GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding-Reference-Cited by-同舟云学术

GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:The World Wide Web Conference on - WWW '19
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Author:

Zhu Zhaocheng¹,Xu Shizhen²,Tang Jian³,Qu Meng¹

Affiliation:

1. Montr??al Institute for Learning Algorithms, Canada

2. Tsinghua University, China

3. HEC Montr??al / Montr??al Institute for Learning Algorithms, Canada

Publisher

ACM Press

Reference40 articles.

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2. Natural Language Processing Lab at Tsinghua University. 2017. OpenNE: An open source toolkit for Network Embedding. https://github.com/thunlp/OpenNE.

3. Prasad G Bhavana and Vineet C Nair. 2019. BMF: Block matrix approach to factorization of large scale data. arXiv preprint arXiv:1901.00444(2019).

4. Shaosheng Cao, Wei Lu, and Qiongkai Xu. 2015. Grarep: Learning graph representations with global structural information. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management. ACM, 891-900.

5. Dan C Ciresan, Ueli Meier, Jonathan Masci, Luca Maria Gambardella, and Jürgen Schmidhuber. 2011. Flexible, high performance convolutional neural networks for image classification. In IJCAI Proceedings-International Joint Conference on Artificial Intelligence, Vol. 22. Barcelona, Spain, 1237.

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