Statistical verification of power grids considering process-induced leakage current variations
Why this work is in the frame
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Bibliographic record
Abstract
Transistor threshold voltages (V/sub th/) have been reduced as part of on-going technology scaling. The smaller V/sub th/ values feature increased variations due to underlying process variations, with a strong within-die component. Correspondingly, given the exponential dependence of leakage on V/sub th/, circuit leakage currents are increasing significantly and have strong within-die statistical variations. With these leakage currents loading the power grid, the grid develops correspondingly large statistical voltage drops. This leakage-induced voltage drop is an unavoidable background level of noise on the grid. Any additional non-leakage currents due to circuit activity will lead to voltage drop which is to be added to this background noise. We propose a technique for checking whether the statistical voltage drop on every node is within user-specified bounds, given user-specified statistics of the leakage currents.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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