Hardware-friendly compression and hardware acceleration for transformer: A survey

Hardware-friendly compression and hardware acceleration for transformer: A survey

The transformer model has recently been a milestone in artificial intelligence. The algorithm has enhanced the performance of tasks such as Machine Translation and Computer Vision to a level previously unattainable. However, the transformer model has a strong performance but also requires a high amo...

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Bibliographic Details
Main Authors: Shizhen Huang, Enhao Tang, Shun Li, Xiangzhan Ping, Ruiqi Chen
Format: Article
Language:English
Published: AIMS Press 2022-08-01
Series:Electronic Research Archive
Subjects:
transformer
hardware accelerators
self-attention
compression
fpga
Online Access:https://www.aimspress.com/article/doi/10.3934/era.2022192?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/era.2022192?viewType=HTML

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