NVIDIA DSX Enables European AI Factories to Slash Water Use and Cut Power Consumption by 30%

European Leaders Adopt NVIDIA DSX to Transform AI Infrastructure

European infrastructure companies including Nscale, Siemens, and Schneider Electric are building AI data centers on NVIDIA DSX, the chipmaker's comprehensive AI factory platform announced at GTC Berlin2

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. The NVIDIA DSX platform represents a fundamental shift in how AI infrastructure is designed, treating chips, networking, power, and cooling as one integrated system rather than siloed components1

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The adoption addresses a critical challenge facing the AI industry. Power consumption has become the biggest bottleneck in AI infrastructure development, with more than $300 billion in equipment backlogged and over 200 gigawatts of projects waiting in U.S. interconnection queues1

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. Warren Barkley, who leads DSX product management at NVIDIA, emphasized the urgency: "Europe's technology leadership depends on how efficiently we turn power and infrastructure into intelligence"2

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Near-Zero Water Consumption Through Advanced Cooling Technology

The NVIDIA DSX reference designs achieve near-zero facility cooling water consumption by replacing conventional cooling towers with closed-loop liquid cooling systems and dry coolers3

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. Instead of evaporating water to remove heat, cooling liquid absorbs heat from computing equipment and circulates in a closed loop while outdoor dry coolers release heat into the air without water evaporation3

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At 2-gigawatt scale, AI factories built on NVIDIA DSX can save 54 million liters of water daily compared with conventional cooling-tower-based systems—equivalent to the daily water use of 180,000 households2

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. The NVIDIA Vera Rubin infrastructure supports 100% liquid cooling with coolant temperatures reaching up to 45 degrees Celsius, enabling this water-saving approach3

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MaxLPS Delivers 30% Power Efficiency Gains

DSX MaxLPS software dynamically allocates power within an AI factory's provisioned budget, helping operators generate the same number of tokens with up to 30% less power3

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. London-based Nscale tested MaxLPS on four racks of GB300 servers at its Iceland site, achieving a 49% increase in inference throughput within the same 264-kilowatt power budget2

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CoreWeave, Firmus, Google Cloud, IREN, Lambda, Nebius, Nscale, and Sharon AI are planning to deploy this technology3

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. Nscale CEO Josh Payne stated the case directly: "Europe's AI ambitions demand that we make every megawatt count"2

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. The company is using DSX to create digital models of both its Iceland and Portugal sites before construction begins2

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Comprehensive Platform Addresses Power Bottleneck

The NVIDIA DSX AI Factory Platform integrates multiple components to optimize AI infrastructure from design through operation. DSX Sim and SimReady assets from leading energy manufacturers enable engineers to simulate the grid, substation, and AI factory together, validating generators, switchgear, power systems, and cooling before breaking ground1

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. DSX Flex synchronizes AI factory demand with grid conditions and onsite generation, transforming AI factories from static loads into flexible grid assets1

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A UK trial with National Grid and cloud firm Nebius demonstrated how compute resources respond to grid strain. The cluster reduced power draw by up to 40% during simulated grid events while critical work continued running2

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. This grid reliability capability enables faster grid connection and supports broader infrastructure stability3

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Expanding Ecosystem of Infrastructure Partners

A growing ecosystem of technology and industrial leaders is advancing NVIDIA DSX capabilities. Schneider Electric, working with AVEVA and ETAP, is developing validated NVIDIA Vera Rubin power and cooling reference architectures alongside Omniverse-powered AI factory digital twins1

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. The collaboration connects simulations, real-time operational data, and AI-driven optimization across multiple solutions to improve energy efficiency and workload performance while accelerating time to token1

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Siemens Energy is expanding its collaboration by developing reference designs for resilient, scalable, and grid-aware power infrastructure across generation, transmission, and distribution aligned with DSX Vera Rubin requirements1

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. Siemens is simulating power consumption, cooling, and noise characteristics2

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. Dassault Systèmes is building digital twins of Vertiv equipment, while ABB, Hitachi Energy, and Trane Technologies are contributing specialized components2

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Hitachi Energy's battery energy storage system has qualified as NVIDIA DSX Ready, helping customers identify power infrastructure meeting applicable reference architecture requirements for resilient, reliable, and scalable AI factories1

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. GE Vernova is deploying grid-to-facility and rack power expertise to complement DSX systems, enabling customers to transform power constraints into competitive advantages1

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Sustainability and Efficiency Drive European AI Development

Phaidra integrated DSX Flex, DSX Max-Q, and DSX Exchange into its self-learning agents, optimizing cooling and power allocation to maximize tokens per watt and deliver approximately 10% more compute within the same power envelope1

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. Emerald AI integrated its Conductor platform into DSX Flex to help utilities access underused grid capacity, an approach modeled to unlock up to 100 gigawatts on the existing U.S. grid1

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The sustainability and efficiency in AI infrastructure enabled by NVIDIA DSX positions European companies to compete globally while addressing environmental concerns. AI clouds across Europe are building and operating DSX-based AI data centers to expand access to accelerated computing for the continent's enterprises, developers, and governments3

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. The platform's ability to reduce both water and energy usage while maintaining or improving AI output creates a pathway for responsible expansion of AI infrastructure capacity across the region.