The document discusses distributed deep learning using Hopsworks. It describes how Hopsworks can be used for distributed training, hyperparameter optimization, and model serving. Hopsworks provides a feature store, distributed file system, and workflows for building scalable machine learning pipelines. It supports frameworks like TensorFlow, PyTorch, and Spark for distributed deep learning tasks like data parallel training using collective all-reduce strategies.