zheng Long¹,Yao Pengcheng¹,Wang Qinggang¹,Liao Xiaofei¹,Jin Hai¹,Xue Jingling²

Affiliation:

1. Huazhong University of Science and Technology,National Engineering Research Center for Big Data Technology and System, Service Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology,China

2. UNSW Sydney,Australia

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9773179/9773180/09773267.pdf?arnumber=9773267

Reference55 articles.

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4. Timely: Pushing Data Movements And Interfaces In Pim Accelerators Towards Local And In Time Domain

5. GCNAX: A Flexible and Energy-efficient Accelerator for Graph Convolutional Neural Networks

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