Energy-cost-aware scheduling of HPC workloads
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
Job submission in high performance computing workloads exhibits a diurnal pattern similar to electrical prices. While high-priority jobs may need immediate access to resources, by altering the cluster scheduler to delay the execution of lower-priority jobs when power prices are high, significant cost savings can be achieved. Reduction of power demands by consumers such as data centres when energy availability is low, as signaled by high prices, can also help to simplify challenges faced in reducing the carbon footprint of the electrical grid. In this paper we discuss patterns in electrical pricing and also look at some challenges in integrating more volatile, but environmentally friendly renewable energy sources into the electrical grid. Simulation results are also presented showing that high-priority jobs can still receive rapid service while achieving 25-50% electricity cost savings for lower priority jobs.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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