Poster: A Fast, Scalable, and Energy-efficient Edge Acceleration Architecture based on GPU Cluster-Reference-Cited by-同舟云学术

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Poster: A Fast, Scalable, and Energy-efficient Edge Acceleration Architecture based on GPU Cluster

Published:2023-12-05 Issue: Volume: Page:
ISSN:
Container-title:Companion of the 19th International Conference on emerging Networking EXperiments and Technologies
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Author:

Wang Yanwei¹^ORCID,Su Dongdong²^ORCID,Zhao Qianqian¹^ORCID,Xiao Linge¹^ORCID,Shen Yanmei¹^ORCID,Zhu Kefeng³^ORCID

Affiliation:

1. Inspur Electronic Information Industry Co., Ltd, Jinan, China

2. Inspur Electronic Information Industry Co., Ltd & Guangdong Inspur Intelligent Computing Technology Co., Ltd, Jinan, China

3. Guangdong Inspur Intelligent Computing Technology Co., Ltd, Guangzhou, China

Funder

This work is supported by Key-Area Research and Development Program of Guangdong Province Grants

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3624354.3630083

Reference3 articles.

1. Exploiting Hardware Multicast and GPUDirect RDMA for Efficient Broadcast

2. Vortex: Extending the RISC-V ISA for GPGPU and 3D-Graphics

3. Hong Zhang , Yupeng Tang , Anurag Khandelwal , and Ion Stoica . 2023 . SHEPHERD: Serving DNNs in the Wild. In 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23) . USENIX Association, Boston, MA, 787--808. https://www.usenix.org/conference/nsdi23/presentation/zhang-hong Hong Zhang, Yupeng Tang, Anurag Khandelwal, and Ion Stoica. 2023. SHEPHERD: Serving DNNs in the Wild. In 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23). USENIX Association, Boston, MA, 787--808. https://www.usenix.org/conference/nsdi23/presentation/zhang-hong

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