[xiphias2]

I wish Nvidia would put more work into making sure that its stable software packages work together with other stable software. I have a laptop that's more than 1 year old with tensor cores (RTX 2070), but it's still not supported on stable Windows.

I had to install dev channel MS Windows + subsystem for linux 2 + NVidia CUDA 10.2 (an old version of the NVIDIA driver) to be able to run mixed precision training on my NVIDIA card.

I could try to run Linux, but in that case I may not be able to use the newest games that are created for the same NVIDIA card.

The situation is so bad that Jeremy Howard from Fast.AI suggests people to run training models on the cloud even if they put significant amount of money into having their own NVIDIA cards.

[freeone3000]

These are problems of third parties, not Nvidia.

Every game that runs on Linux gets full graphics acceleration.

As for Windows, PyTorch AMP allows for mixed precision training on native windows through conda, no apex needed. And of course, the same APIs from Nvidia are available on both.

[xiphias2]

Thanks, it's great to know that I can use PyTorch AMP for mixed precision training, I was following NVIDIA's documentation, and this wasn't explained.

[beojan]

You could always dual boot.