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Accelerating Large Scale Real-Time GNN Inference using Channel Pruning


May 10, 2021
Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor Prasanna


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Deep Graph Neural Networks with Shallow Subgraph Samplers


Dec 02, 2020
Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Rajgopal Kannan, Viktor Prasanna, Long Jin, Andrey Malevich, Ren Chen

* 21 pages 

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Accurate, Efficient and Scalable Training of Graph Neural Networks


Oct 05, 2020
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor Prasanna

* Journal of Parallel and Distributed Computing, Volume 147, January 2021, Pages 166-183 
* 43 pages, 8 figures. arXiv admin note: text overlap with arXiv:1810.11899 

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GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms


Dec 31, 2019
Hanqing Zeng, Viktor Prasanna

* Published in ACM/SIGDA FPGA '20 

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SPEC2: SPECtral SParsE CNN Accelerator on FPGAs


Oct 16, 2019
Yue Niu, Hanqing Zeng, Ajitesh Srivastava, Kartik Lakhotia, Rajgopal Kannan, Yanzhi Wang, Viktor Prasanna

* This is a 10-page conference paper in 26TH IEEE International Conference On High Performance Computing, Data, and Analytics (HiPC) 

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GraphSAINT: Graph Sampling Based Inductive Learning Method


Jul 10, 2019
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor Prasanna

* 16 pages 

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Accurate, Efficient and Scalable Graph Embedding


Oct 30, 2018
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor Prasanna

* 10 pages 

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