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For example, the figure above presents the processing time of a single mini-batch of 32 samples. SRU achieves 10 to 16 times speed-up compared to LSTM, and operates as fast as (or faster than) word-level convolution using conv2d.
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### Reference:
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#### Reference:
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[Training RNNs as Fast as CNNs](https://arxiv.org/abs/1709.02755)
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```
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@article{lei2017sru,
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year={2017}
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}
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```
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<br>
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## Requirements
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- **GPU and CUDA are required**

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