Data-Aware Storage Tiering for Deep Learning

DNN models trained with very large datasets can perform rich deep learning tasks with high accuracy. However, feeding huge volumes of training data exerts significant pressure on IO subsystems as the entire data is re-loaded in random order on every iteration to enable convergence, with very little scope for reuse. To address this challenge, we co-optimize data tiering and iteration in DNN trainin...