Exploring Attention Sparsity to Accelerate Transformer Training on GPUs
The computational complexity required for training a Transformer model quadratically increases as the length of the input sequence increases. Therefore, to accelerate the training of a large-scale Transformer with long sequences, it is crucial to reduce the number of operations for the multi-head at...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10589623/ |
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