this post was submitted on 15 Jun 2024
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For years I’ve had a dream of building a rack mounted PC capable of splitting its resources to host multiple GPU intensive VMs:

  • a few gaming VMs
  • a VM for work that can run Davinci Resolve and Blender renders
  • an LLM server
  • a Stable Diffusion server
  • media server

Just to name a few possibilities…

Everytime I’ve looked into it, it seemed like the technology just wasn’t there yet. I remember a few years ago Linus TT took a shot at it, but in the end suggested the technology (for non-commercial entities) just wasn’t in a comfortable spot yet.

So how far off are we? Obviously AI focused companies seem to make it work, but what possibilities exist for us self-hosters who might also want to run multiple displays in addition to the web gui LLM servers? And without forking out crazy money for GPU virtualization software licenses?

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[–] zelifcam@lemmy.world 8 points 3 months ago* (last edited 3 months ago)

Everytime I’ve looked into it, it seemed like the technology just wasn’t there yet. I remember a few years ago Linus TT took a shot at it, but in the end suggested the technology (for non-commercial entities) just wasn’t in a comfortable spot yet.

I had a sever in my basement running proxmox ( actually ended up doing it all manually eventually ), with a windows gaming VM and handful of utility Linux servers in 2015? The only problem being Windows games using kernel level anti cheat.

I get it really comes down to GPU sharing and I think it’s doable on consumer GPUs now but I’m not sure about gaming. Honestly the tech has been here for a long time. But companies like NVIDIA held on forever to the GPU resource sharing features and kept it away from consumer cards.

I’m a bit older these days and have gone through many generations of hardware with a different setup. I keep two or more GFX cards on hand. Latest always goes to my workstation while last gen is thrown in my sever and used by all my docker containers. Then have an older Xeon with 24 bays that I use for storage.