Earlier quoted context omitted.
You could power limit the 3090s to fit a standard 120V*20A = 2400W outlet if you really want to. The default power limit is 350W each so you'll only lose a little perf. Also most rooms have multiple circuits. Just connect half the GPUs to each outlet. I already do this with my desktop PC because it has 2 PSUs. Also most homes in the US have 30A*240V = 7200W dryer/stove outlets in the kitchen, laundry room, garage, et…
Brb replacing my stove with a bunch of GPUs
Serving AI from the Basement – 192GB of VRAM Setup
41–50 of 279 posts
Re: Serving AI from the Basement – 192GB of VRAM Setup
#42Hey guys, this is something I have been intending to share here for a while. This setup took me some time to plan and put together, and then some more time to explore the software part of things and the possibilities that came with it. Part of the main reason I built this was data privacy, I do not want to hand over my private data to any company to further train their closed weight models; and given the recent drop…
Re: Serving AI from the Basement – 192GB of VRAM Setup
#43You could just buy a Mac Studio for 6500 USD, have 192 GB of unified RAM and have way less power consumption.
You could for sure, but the nVidia setup described in this article would be many times faster at inference. So it’s a tradeoff between power consumption and performance. Also, modern GPUs are surprisingly good at throttling their power usage when not actively in use, just like CPUs. So while you need 3kW+ worth of PSU for an 8x3090 setup, it’s not going to be using anywhere near 3kW of power on average, unless you’re…
Re: Serving AI from the Basement – 192GB of VRAM Setup
#44Re: Serving AI from the Basement – 192GB of VRAM Setup
#45Earlier quoted context omitted.
Yep. The 8x3090 setup should be at least 10 times faster than the Mac.
Yes though for inference memory bandwidth is more important than tflops. Not sure how Apple compares in that regard. The OP does train models too though which is more compute heavy.
Re: Serving AI from the Basement – 192GB of VRAM Setup
#46Earlier quoted context omitted.
Do you run this 24/7? What is your cost of electricity per kilowatt hour and what is the cost of this setup per month?
I have a much smaller setup than the author - a quarter the GPUs and RAM - and I was surprised to find it draws 300W at idle
Re: Serving AI from the Basement – 192GB of VRAM Setup
#47Earlier quoted context omitted.
A single 3090 will deliver more tflops than the m2 ultra.
The M2 Ultra doesn't require doing electrical work on your house like this 8x 3090 setup did though.
Re: Serving AI from the Basement – 192GB of VRAM Setup
#48What is the power draw under load/idle? Does it noticeably increase the room temperature? Given the surroundings (aka the huge pile of boxes behind the setup), curious if you could get away with just a couple of box fans instead of the array of case fans. Are you intending to use the capacity all for yourself or rent it out to others?
Box fans are surprisingly power hungry. You'd be better off using large 200mm PC fans. They're also a lot quieter
Re: Serving AI from the Basement – 192GB of VRAM Setup
#49Earlier quoted context omitted.
You could for sure, but the nVidia setup described in this article would be many times faster at inference. So it’s a tradeoff between power consumption and performance. Also, modern GPUs are surprisingly good at throttling their power usage when not actively in use, just like CPUs. So while you need 3kW+ worth of PSU for an 8x3090 setup, it’s not going to be using anywhere near 3kW of power on average, unless you’re…
Can Reflection:70b work on them?
Edit: I guess to directly answer your question, I don’t see why you couldn’t run a 70b model at full quality on either a M2 192GB machine or on an 8x 3090 setup.
Re: Serving AI from the Basement – 192GB of VRAM Setup
#50Hey guys, this is something I have been intending to share here for a while. This setup took me some time to plan and put together, and then some more time to explore the software part of things and the possibilities that came with it. Part of the main reason I built this was data privacy, I do not want to hand over my private data to any company to further train their closed weight models; and given the recent drop…