MG-GCN: A Scalable multi-GPU GCN Training Framework-Reference-Cited by-同舟云学术

MG-GCN: A Scalable multi-GPU GCN Training Framework

Published:2022-08-29 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 51st International Conference on Parallel Processing
language:
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Author:

Balin Muhammed Fatih¹,Sancak Kaan¹,Catalyurek Umit V.²

Affiliation:

1. Computational Science and Engineering, Georgia Institute of Technology, United States of America

2. Computational Science and Engineering, Georgia Institute of Technology, United States of America and Amazon Web Services, United States of America

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3545008.3545082

Reference46 articles.

1. Martín Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen 2015. TensorFlow Large-scale machine learning on heterogeneous systems. Martín Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen 2015. TensorFlow Large-scale machine learning on heterogeneous systems.

2. Demystifying Parallel and Distributed Deep Learning

3. DGCL

4. Jie Chen , Tengfei Ma , and Cao Xiao . 2018 . FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling . In International Conference on Learning Representations. Jie Chen, Tengfei Ma, and Cao Xiao. 2018. FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. In International Conference on Learning Representations.

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