Even_Oldridge:

s not really worth doing from what I can see. I’m relatively new to multiprocessing so there’s a good chance I’m doing something wrong, and it may just make sense to stick to CPU dataloading to keep the GPU memory available for the model, but I’d love to figure out a more robust solution, particularly in light of in GPU prepro


It doesn’t seem to me that the data will be pre-loaded to the GPU. Also if the next operation depends on the data this doesn’t really gain any performance. Also if we’re moving data back to the CPU the data-loading isn’t overlapped. Is there any way to pre-load the data in the main CUDA context?