Handling large 3d image dataset with DataLoader

[ptrblck]

@Siddharth_Tandon

I am facing some issue with GPU utilization:
Problem is, nvidia-sme command is showing only 1 process (whereas I have specified 4 workers in dataloader) running, with GPU memory usage as 4GB. Secondly there is no GPU utilization at all.

The num_workers specified in the DataLoader are executed on the CPU using multiprocessing and will not be shown on nvidia-smi.
The GPU utilization might be low, if you are facing bottlenecks in your code, such as data loading.
Take a look at this post, which explains it well and suggests some performance improvements.

@Siddharth_Tandon

I was reading an article which says that if DataLoader is slow, model will run on CPU.

This is not correct. The model will use the specified device and PyTorch will not automatically use the CPU based on the performance of the DataLoader.