At this week’s AI Infrastructure Summit in Silicon Valley, NVIDIA’s VP of Accelerated Computing Ian Buck unveiled a daring new imaginative and prescient: the transformation of conventional information facilities into totally built-in AI factories.
As a part of this initiative, NVIDIA is growing reference designs to be shared with companions and enterprises worldwide — providing an NVIDIA Omniverse Blueprint for constructing high-performance, energy-efficient infrastructure optimized for the age of AI reasoning.
Already, NVIDIA is collaborating with scores of corporations throughout each layer of the stack, from constructing design and grid integration to energy, cooling and orchestration.
It’s a pure evolution for the corporate, scaling past chips and techniques into a brand new class of commercial merchandise — so complicated and interconnected that no single participant can construct them alone.
NVIDIA, together with a deep bench of commercial and know-how companions, is reactivating many years of infrastructure experience to construct this new class of AI factories.
Amongst these companions, Jacobs serves because the design integrator, serving to to coordinate the bodily and digital layers of the infrastructure to make sure seamless orchestration.
The embodiment of the reference design might be a digital twin of the AI manufacturing facility. This digital twin integrates the IT techniques inside the info middle with the operational know-how for energy and cooling techniques inside and out of doors the info middle.
The brand new initiative expands the digital twin to combine native energy technology, power storage techniques, cooling know-how and AI brokers for operations.
Longtime collaborators in energy and cooling — Schneider Electrical, Siemens and Vertiv — have been instrumental in shaping resilient, high-efficiency environments tailor-made for AI-scale workloads.
Siemens and Siemens Vitality performs a crucial position in on-premises energy supply, supporting the necessity for quickly deployable, steady energy to fulfill the gigawatt-scale power calls for of those services. GE Vernova collaborates in energy technology and electrification to the rack.
These corporations, together with a rising ecosystem of specialists in infrastructure design and simulation, and orchestration — together with Cadence, Emerald AI, E Tech Group, phaidra.ai, PTC, Schneider Electrical with ETAP, Siemens and Vertech — are serving to NVIDIA activate a system-level transformation.
On the coronary heart of this imaginative and prescient lies a basic problem: learn how to optimize each watt of power that enters the power in order that it contributes on to intelligence technology.
In at the moment’s information middle paradigm, buildings are sometimes designed independently of the compute platforms they home, resulting in inefficiencies in energy distribution, cooling and system orchestration.
NVIDIA and its companions are flipping that mannequin.
By designing the infrastructure and know-how stack in tandem, the corporate allows true system-level optimization — the place energy, cooling, compute and software program are engineered as a unified entire.
Simulation performs a central position on this shift.
Corporations will be capable to share simulation-ready belongings, permitting designers to mannequin parts in Omniverse utilizing AI manufacturing facility digital twins even earlier than they’re bodily accessible.
These digital twins not solely optimize AI factories earlier than they’re constructed — additionally they assist handle them as soon as they’re operational.
By adopting the OpenUSD framework, the simulation platform can precisely mannequin each side of a facility’s operations, from energy and cooling to networking infrastructure. This open and extensible method permits for the creation of bodily correct belongings, which in flip results in the design of smarter, extra dependable services.
And the complexity doesn’t cease on the facility partitions.
AI factories have to be plugged into broader techniques — energy grids, water provides and transportation networks — that require cautious coordination and simulation all through their lifecycle to make sure reliability and scalability.
This work has already begun.
Earlier this 12 months, NVIDIA launched an Omniverse Blueprint for AI manufacturing facility digital twins. This blueprint connects platforms like Cadence and ETAP, permitting companions to plug of their core instruments to mannequin gigawatt-scale services earlier than a single bodily AI manufacturing facility website has even been chosen.
Extra not too long ago, the corporate expanded its ecosystem with integrations from Delta, Jacobs, Siemens and Siemens Vitality, enabling unified simulation of energy, cooling and networking techniques.
When this blueprint is full subsequent 12 months, it would enable companions to plug into the system through software programming interfaces and simulation-ready digital belongings, enabling real-time collaboration and orchestration throughout the complete lifecycle — from design to deployment to operation.
Because of this work, the place conventional services operated in isolation, AI factories might be designed for composability, resilience and scale.
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