面向大模型预训练的智算网络技术研究

王学聪; 冀思伟; 李聪

doi:10.11959/j.issn.1000-0801.2024167

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面向大模型预训练的智算网络技术研究

专栏：面向大模型的网络技术 | 更新时间：2024-08-05

- 面向大模型预训练的智算网络技术研究
- Research on intelligent computing network technology for large-scale pre-trained models
- 电信科学 2024年40卷第6期页码：160-172
- 作者机构：
  
  中国电信股份有限公司研究院，北京 102209
- 作者简介：
  
  [ "王学聪（1989- ），男，中国电信股份有限公司研究院工程师，主要研究方向为人工智能、云计算、智算网络等。" ]
  [ "冀思伟（1996- ），女，中国电信股份有限公司研究院工程师，主要研究方向为云计算、算力网络、智算网络等。" ]
  [ "李聪（1993- ），女，中国电信股份有限公司研究院未来网络研究中心副总监，主要研究方向为未来网络技术、下一代互联网技术、数据中心网络等。" ]
- 基金信息：
  
  国家重点研发计划项目(2023YFB2904100)
- DOI：10.11959/j.issn.1000-0801.2024167
  中图分类号： TP393
- 收稿日期：2024-04-03，
  
  修回日期：2024-06-14，
  
  纸质出版日期：2024-06-20
- 稿件说明：
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王学聪,冀思伟,李聪.面向大模型预训练的智算网络技术研究[J].电信科学,2024,40(06):160-172.

WANG Xuecong,JI Siwei,LI Cong.Research on intelligent computing network technology for large-scale pre-trained models[J].Telecommunications Science,2024,40(06):160-172.
王学聪,冀思伟,李聪.面向大模型预训练的智算网络技术研究[J].电信科学,2024,40(06):160-172. DOI： 10.11959/j.issn.1000-0801.2024167.

WANG Xuecong,JI Siwei,LI Cong.Research on intelligent computing network technology for large-scale pre-trained models[J].Telecommunications Science,2024,40(06):160-172. DOI： 10.11959/j.issn.1000-0801.2024167.

摘要

随着人工智能的发展，大规模预训练模型在自然语言处理和计算机视觉等领域都取得了显著成果，促进了智算中心的建设。针对面向大模型预训练的智算网络关键技术展开研究，系统梳理了智算网络国内外最新的标准化进展，提出了一种面向智算网络的目标架构，探讨了智算网络关键技术的原理，包括远程直接内存访问（RDMA）、IB（InfiniBand）、基于以太网的RDMA（RoCE）、集合通信等，同时也分析了智算网络目前存在的问题以及未来的发展趋势，在推动智算网络技术发展、指导智算中心建设等方面具有重要意义。

Abstract

With the development of artificial intelligence

significant achievements are made in various fields such as natural language processing and computer vision through the utilization of large-scale pre-trained models

which promotes the construction of intelligent computing centers. Key technologies related to large-scale pre-trained models in intelligent computing networks were studied. The latest standardization progress of intelligent computing network at home and abroad was systematically reviewed. A target architecture for intelligent computing network was proposed

and the principles of key technologies

including remote direct memory access (RDMA)

RoCE

and collective communication

were explored. Moreover

the current issues and future development trends of intelligent computing networks were analyzed. This research holds crucial importance in advancing the development of intelligent computing network technology and providing guidance for the establishment of intelligent computing centers.

关键词

Keywords

references

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