this post was submitted on 16 Oct 2024
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I see the raise of popularity of Linux laptops so the hardware compatibility is ready out of the box. However I wonder how would I build PC right know that has budget - high end specification. For now I'm thinking

  • Case: does not matter
  • Fans: does not matter
  • PSU: does not matter
  • RAM: does not matter I guess?
  • Disks: does not matter I guess?
  • CPU: AMD / Intel - does not matter but I would prefer AMD
  • GPU: AMD / Intel / Nvidia - for gaming and Wayland - AMD, for AI, ML, CUDA and other first supported technologies - Nvidia.

And now the most confusing part for me - motherboard... Is there even some coreboot or libreboot motherboard for PC that supports "high end" hardware?

Let's just say also a purpose of this Linux PC. Choose any of these

  1. Blender 3D Animation rendering
  2. Gaming
  3. Local LLM running

If you have some good resources on this also let me know.

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[–] bloodfart@lemmy.ml 0 points 2 months ago (8 children)

You need to use intel/nvidia.

You might be able to get away with amd instead of intel, but nvenc and cuda support is a non negotiable thing for your use case.

You will not encounter any problems as long as you don’t run Wayland.

Any motherboard is fine. You don’t need coreboot support to run Linux.

[–] Psyhackological@lemmy.ml 1 points 1 month ago (1 children)

Interesting you exclude AMD.

Any? I was thinking of MSI or Asus motherboards.

[–] bloodfart@lemmy.ml 2 points 1 month ago

I don’t know of any msi or asus boards with problems. Of course, I rejected coreboot as a requirement so that plays into it.

My personal experience is: don’t overclock and everything will run fine for at least ten years.

Blender works faster with nvidia and it’s been the optimal hardware for maybe two decades now. There’s just so much support and knowledge out there for getting every feature in the tool working with it that I couldn’t in good faith recommend a person use amd cards to have a slightly nicer Wayland experience or a little better deal.

If you’re only doing llm text work then a case could be made for a non cuda (non-nvidia) accelerator. Of course at that point you’d be better served by one of those coral doodads.

Were you only doing text based ml work or was there image recognition/diffusion/whatever in there too?

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