[D] Optimizing PyTorch Performance and Costs with Cloud Storage Solutions

I've been wrestling with the common issue of feeding my PyTorch ML pipelines directly from cloud storage options like S3 instead of EFS. While it's a convenient setup, the performance hit can be quite discouraging, especially when dealing with large datasets or needing speedy iterations for model training and evaluation.

I stumbled upon [this guide](https://cuno.io/blog/optimizing-pytorch-machine-learning-cost-and-performance-using-cunofs/) that talks about optimizing PyTorch performance while reducing costs.

Would love to hear your thoughts on this or if anyone has tried this in their …

cloud cloud storage cloud storage solutions costs datasets evaluation issue large datasets machinelearning ml pipelines performance pipelines pytorch setup solutions storage training