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4× RTX Pro 6000 Blackwell on Water, and the One Card That Wouldn't Behave (sabareesh.com)
28 points by sabareesh 3 days ago
11 comments

It's difficult to speculate as to the exact failure from blurry pictures but the solder on that choke (inductor) looks terrible.

Something went wrong in manufacturing. The solder should have wicked to cover the entire pad, not just a small square, and there should be no (brown) discoloration.

What a time to be alive, I remember 10 years ago as a poor student waiting to buy a ATI Radeon X1600 Pro with 256mb, yes 256mb of RAM.

It cost about £190 in 2006.

Now we have GPUs that are in tens of thousands of pounds with insane performance, but what would their price be without the AI and Datacentre squeeze?

2006 is 20 years ago
I remember buying the Radeon PCI with 32MB RAM for $650AUD…
Ok, how are people powering these things? 2.4kW is well beyond a standard circuit in the US. Are people having 240V/30A circuits installed? Are they hijacking the dryer plugs? EV charger plugs? Hottub circuits?
240V-20A circuits will handle 3.8kW continuous. It’s probably a 240V-20A circuit, as that is what the power supplies typically want. Also, easy to convert an outlet to 240V, if the breaker is dedicated to that outlet. Just requires swapping the breaker and the outlet, not the wires.
Chaining two PSUs on separate circuits is also an option. If they're using the MaxQ versions though, the total GPU power draw is only ~1200W. The bigger question to me is how are they cooling it? Sticking an AC in that room just doubles the power draw issues.
It is basically on 2 different circuits/breakers. Asus wrx90e supports 2 psu as well. You may need to synchronize both psu and several adapter for this is available in Amazon. Soon planning to upgrade it to 240V
exactly, I had a 220v 30a circuit installed to run a multi-GPU server in my basement.

I'm air cooling so I set -pl 450 so I'm not running them all at the full 600w

I wonder whether those cards ran the model that wrote the nonsense about the forces involved.

Hint: when you have a piece of metal stuck with thermal goop to a lot of components, the force doesn’t “concentrate” on one of them. You need to detach it from each one with however much force is needed to detach it from that component.

Not sure what really happened but some force or bad solder caused it.
Cool post. FYI you might be better off getting one big fan for your "radiator" instead of lots of little fans. Big fans don't need to spin as fast as small fans to push the same amount of air. So they run a lot quieter.
Sure 140mm fans you may call little but it does need enough static pressure for the radiators. This setup is already several times quieter than stock setup
Is that little computer training LLMs from scratch all by itself? That must take years to get any kind of progress, given the scale of training other providers do. Where do you get the training data from?
Most of the training i am working on is with post training. You can do so much with a system that is running 24/7
You can train TinyStories in a few hours on retail hardware, and this is a highly illuminating experience that I can recommend for everyone.
Complete side note, but I can’t work out how the author managed to mistype “at” as “Δt”.

Edit: reading fail on my part, nothing to see here.

I caught that too, probably a qwen bug (;
huh? the only Δt in the article is used correctly.

> With 18× 140 mm of surface, the fans run quietly and the coolant Δt across the rads stays small

Hah, wow, I completely misread it. Delta-t makes sense when you get the context right, thanks.
Ditch the tiny DC fans. Build a shroud and switch to a single ac-powered industrial blower / duct fan.
If you want ready, well engineered, water-cooled multi-GPU research workstations, my colleagues at https://comino.com build and sell them. Or you can purchase fitted waterblocks from them for many GPUs, and build your own.
Converting four RTX PRO 6000 Blackwell cards to waterblocks, finding a VRM choke loose on the workbench, and getting back to 41k tok/s.
AI slop post.