Parallelizing Neural Network Models Effectively on GPU by Implementing Reductions Atomically-Reference-Cited by-同舟云学术

Parallelizing Neural Network Models Effectively on GPU by Implementing Reductions Atomically

Published:2022-10-08 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the International Conference on Parallel Architectures and Compilation Techniques
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Author:

Zhao Jie¹^ORCID,Bastoul Cédric²^ORCID,Yi Yanzhi³^ORCID,Hu Jiahui³^ORCID,Nie Wang³^ORCID,Zhang Renwei³^ORCID,Geng Zhen⁴^ORCID,Li Chong²^ORCID,Tachon Thibaut²^ORCID,Gan Zhiliang⁵^ORCID

Affiliation:

1. State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, China

2. Huawei Technologies France SASU, Paris, France

3. Huawei Technologies Co., Ltd., Beijing, China

4. Huawei Technologies Co., Ltd., Hangzhou, China

5. Huawei Technologies Co., Ltd., Shenzhen, China

Funder

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3559009.3569656

Reference64 articles.

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