Deep Quantization of Graph Neural Networks with Run-Time Hardware-Aware Training
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Springer Nature Switzerland
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https://link.springer.com/content/pdf/10.1007/978-3-031-55673-9_3
Reference17 articles.
1. Chen, Y., Khadem, A., He, X., Talati, N., Khan, T.A., Mudge, T.: PEDAL: a power efficient GCN accelerator with multiple dataflows. In: Proceedings of Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, April 2023. https://doi.org/10.23919/date56975.2023.10137240
2. Courbariaux, M., Bengio, Y., David, J.P.: Training deep neural networks with low precision multiplications (2014). https://doi.org/10.48550/ARXIV.1412.7024
3. Geng, T., et al.: AWB-GCN: a graph convolutional network accelerator with runtime workload rebalancing (2019). https://doi.org/10.48550/ARXIV.1908.10834
4. Grohe, M.: The descriptive complexity of graph neural networks (2023). https://doi.org/10.48550/ARXIV.2303.04613
5. Gupta, S., Agrawal, A., Gopalakrishnan, K., Narayanan, P.: Deep learning with limited numerical precision (2015). https://doi.org/10.48550/ARXIV.1502.02551
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