Challenges and development trends of collective communication libraries in intelligent computing scenarios

With the development of artificial intelligence (AI) large models progresses, the demand for computing resources in distributed training has increased significantly. This leads to a substantial increase in the amount of data communicated between clusters,which poses severe challenges to collective communication libraries in intelligent computing scenarios.. Focusing on the performance bottlenecks and business requirements of computing tasks in intelligent computing scenarios, the technical difficulties faced by current collective communication libraries were analyzed. At the same time, the future development trends of these libraries were also envisioned, such as developing more efficient communication algorithms, implementing more flexible scheduling mechanisms, and enhancing cross-platform compatibility, with the aim to provide valuable references and support for research and practical applications in the field of intelligent computing.