Supercomputers and cutting-edge AI data centers are fueling the artificial intelligence (AI) revolution. Large-scale systems need comprehensive builds that are increasingly integrated to meet the evolving demands of complex workloads. As AI applications become more sophisticated, the need for infrastructure that's not only incredibly powerful but also energy-efficient is growing exponentially. Innovations like NVIDIA’s GB200 are designed to deliver the scalability needed for next-generation AI superclusters.  

At the 2025 NVIDIA GPU Technology Conference (GTC), VP and Chief Architect of Systems, Mike Houston, and Senior Director of Applied Systems Engineering, Julie Bernauer, discussed large-scale systems design principles in their May 18 presentation, “Next-generation at Scale Compute in the Data Center.”

NVIDIA’s First Rack-Scale Product is the GB200 Superchip

The NVIDIA Grace Blackwell 200 (GB200) Superchip combines two Blackwell GPUs and one Grace CPU. It’s NVIDIA’s first rack-scale product. The NVIDIA GB200 NVL72 is a configuration and rack-scale, liquid-cooled AI computing platform, which is purpose-built for AI training and inferencing, handling up to 27 trillion parameters for generative AI models. The GB200 includes base components like Grace Hopper compute trays, NVLink switches (a connector in the middle of the rack linking all GPUs) and cable cartridges (literally miles of cables in the back to tie everything together). The design includes quantum switches for InfiniBand (a high-speed network for linking clusters) and spectrum switches for Ethernet.

AI 101: What are Clusters and Superclusters?