POSTER: ParGNN: Efficient Training for Large-Scale Graph Neural Network on GPU Clusters-Reference-Cited by-同舟云学术

POSTER: ParGNN: Efficient Training for Large-Scale Graph Neural Network on GPU Clusters

Published:2024-02-20 Issue: Volume: Page:469-471
ISSN:
Container-title:Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming
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Author:

Li Shunde¹²^ORCID,Gu Junyu¹²^ORCID,Wang Jue¹²^ORCID,Yao Tiechui³¹^ORCID,Liang Zhiqiang¹²^ORCID,Shi Yumeng¹²^ORCID,Li Shigang⁴^ORCID,Xi Weiting⁵^ORCID,Li Shushen⁵^ORCID,Zhou Chunbao¹²^ORCID,Wang Yangang¹²^ORCID,Chi Xuebin¹²^ORCID

Affiliation:

1. Computer Network Information Center, Chinese Academy of Sciences, Beijing, China

2. University of Chinese Academy of Sciences, Beijing, China

3. State Grid Smart Grid Research Institute Co., LTD, Beijing, China

4. School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China

5. North China Electric Power University, Beijing, China

Funder

the the National Key Research & Development Program of China

National Natural Science Foundation of China

the Fundamental Research Funds for the Central Universities

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3627535.3638488

Reference9 articles.

1. DGCL

2. AlphaSparse: Generating High Performance SpMV Codes Directly from Sparse Matrices

3. Matthias Fey Jan E. Lenssen Frank Weichert and Jure Leskovec. 2021. GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings. arXiv:2106.05609 [cs.LG]

4. Lingxiao Ma Zhi Yang Youshan Miao Jilong Xue Ming Wu Lidong Zhou and Yafei Dai. 2019. NeuGraph: Parallel Deep Neural Network Computation on Large Graphs. In 2019 USENIX Annual Technical Conference. https://www.microsoft.com/en-us/research/publication/neugraph-parallel-deep-neural-network-computation-on-large-graphs/

5. Hesham Mostafa. 2021. Sequential Aggregation and Rematerialization: Distributed Full-batch Training of Graph Neural Networks on Large Graphs. ArXiv abs/2111.06483 (2021). https://api.semanticscholar.org/CorpusID:244103039