Adaptive Distributed Training Framework for Mitigating Leader and Straggler Nodes

The AntDT framework provides a unified and self-adaptive approach to efficiently address various types of stragglers in distributed deep learning training, including deterministic, transient, and persistent stragglers, while ensuring data integrity and scalability.