NVIDIA DSX adopted for lower-water AI factories in Europe
2 companies named across 4 categories, one of 616 articles referencing Nvidia. Previous coverage: Dell'Oro Group finds optics central to AI networking at OCP 2026 (Oct 2026).
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At GTC Berlin, Europe’s leading ecosystem partners were described as adopting the NVIDIA DSX AI Factory Platform to build AI factories that reduce cooling water use and power draw for the same AI output.
Power availability defines how much capacity operators can bring online. The platform also helps partners bring new capacity online faster and adjust workload power consumption to support grid reliability.
Conventional cooling towers remove heat by evaporating water and need a continual supply of replacement water. NVIDIA DSX reference designs instead use closed-loop liquid cooling with outdoor dry coolers that release heat into the air without evaporating water. Compared with conventional cooling-tower systems, a 2-gigawatt deployment can save 54 million liters a day, equal to the daily water use of 180,000 households.
DSX MaxLPS allocates power dynamically within an AI factory’s provisioned budget, allowing operators to generate the same number of tokens with up to 30% less power. In a proof of concept on NVIDIA HGX B200 systems, Lambda demonstrated 24% more cluster token throughput and 19% more GPU capacity within a fixed power budget.
DSX Flex coordinates workload power consumption with grid conditions, and Nscale demonstrated DSX MaxLPS across four NVIDIA GB300 NVL72 racks at its Iceland AI factory, reporting 49% higher inference throughput and 37% more managed GPU capacity within a 264-kilowatt provisioned power budget. New NVIDIA DSX OS components, in developer preview, help automate infrastructure lifecycle tasks, while cloud partners are exploring them.
“Europe’s technology leadership depends on how efficiently we turn power and infrastructure into intelligence,” said Warren Barkley, vice president of DSX product management at NVIDIA. “NVIDIA DSX brings together the technologies and ecosystem expertise operators need to build responsibly, operate efficiently at scale and bring intelligence to the market faster.” Forward-looking statements in the source material are subject to risks and uncertainties and do not guarantee future performance.
Press release, provided by Globe Newswire on behalf of Nvidia. Read the original.