Revisiting "Cooler is Better": ITD-Aware Per-CPU Thermal Optimization for Sustainable Data Center Operation
2026-06-09 • Distributed, Parallel, and Cluster Computing
Distributed, Parallel, and Cluster ComputingHardware Architecture
AI summaryⓘ
The authors studied how the amount of power used by modern CPUs changes with temperature and found that cooler isn't always better for energy efficiency. They showed that many CPUs work most efficiently at a specific, warmer temperature rather than the usual cooler settings in data centers. By adjusting cooling and grouping CPUs based on this finding, data centers can save energy without losing performance. Their tests in real cloud data centers showed energy savings of 4-13%.
data center coolingCPU power efficiencyinverse temperature dependence (ITD)Intel Xeon CPUsperformance-per-wattthermal managementlow-voltage CPUcloud computingenergy optimizationserver infrastructure
Authors
Jason Crop, Hayden Moore, Sudeep Pasricha
Abstract
As data center energy demand approaches grid-level constraints, optimizing conventional server infrastructure is essential for sustainable growth. The long-standing assumption that "cooler is better", i.e., lower CPU temperatures reduce power, does not fully hold for modern low-voltage CPUs, where inverse temperature dependence (ITD) drives higher supply voltages at lower temperatures. This creates a non-monotonic performance-per-watt curve where efficiency peaks at an intermediate thermal point. In this paper, for the first time, we empirically characterize ITD on production Intel Xeon CPUs and demonstrate that efficiency-optimal temperatures are CPU part-specific, and frequently higher than typical data center operating conditions. Measurements from commercial cloud data center platforms (Amazon, Equinix) reveal that approximately half of modern high-power CPUs operate about 10°C below their efficiency-optimal thermal point. By implementing ITD-aware thermal grouping of CPUs and inlet temperature adjustments, data center operators can optimize facility-level cooling and overall sustainability. Our case study shows that this approach can reduce total data center energy by 4-13% without sacrificing performance or reliability.