An Overview of the Data-Loader Landscape: Comparative Performance Analysis. (arXiv:2209.13705v1 [cs.DC])

Dataloaders, in charge of moving data from storage into GPUs while training
machine learning models, might hold the key to drastically improving the
performance of training jobs. Recent advances have shown promise not only by
considerably decreasing training time but also by offering new features such as
loading data from remote storage like S3. In this paper, we are the first to
distinguish the dataloader as a separate component in the Deep Learning (DL)
workflow and to outline its structure …

analysis arxiv data landscape overview performance performance analysis