GB200, GB300, and Vera Rubin belong to a class of rack-scale AI systems that push heat rejection beyond what conventional air-only design can handle. The operating model is increasingly liquid-first: direct-to-chip cooling, a CDU-based distribution layer, and a chilled-water plant that may be supported by a cooling tower, dry cooler, or hybrid heat-rejection path.
For operators, the practical question is not whether one component is “the answer.” The real question is how the rack, CDU, pumps, valves, chillers, and plant controls stay balanced under fast-changing GPU load. That is why telemetry, BMS integration, and predictable maintenance are now part of the thermal design itself.
- Liquid cooling carries the highest heat density at the rack.
- The CDU translates rack demand into a stable facility-side water loop.
- The chiller plant, tower, and controls determine efficiency, resilience, and operating margin.
Air cooling still matters for support areas and lower-density spaces, but for these accelerators it is usually secondary to the liquid path. In practice, teams should think in layers: rack capture, water transport, heat rejection, and supervisory control.
Sources
NVIDIA GB200 NVL72 · NVIDIA GB300 NVL72 · NVIDIA Vera Rubin · NVIDIA Mission Control BMS integration · ASHRAE AI Data Center Energy Performance Framework
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