Company developing digital twins to model data centers before they're built
Nvidia is developing a data center reference design and expanded digital twin optimized for its hardware.
At the AI Infrastructure Summit in Silicon Valley this week, the chip giant announced it was developing data center reference designs to be shared with partners and enterprises worldwide, known as the AI Factory Giga-Scale Reference Designs.
The GPU designer said it would be offering an Omniverse Blueprint digital twin for building high-performance, energy-efficient infrastructure optimized for AI hardware. The blueprint is set to be complete earlier this year.
Earlier this year, Nvidia introduced an Omniverse Blueprint for AI factory digital twins, allowing customers to aggregate detailed 3D and simulation data representing all aspects of the data center into a single, unified model, enabling them to design and simulate high-density hardware and allowing partners to model gigawatt-scale facilities ahead of time.
This digital twin integrates the IT systems inside the data center with the operational technology for power and cooling systems inside and outside the data center. The new initiative expands the digital twin to integrate local power generation, energy storage systems, cooling technology, and AI agents for operations.
“AI factories must be plugged into broader systems - power grids, water supplies, and transportation networks - that require careful coordination and simulation throughout their lifecycle to ensure reliability and scalability,” Nvidia said. “By designing the infrastructure and technology stack in tandem, the company enables true system-level optimization - where power, cooling, compute, and software are engineered as a unified whole. Simulation plays a central role in this shift.”
Collaborators in power and cooling include Schneider Electric, Siemens Energy, and Vertiv. Other companies involved include Cadence, emeraldai, E Tech Group, phaidra.ai, PTC, Schneider Electric with ETAP, Siemens, and Vertech.
Source: DCD
