Data Center Simulation for AI Infrastructure: Cadence and Nvidia Collaborate

As the demand for AI and generative AI models accelerates, datacenters are facing unprecedented pressure to handle intensive workloads. Before committing billions to new GPU hardware, Cadence Systems recommends simulating how well your existing or planned data center infrastructure can manage the heat and power demands of these powerful systems.

At this week's AI Infrastructure Summit, Cadence showcased an advanced digital twin of Nvidia’s massive GB200 NVL72 Superpod—one of the most complex GPU clusters to date, consuming about one megawatt of power. This Superpod is composed of eight racks, each with 120 kW of NVL72 nodes, housing over 500 Blackwell GPUs and 288 Grace CPUs capable of delivering an impressive 11.5 exaFLOPS of low-precision compute.

The Importance of Thermal and Power Simulation

Maximizing the performance of such heavy-duty systems requires a data center specifically designed to manage intense thermal loads and rapid fluctuations in power consumption—from idle to full capacity within seconds. Under-sizing cooling or power infrastructure can lead to performance bottlenecks or, worse, hardware failures—costly mistakes for operators investing billions into next-generation AI hardware.

Cadence suggests leveraging digital twin simulations—using some spare GPUs to run virtual models—to test infrastructure capabilities via a game-like platform, akin to 'Datacenter Tycoon.' This preemptive modeling helps identify potential issues before hardware procurement and deployment, saving time and money.

Nvidia’s Role and the Digital Twin Ecosystem

Nvidia CEO Jensen Huang has been advocating for AI factories—or how he terms them, "bit barns"—as the next frontier in datacenter design. By partnering with Cadence since March, Nvidia aims to integrate its Omniverse-based visualization tools to simulate and optimize datacenter layouts and thermal performance.

Cadence’s Reality Digital Twin Platform supports drag-and-drop placement of virtual components such as racks, cooling units, and power supplies within a 3D environment. It incorporates over 14,000 models from more than 750 vendors, allowing for detailed physics simulations—such as computational fluid dynamics—to predict how infrastructure components will perform under various scenarios.

Continuous Optimization and Future Technologies

This capability doesn’t end once a purchase order is placed. Cadence emphasizes that its platform allows ongoing simulations of infrastructure modifications, failure scenarios, and performance optimizations—helping operators adapt to new hardware like Nvidia’s upcoming Kyber racks, which are expected to deliver up to 600 kW of power when shipped in 2027.

In essence, such digital twin models serve as vital planning tools, reducing risks and enabling efficient, resilient AI data centers capable of supporting the next wave of advanced workloads.

Note: If Cadence doesn’t have a model of a specific hardware component, they can create custom models, making the platform flexible for evolving data center designs and hardware deployments.

Sources: Industry Summit Reports and Nvidia’s Announcements