I’m looking to buy a new GPU. My main use case will be training and running neural nets (tensorflow+pytorch); gaming isn’t really a priority.

Thing is, I use wayland (via sway), and so I’d really prefer to get an AMD GPU. Nvidia doesn’t seem very linux friendly at the moment, especially when it comes to wayland unfortunately.

On the other hand, Nvidia seems to be the clear frontrunner right now when it comes to NN acceleration. I’m worried that if I got an AMD GPU to accelerate my NN work, I’d just be wasting my money.

What do you all think?

Edit: I’ve used GPUs to accelerate NN models in the past, but they weren’t my own, they were provided by my uni’s research infra and/or google collab. So this would be the first time I’d be using my own GPU hardware for this purpose.

  • joba2ca@feddit.de
    1·
    2 years ago

    I was in the same boat as you, i.e. using the GPU during my studies. My premise is to optimise the most frequent use case, i.e., deep learning.

    IMO going with NVIDIA will save you so much worries and frustration that it clearly outweighs the downsides of worse Wayland support compared with AMD.

    When you have tough university assignments/projects, you want to focus on the actual problem instead of debugging/compiling libraries for use with AMD. I am sure that with a bit of work many libraries can be made to work with AMD, but apparently it is still a pain oftentimes.

    So I strongly suggest choosing NVIDIA. Disclaimer: have not used AMD for deep learning yet, but have monitored the development of AMD support, because I would like to switch to AMD.

    Btw. I found Pop!OS to be very nice for both “regular” university work and all computer science tasks.