Metrics and an Infrastructure Model to Evaluate Data Center Efficiency
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This work describes two data center efficiency metrics: Power Usage Effectiveness (PUE) and Compute Power Efficiency (CPE). PUE characterizes the fraction of the total data center power used for IT work. CPE characterizes the overall data center efficiency, considering IT equipment utilization as well as how power is used in the data center. The PUE results from three data center studies are presented here. The data suggests that a carefully designed and managed data center has a PUE of 2.0. More studies are required to determine the range of values for the typical data center. A data center infrastructure and energy cost model is presented to compare hardware costs to infrastructure and energy costs. The impact of PUE on these costs is examined to illustrate the impact of data center efficiency on the total cost of operating a data center.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it