Research on the development of intelligent computing network for large models - GUO Liang; WANG Shaopeng; QUAN Wei; LI Jie (Dianxin kexue, 2024)
In recent years, the world has entered a period of vigorous development in intelligent computing. As deep learning models with huge parameters and complex structures, large model training requires fast synchronization of training parameters between multiple cards and servers, which imposes higher requirements on the bandwidth, latency, reliability, scalability and security of datacenter networks. The requirements and related key technologies of intelligent computing networks for large model training were studied, and the standard specifications, academic research, and case practices of intelligent computing networks were analyzed, in order to promote the development of intelligent computing networks.