Overview and Trend of Large-scale Model Deployment Mode

Currently, large-scale model have transitioned from a period of algorithm research to a period of industry application. This paper presents a comprehensive review of large-scale model deployment modes. It provides an overview of the various deployment mode, their advantages and disadvantages. We del...

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Bibliographic Details
Published in2024 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) pp. 1 - 6
Main Authors Zheng, Qiuhong, Wang, Jinghan, Shen, Yun
Format Conference Proceeding
LanguageEnglish
Published IEEE 19.06.2024
Subjects
Analytical models
Broadcasting
Computational modeling
computing power
deployment
Edge AI
Industry applications
infrastructure
large-scale model
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Summary:Currently, large-scale model have transitioned from a period of algorithm research to a period of industry application. This paper presents a comprehensive review of large-scale model deployment modes. It provides an overview of the various deployment mode, their advantages and disadvantages. We delve into the critical factors that must be taken into account when selecting a deployment mode for large-scale model. We present the various deployment modes available for large-scale models, including centralized deployment, distributed deployment, and edge computing deployment. We particularly focus on edge computing deployment mode and analyze evolving trends in large-scale model deployment. We specially conducted an analysis on converged infrastructure and edge AI of large-scale model. Furthermore, we provide insights into the main challenges and future research directions in this field.
ISSN:2155-5052
DOI:10.1109/BMSB62888.2024.10608242