I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization-Reference-Cited by-同舟云学术

I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization

Published:2021-10-17 Issue: Volume: Page:
ISSN:
Container-title:MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture
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Author:

Geng Tong¹,Wu Chunshu²,Zhang Yongan³,Tan Cheng⁴,Xie Chenhao¹,You Haoran⁵,Herbordt Martin²,Lin Yingyan³,Li Ang⁴

Affiliation:

1. Pacific Northwest National Laboratory

2. Boston University

3. Rice University, United States of America

4. Pacific Northwest National Laboratory, United States of America

5. rice.edu, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3466752.3480113

Reference56 articles.

1. Sergi Abadal Akshay Jain Robert Guirado Jorge López-Alonso and Eduard Alarcón. 2020. Computing Graph Neural Networks: A Survey from Algorithms to Accelerators. arxiv:2010.00130 [cs.LG] Sergi Abadal Akshay Jain Robert Guirado Jorge López-Alonso and Eduard Alarcón. 2020. Computing Graph Neural Networks: A Survey from Algorithms to Accelerators. arxiv:2010.00130 [cs.LG]

2. IEEE International Symposium on Workload Characterization

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