POSTER: Adaptive Load Balancing with Flow Block for LLM-Reference-Cited by-同舟云学术

POSTER: Adaptive Load Balancing with Flow Block for LLM

Published:2024-08-04 Issue: Volume:21 Page:69-71
ISSN:
Container-title:Proceedings of the ACM SIGCOMM 2024 Conference: Posters and Demos
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Author:

Li Xingyi¹^ORCID,Zhang Yiran¹²³^ORCID,Zhang Hu³⁴^ORCID,Wang Shangguang¹^ORCID

Affiliation:

1. Beijing University of Posts and Telecommunications, Beijing, China

2. State Key Laboratory of Networking and Switching Technology, Beijing, China

3. Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China

4. Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan, China

Funder

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3672202.3673747

Reference8 articles.

1. Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018).

2. Yuliang Li, Rui Miao, Hongqiang Harry Liu, Yan Zhuang, Fei Feng, Lingbo Tang, Zheng Cao, Ming Zhang, Frank Kelly, Mohammad Alizadeh, et al. 2019. HPCC: High precision congestion control. In Proceedings of the ACM Special Interest Group on Data Communication. 44--58.

3. The power of two choices in randomized load balancing

4. Exploring the limits of transfer learning with a unified text-to-text transformer;Raffel Colin;Journal of machine learning research,2020

5. Shan Sinha, Srikanth Kandula, and Dina Katabi. 2004. Harnessing TCP's burstiness with flowlet switching. In Proc. 3rd ACM Workshop on Hot Topics in Networks (Hotnets-III). Citeseer.