Loading data onto GPUs for training has historically been a minor issue for most deep learning practitioners. Data read from a local spinning hard drive or NAS device would be preprocessed on the CPU, then shipped to the GPU for training. The data input pipeline rarely proved to be the bottleneck given the long number-crunching times involved. As GPUs improve and DL frameworks use them more��
]]>