Accelerating attention through gradient-based learned runtime pruning-Reference-Cited by-同舟云学术

Accelerating attention through gradient-based learned runtime pruning

Published:2022-06-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 49th Annual International Symposium on Computer Architecture
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Author:

Li Zheng¹,Ghodrati Soroush¹,Yazdanbakhsh Amir²,Esmaeilzadeh Hadi¹,Kang Mingu¹

Affiliation:

1. University of California

2. Google Research

Funder

National Science Foundation

Semiconductor Research Corporation (SRC)

Defense Advanced Research Project Agency (DARPA)

National Institute of Health

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3470496.3527423

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4. Vahide Aklaghi , Amir Yazdanbakhsh , Kambiz Samadi , Hadi Esmaeilzadeh , and Rajesh K . Gupta . 2018 . SnaPEA: Predictive Early Activation for Reducing Computation in Deep Convolutional Neural Networks. In ISCA. Vahide Aklaghi, Amir Yazdanbakhsh, Kambiz Samadi, Hadi Esmaeilzadeh, and Rajesh K. Gupta. 2018. SnaPEA: Predictive Early Activation for Reducing Computation in Deep Convolutional Neural Networks. In ISCA.

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