Distributed deep learning has emerged as an essential approach for training large-scale deep neural networks by utilising multiple computational nodes. This methodology partitions the workload either ...

In the context of deep learning model training, checkpoint-based error recovery techniques are a simple and effective form of fault tolerance. By regularly saving the ...