Optimizing Direct Convolutions on ARM Multi-Cores-Reference-Cited by-同舟云学术

Optimizing Direct Convolutions on ARM Multi-Cores

Published:2023-11-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
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Author:

Wang Pengyu¹^ORCID,Yang Weiling¹^ORCID,Fang Jianbin¹^ORCID,Dong Dezun¹^ORCID,Huang Chun¹^ORCID,Zhang Peng¹^ORCID,Tang Tao¹^ORCID,Wang Zheng²^ORCID

Affiliation:

1. College of Computer Science and Technology, National University of Defense Technology, Changsha, China

2. School of Computing, University of Leeds, Leeds, United Kingdom

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581784.3607107

Reference72 articles.

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2. Armv9. https://www.arm.com/company/news/2021/03/arms-answer-to-the-future-of-ai-armv9-architecture. Armv9. https://www.arm.com/company/news/2021/03/arms-answer-to-the-future-of-ai-armv9-architecture.

3. cublas. https://developer.nvidia.com/cublas. cublas. https://developer.nvidia.com/cublas.

4. Kunpeng-920. https://www.hisilicon.com/cn/products/Kunpeng/Huawei-Kunpeng/Huawei-Kunpeng-920. Kunpeng-920. https://www.hisilicon.com/cn/products/Kunpeng/Huawei-Kunpeng/Huawei-Kunpeng-920.

5. Libxsmm. https://github.com/libxsmm/libxsmm. Libxsmm. https://github.com/libxsmm/libxsmm.

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