Your AI data center is running multiple high-power NVIDIA GPUs, and you’ve noticed an increase in operational costs related to power consumption and…

Implementing AI-based dynamic thermal management systems is the most effective strategy for

optimizing power and cooling efficiency in an AI data center with NVIDIA GPUs without sacrificing

performance. NVIDIA’s DGX systems and DCGM support advanced power management features that

use AI to dynamically adjust power usage and cooling based on workload demands, GPU

temperature, and environmental conditions. This ensures optimal efficiency while maintaining peak

performance. Option B (reducing utilization) compromises performance, defeating the purpose of

high-power GPUs. Option C (switching to air-cooling) is less efficient than liquid-cooling for high-

density GPU setups, per NVIDIA’s data center designs. Option D (increasing fan speeds) raises power

consumption without addressing root inefficiencies. NVIDIA’s documentation on energy-efficient

computing highlights dynamic thermal management as a best practice.

Reference: NVIDIA AI Infrastructure for Enterprise (www.nvidia.com), Modern Data Centers

(www.nvidia.com).