Research on the Reconstruction of Domestic Computing Power System and Development Path of Guangdong in the Era of Large Models

DOI

10.2991/978-94-6463-958-2_25How to use a DOI?

Keywords

Artificial Intelligence Large Models; Domestic Computing Power; System-level Innovation; Ecosystem Building; Guangdong

Abstract

The rise of large artificial intelligence models has driven a sharp increase in global computing power demand, and the intensification of international technological blockades has urged China to accelerate the construction of its domestic computing power system. This article analyzes the dual drivers of AI large model development and external blockades, providing empirical evidence and case studies to illustrate Guangdong’s domestic computing power initiatives, highlighting the current effectiveness and challenges. In terms of technical paths, domestic computing power is achieving breakthroughs through advanced packaging, system-level collaborative optimization, and ecosystem improvement, forming a diversified system represented by Huawei’s Ascend, Hygon, and Cambricon. Industrial chain analysis shows significant progress in servers, storage, and optical modules, with increasingly mature ecosystems. Comparative studies with other leading regions such as Beijing, Shanghai, and Shenzhen identify best practices that could be applied in Guangdong. Looking ahead, computing power infrastructure will be moderately advanced in construction, with green and low-carbon becoming important indicators, and the domestic computing power ecosystem will accelerate its maturation. Recommendations for Guangdong include strengthening independent innovation and systematic layout of computing power, building national-level innovation and verification platforms, integrating computing power with key industries, and establishing a secure, efficient, and sustainable domestic computing power system.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Huan Wang
AU  - Kai Guo
PY  - 2025
DA  - 2025/12/26
TI  - Research on the Reconstruction of Domestic Computing Power System and Development Path of Guangdong in the Era of Large Models
BT  - Proceedings of the 5th International Conference on Management Science and Software Engineering (ICMSSE 2025)
PB  - Atlantis Press
SP  - 224
EP  - 231
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-958-2_25
DO  - 10.2991/978-94-6463-958-2_25
ID  - Wang2025
ER  -