TT-GNN: Efficient On-Chip Graph Neural Network Training via Embedding Reformation and Hardware Optimization
Author:
Affiliation:
1. Unversity of California, Santa Barbara, United States
2. Alibaba Group Inc., USA
3. Alibaba Group Inc., United States
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3613424.3614305
Reference50 articles.
1. Efficient Data Loader for Fast Sampling-Based GNN Training on Large Graphs
2. ReGNN: A Redundancy-Eliminated Graph Neural Networks Accelerator
3. Cluster-GCN
4. Cluster-GCN
5. Matthieu Courbariaux and Yoshua Bengio . 2016. BinaryNet: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1. CoRR abs/1602.02830 ( 2016 ). arXiv:1602.02830http://arxiv.org/abs/1602.02830 Matthieu Courbariaux and Yoshua Bengio. 2016. BinaryNet: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1. CoRR abs/1602.02830 (2016). arXiv:1602.02830http://arxiv.org/abs/1602.02830
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