Energy Profiling in Games: Introducing a Frame-Based Power Consumption Metric
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
The pervasive integration of Information and Communication Technologies into everyday life has amplified concerns regarding their environmental impact, particularly due to the substantial energy consumption of their underlying infrastructures. Video games contribute significantly to this consumption. As the global gaming market continues to grow, green computing practices aimed at reducing the environmental footprint of digital systems have become imperative. However, measuring the energy consumption of video games lacks a standardized approach. This paper proposes a generic method for quantifying energy consumption in games, based on a performance-energy metric of joules per frame (J/frame). By combining two context-independent metrics, namely, game performance measured in frames per second and energy consumption in joules, this method provides a generic calculation applicable across every scenario.We present a new solution with a practical example, and discusses its advantages over current industry methods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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