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Graph Neural Networks (GNNs) have been widely used in various domains, and GNNs with sophisticated computational graph lead to higher latency and larger memory consumption.
Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems
Wang, H., Zhang, F., Zhang, M., Leskovec, J., Zhao, M., Li, W., and Wang, Z · 1905
Earlier work this paper cites.
3d shapenets: A deep representation for volumetric shapes
Wu, Z., Song, S., Khosla, A., Yu, F., Zhang, L., Tang, X., and Xiao, J · 2015
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Rabbit order: Just-in-time parallel reordering for fast graph analysis
Arai, J., Shiokawa, H., Yamamuro, T., Onizuka, M., and Iwamura, S · 2016
Earlier work this paper cites.
Training deep nets with sublinear memory cost, 2016
Chen, T., Xu, B., Zhang, C., and Guestrin, C · 2016
Earlier work this paper cites.
Semi-supervised Classification with Graph Convolutional Networks
Kipf, T. N. and Welling, M · 2016
Earlier work this paper cites.
Geometric deep learning on graphs and manifolds using mixture model cnns
Monti, F., Boscaini, D., Masci, J., Rodolà, E., Svoboda, J., and Bronstein, M. M · 2016
Earlier work this paper cites.
Inductive Representation Learning on Large Graphs
Hamilton, W. L., Ying, R., and Leskovec, J · 2017
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Veličković, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., and Bengio, Y · 2017
Earlier work this paper cites.
Graph Convolutional Networks With Argument-Aware Pooling for Event Detection
Nguyen, T. and Grishman, R · 2018
Cited alongside, same era.
Learning Human-Object Interactions by Graph Parsing Neural Networks
Qi, S., Wang, W., Jia, B., Shen, J., and Zhu, S.-C · 2018
Cited alongside, same era.
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
Yan, S., Xiong, Y., and Lin, D · 2018
Cited alongside, same era.
Graph Convolutional Networks for Text Classification
Yao, L., Mao, C., and Luo, Y · 2018
Cited alongside, same era.
Graph Convolutional Neural Networks for Web-scale Recommender Systems
Ying, R., He, R., Chen, K., Eksombatchai, P., Hamilton, W. L., and Leskovec, J · 2018
Neugraph: Parallel deep neural network computation on large graphs
Ma, L., Yang, Z., Miao, Y., Xue, J., Wu, M., Zhou, L., and Dai, Y · 2019
Later among the works it cites.
fuseGNN: Accelerating Graph Convolutional Neural Network Training on GPGPU
Chen, Z., Yan, M., Zhu, M., Deng, L., Li, G., Li, S., and Xie, Y · 2020
Later among the works it cites.
Ge-spmm: General-purpose sparse matrix-matrix multiplication on gpus for graph neural networks
Huang, G., Dai, G., Wang, Y., and Yang, H · 2020
Later among the works it cites.
Hygcn: A gcn accelerator with hybrid architecture
Yan, M., Deng, L., Hu, X., Liang, L., Feng, Y., Ye, X., Zhang, Z., Fan, D., and Xie, Y · 2020
Later among the works it cites.
Understanding and Bridging the Gaps in Current GNN Performance Optimizations
Huang, K., Zhai, J., Zheng, Z., Yi, Y., and Shen, X · 2021
Closest in time.
DNNFusion: Accelerating Deep Neural Networks Execution with Advanced Operator Fusion
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Cited alongside, same era.
Fast graph representation learning with pytorch geometric
Fey, M. and Lenssen, J. E · 2019
Cited alongside, same era.
Taso: Optimizing deep learning computation with automatic generation of graph substitutions
Jia, Z., Padon, O., Thomas, J., Warszawski, T., Zaharia, M., and Aiken, A · 2019
Cited alongside, same era.
Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs
Wang, M., Yu, L., Zheng, D., Gan, Q., Gai, Y., Ye, Z., Li, M., Zhou, J., Huang, Q., Ma, C., et al
Cited in the paper.
Dynamic graph cnn for learning on point clouds
Wang, Y., Sun, Y., Liu, Z., Sarma, S. E., Bronstein, M. M., and Solomon, J. M
Cited in the paper.
Niu, W., Guan, J., Wang, Y., Agrawal, G., and Ren, B · 2021
Closest in time.
Gnnadvisor: An adaptive and efficient runtime system for GNN acceleration on gpus
Wang, Y., Feng, B., Li, G., Li, S., Deng, L., Xie, Y., and Ding, Y · 2021
Closest in time.