Bibliographic record
Abstract
As part of integrated circuit design verification, one should check if the voltage drop on the power grid exceeds some critical threshold. One way to do this is by simulation, but that is computationally expensive and gets prohibitive for large circuits with a large variety of possible operational modes. Another limitation of a simulation-based approach is that it requires complete knowledge of the logic circuitry drawing current from the grid, thus precluding grid verification early in the design process. In this paper, we model the grid as an RLC circuit and we propose three verification techniques that can be applied in the early stages of the design process. These techniques do not require exact knowledge of the circuit currents. Instead, the currents drawn by the logic beneath the power grid are described by means of current constraints that capture the uncertainty about circuit details and activity. The first verification approach gives the exact worst-case voltage drop at every node of the grid, but it is slow. A second faster approach gives conservative bounds on the worst-case voltage drop at every node of the grid. The third approach is much faster; it is a conservative approach which simply checks if the grid voltage drop exceeds some pre-defined thresholds, without actually computing the worst-case voltage drop at every node.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".