3 ms·

I was aware that AMD had officially supported open source linux drivers, and that Nvidia did not support Wayland. Unfortunately, I needed a machine which would

by suby 5y ago

I was aware that AMD had officially supported open source linux drivers, and that Nvidia did not support Wayland. Unfortunately, I needed a machine which would work well with the existing machine learning ecosystem, and that means getting an nvidia card over AMD. It's pretty terrible that the machine learning ecosystem is centered around nvidia hardware.

phkahler 5y ago
Yeah, 15 years ago it was nvidia for Linux because they were the only ones with functioning graphics drivers even if they were closed source. Now it's similar for ML on Linux even though for regular graphics the situation has reversed. I suppose many new areas start out with proprietary solutions and become more open and standardized over time?
Steltek 5y ago
Has anyone tried using an AMD card for desktop/Wayland alongside an Nvidia card for ML/CUDA? Especially with Sway? I use Sway/AMD for desktop but all the photogrammetry software out there requires CUDA. It's a bit of a PITA.
- Mehdi2277 5y ago
  It can work but generally you either have performance issues or less library support or run into more operational pains. I mainly work on building library tooling over tensorflow. Losing support for good number of operations is not something that I could reasonably consider. Also cloud amd gpu support is near non-existent and most of my company's compute relies on the cloud. t4 pricing is very nice on gcp. Like AMD rocm exists for ml, but is very far behind cuda in support/libraries for ml. I don't think any moderate investment in AMD gpus is likely to catch up, so I'm pretty pessimistic of AMD being a good solution for ML usage anytime in the next several years. I think a hobbyist who already owns an AMD card and wants to do basic ML is only situation I'd consider it. Any other situation and I'd strongly advise against it.
  - Steltek 5y ago
    Sorry, I think you misunderstood. This is installing both types of card in the same computer: one for desktop/Wayland (AMD), and the other for ML/CUDA (Nvidia).
my123 5y ago
> and that Nvidia did not support Wayland Nvidia does support Wayland. For KDE, the issue is: https://invent.kde.org/qt/qt/qtwayland/-/merge_requests/24 https://invent.kde.org/qt/qt/qtwayland/-/merge_requests/24 You'll have to wait until that gets to your distribution to have a usable KDE experience with NVIDIA on Wayland. In general, if you use those GPUs, please use the latest distributions.

by suby 5y ago

phkahler 5y ago

Yeah, 15 years ago it was nvidia for Linux because they were the only ones with functioning graphics drivers even if they were closed source. Now it's similar for ML on Linux even though for regular graphics the situation has reversed. I suppose many new areas start out with proprietary solutions and become more open and standardized over time?

Steltek 5y ago

Has anyone tried using an AMD card for desktop/Wayland alongside an Nvidia card for ML/CUDA? Especially with Sway? I use Sway/AMD for desktop but all the photogrammetry software out there requires CUDA. It's a bit of a PITA.

Mehdi2277 5y ago
It can work but generally you either have performance issues or less library support or run into more operational pains. I mainly work on building library tooling over tensorflow. Losing support for good number of operations is not something that I could reasonably consider. Also cloud amd gpu support is near non-existent and most of my company's compute relies on the cloud. t4 pricing is very nice on gcp. Like AMD rocm exists for ml, but is very far behind cuda in support/libraries for ml. I don't think any moderate investment in AMD gpus is likely to catch up, so I'm pretty pessimistic of AMD being a good solution for ML usage anytime in the next several years. I think a hobbyist who already owns an AMD card and wants to do basic ML is only situation I'd consider it. Any other situation and I'd strongly advise against it.
- Steltek 5y ago
  Sorry, I think you misunderstood. This is installing both types of card in the same computer: one for desktop/Wayland (AMD), and the other for ML/CUDA (Nvidia).

my123 5y ago

> and that Nvidia did not support Wayland Nvidia does support Wayland. For KDE, the issue is: https://invent.kde.org/qt/qt/qtwayland/-/merge_requests/24 https://invent.kde.org/qt/qt/qtwayland/-/merge_requests/24 You'll have to wait until that gets to your distribution to have a usable KDE experience with NVIDIA on Wayland. In general, if you use those GPUs, please use the latest distributions.