What makes an "AI datacenter" different than a normal datacenter? Is it just that it's fully dedicated to racks of servers specifically for AI purposes?
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@lattera the density is higher i think. I've heard that they can't just swap out hardware if they want to upgrade. Requires entire tear down of the racks, power, and cooling and rebuilding it.
edit: obviously this just sounds insanely stupid and risky to not be able to repurpose the infra
edit: obviously this just sounds insanely stupid and risky to not be able to repurpose the infra
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@phnt @lattera @feld iirc are there a few engineering problems, why retrofitting isn't really possible.
like those racks have A LOT more weight per sqm and A LOT higher Power-Demand then what one would normally plan for with a normal datacenter.
Also probably higher cooling needs with more compute density with all those GPUs(?)
@feld @lattera Companies like Amazon and Google already don’t service systems within a rack. They build a whole rack, deploy it as one unit, then decommission it as one unit when a certain percentage of it has failed.
I suspect what makes an “AI datacenter” is actually buzzword bingo, but it could plausibly be about the dominant type of compute it provides: CPU or GPU.