I am reasonably knowledgeable with Caffe and pretty strong with Python and C++, but a fair newbie to PyTorch. I have questions about performance - and expected performance - of different hardware while training networks like ResNet34 using PyTorch. Is there a forum where the focus is on hardware for PyTorch and tuning for hardware, rather than programming with PyTorch per se?
Example: running github.com/pytorch/examples/tree/main/imagenet I get similar performance with an old Radeon Pro VII as an Nvidia L4, and an Nvidia A100 is only about 80% faster than either. But I think this is not the best place to be asking?
To your question about performance of different devices: profile your workload to isolate where the bottleneck if your code is. E.g. if all use cases are CPU-limited, a better GPU will hardly improve the end2end performance.
LOL, I am sitting here trying to type an explanation that I tried permutations of PyTorch parameters, hardware, etc, and, and, and… and I just cannot seem to cause a change in the per-epoch training time except a weak scaling across GPU generations. Which is to say I have a… a… a bottleneck! So, you are very wise! Thankyou for the advice. I will get out a profiler.
Hello sir I need help for my code.The torch doesnt work on my computer I dont know wht?? What can it be the problem I triesd to look on the dependency walker and it said torch is missing some dll files.How can I fix that??The error
