Forget the board – can your whimpy-ass power supply handle the load?
No :(
I have a separate gaming PC and am considering to just use that hardware for my NAS and create a VM for gaming
You have put yourself into this black hole lol.
“I might just get a- Oh god my gaming rig is now my secondary PC and my credit card hurts. How did this happen?!”
3090s snicker evily in the background
Im used to this from the whole “build your own gaming pc/nas” rabbit hole. Now it’s just some extra gpus and I might be able to have a two in one build (which will of course offset any costs for more 3090s /s)
Check out Games on Whales for self hosted game streaming!
Didn’t someone just make a post about a game stream server that would allow multiple gamers to use the same machine?
Not with VMs, but multiple users and virtual displays.Using docker.You’d connect to it via any moonlight client, and it creates the environment for you to use the machine for whatever.
Edit: Yes
Yeah it’s a pretty cool project and I’ll definitely use it. However nothing can beat a straight connection from monitor to gpu, so I’ll probably use passthrough for the gpu when gaming
Look at it this way: not only can you run your own AI stuff yourself, you can have your own cloud gaming too!
Why use commercial graphics accelerators to run a highly limited “AI”-unique work set? There are specific cards made to accelerate machine learning things that are highly potent with far less power draw than 3090’s.
Because those specific cards are fuckloads more expensive.
Well yeah, but 10x the price…
Not if it’s for inference only. What do you think the “AI accelerators” they’re putting in phones now are? Do you think they’d be as expensive or power hungry as an entire 3090 for performance if they were putting them in small devices?
Ok,
Show me a PCE-E board that can do inference calculations as fast as a 3090 but is less expensive than a 3090.
I’d be interested (and surprised) too
Yeah show me a phone with 48GB RAM. It’s a big factor to consider. Actually, some people are recommending a Mac Studio cause you can get it with 128GB RAM and more and it’s shared with the AI/GPU accelerator. Very energy efficient, but sucks as soon as you want to do literally anything other than inference
I wouldn’t say it particularly sucks. It could be used as a powerhouse hosting server. Docker makes it very easy to do no matter the os now a days. Really though I’d say its competition is more along the lines of ampere systems in terms of power to performance. It even beats amperes 128 core arm cpu at a power to performance ratio which is extremely impressive in the server/enterprise world. Not to say you’re gonna see them in data centers because price to performance is a thing as well. I just feel like it fits right into the niche it was designed for.
It’s for inference, not training.
Even better, because those are cheap as hell compared to 3090s.
Huh?
Stuff like llama.cpp really wants a GPU, a 3090 is a great place to start.
What are you recommending, I’d be interested in something that’s similar in price to 3090.
Would you link one? Because the only things I know of are the small coral accelerators that aren’t really comparable, and specialised data centre stuff you need to request quotes for to even get a price, from companies that probably aren’t much interested in selling one direct to customer.
