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?
I’ve been doing exactly that at home for a couple years now. First with Parsec, now Sunshine/Moonlight.
Host is Proxmox on Ryzen 5800x, 64gm RAM GPU is 2070 Super, with VGPU patched drivers from https://gitlab.com/polloloco/vgpu-proxmox
When I’m gaming I’ll dedicate the full 8Gb to my windows Vm, otherwise I split it in 2 or 4Gb chunks to Jellyfin or my home camera monitoring. 8gb can’t split very many ways, and most things require at least 2 to run.
Locally at home I can run 1440p 60fps rock solid over wifi on any device, from my phone/old laptop/apple tv/raspberry pi. Remote I can do 1080p60, but a bit more hit or miss depending on my network connection.
Experimenting with LLMs I’ve done through the same windows VM, or to a ubuntu dev VM. Works the same way. I’m thinking of transitioning my gaming VM to Linux too.
The amount of VRAM is the hard limitation to get past, the virtualization tech itself has been there for a while.
But to be perfectly honest……it really was just a “let’s see if I could do this” type task, direct GPU pass though is more straightforward and it’s not really worth splitting 8Gb these days. Unless you get a card with significantly more VRAM passthrough is much less work.
This is really amazing! In theory, can you can use 2gb with 4 different VMs?
Sure, but you’ll get diminishing returns most likely as consumer hardware doesn’t really have the resources to scale that way very well if all the VMs are running demanding apps simultaneously.
Even for something like 4 VMs that just do NVenc, there are limits for how many streams the GPU can do. I think there’s another patch that lets you raise that, but at some point you’ll run out of resources quick. Even powerful consumer gear isn’t really designed to be used by more than one user/app and it starts to show the more you virtualize and split those resources.
How does the vGPU compare to running it on the bare metal? Last I tried things were painful but technically usable.
I don’t see any performance differences with the vgpu actually. I have more performance bottlenecks with the CPU, and my RAM isn’t the fastest, so I think I’m more CPU limited. Benchmarks I have run that are GPU focused seem to show little to no difference from what the physical card would do.
Hmm. I’m running a 3090 and 4090. Looks like vgpu is not possible yet for those cards.
Yeah unfortunately. 20xx is last generation supported so far via the patch, not sure if support for later cards is coming or not.
Have you tried or do you have any knowledge about utilizing the display ports on the gpu while virtualizing either in lieu or in tandem with streaming displays?
No, but I think you’d have some problems. Only the host has access to the actual DisplayPort outputs, all the vgpus have virtual displays, I don’t think there’s a way to make them use the physical out.