Verification of the Power and Ground Grids Under General and Hierarchical Constraints
Bibliographic record
Abstract
As part of power distribution network verification, one should check if the voltage fluctuations exceed some critical threshold. The traditional simulation-based solution to this problem is intractable due to the large number of possible circuit behaviors. This approach also requires full knowledge of the details of the underlying circuitry, not allowing one to verify the power distribution network early in the design flow. Contrary to previous work on power distribution network verification, we consider the power and ground (P/G) grids together and describe an early verification approach under the framework of current constraints. Then, we present a solution technique in which tight lower and upper bounds on worst case voltage fluctuations are computed via linear programs. Experimental results indicate that the proposed technique results in errors in the range of a few millivolts. In addition to P/G grid verification techniques, we also provide very efficient solution technique to power (single) grid verification under hierarchical current constraints.
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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 | 0.000 | 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 | 0.000 | 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 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".