Research on Key Technologies for Cross-Cloud Federated Training of Large Language Models

Understand

With the rapid development of natural language processing technology, large language models have demonstrated exceptional performance in various application scenarios.

• However, training these models requires significant computational resources and data processing capabilities.
• Cross-cloud federated training offers a new approach to addressing the resource bottlenecks of a single cloud platform, allowing the computational resources of multiple clouds to collaboratively complete the training tasks of large models.
• This study analyzes the key technologies of cross-cloud federated training, including data partitioning and distribution, communication optimization, model aggregation algorithms, and the compatibility of heterogeneous cloud platforms.