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Data Center News > Blog > Power & Cooling > New design demonstrates end-to-end energy-efficient cooling and power
Power & Cooling

New design demonstrates end-to-end energy-efficient cooling and power

Last updated: June 13, 2025 8:55 pm
Published June 13, 2025
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New design demonstrates end-to-end energy-efficient cooling and power
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Along with totally built-in end-to-end cooling and energy methods for this subsequent era platform, the reference structure unlocks a brand new period of infrastructure design by shifting from conventional buildouts. Vertiv options can be found as SimReady™ 3D property within the NVIDIA Omniverse Blueprint for AI manufacturing facility design and operations. The reference structure will be customised for bespoke knowledge centre designs to dramatically scale back planning instances and scale back danger through the buildout course of.

Vertiv works with NVIDIA and its knowledge centre roadmaps, to develop AI infrastructure methods and deployment-ready designs that anticipate elevated rack energy densities. For instance, Vertiv is collaborating with NVIDIA to help 800 VDC knowledge heart energy infrastructure for 1 MW IT racks and past, with Vertiv options accessible beginning in 2026.

“Constructing upon our robust collaboration with NVIDIA and a shared imaginative and prescient to advance AI infrastructure, Vertiv is proud to launch our complete reference design and SimReady™ 3D property for the NVIDIA GB300 NVL72 platform,” said Scott Armul, govt vp of world portfolio and enterprise items at Vertiv. “Vertiv options enable prospects to not solely scale quicker, however to optimise their AI-focused knowledge centres digitally earlier than a single bodily module is constructed.”

“By combining NVIDIA’s superior AI platforms with Vertiv’s experience in energy and cooling infrastructure, we’re enabling prospects to deploy next-generation knowledge centres which can be extra environment friendly, scalable, and prepared for probably the most demanding AI workloads,” stated Dion Harris, senior director of HPC and AI Infrastructure at NVIDIA. “Collectively, we’re serving to organisations unlock new ranges of efficiency and sustainability as they construct the way forward for AI.”

See also  Xela Energy paves the way for sustainable data centers in the UK

The reference structure for NVIDIA GB300 NVL72 is a part of the Vertiv™ 360AI infrastructure platform, designed to assist prospects navigate built-in options for powering and cooling AI workloads and different high-performance computing functions.

Key advantages of Vertiv’s reference structure and SimReady™ 3D property for the NVIDIA GB300 NVL72 design embrace:

● Simulation to Deployment in One Path: Leveraging NVIDIA Omniverse applied sciences within the structure bridges bodily and digital infrastructure, enabling real-time system-level collaboration throughout IT, services, and engineering groups – permitting prospects to check, optimise and validate the design earlier than a single element is constructed.

● Constructed for the Age of AI Reasoning: Supporting rack densities as much as 142kW, the reference structure for NVIDIA GB300 NVL72 defines the brand new benchmark for accelerated infrastructure – engineered for AI factories at scale.

● Accelerated Efficiency, Scale, and Velocity: Delivering 1.5x extra AI efficiency, as much as 50% quicker on-site builds and in 30% much less bodily area, Vertiv’s reference structure for NVIDIA GB300 NVL72 allows prospects to scale AI infrastructure with unprecedented agility and power effectivity.

● Thermal Flexibility Meets Effectivity Features: Liquid cooling-ready, supporting each air- and hybrid- cooled configurations, achieves as much as 70% higher annual power effectivity allowed by increased water temperatures.

● Design, Deploy, Function – Globally: Backed by 4,000+ Vertiv area service engineers globally, Vertiv’s reference structure for GB300 NVL72 brings unmatched scalability, serviceability, and provide chain reliability to world AI rollouts.

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TAGGED: cooling, demonstrates, Design, EndtoEnd, EnergyEfficient, Power
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