Simultaneous adaptive wire adjustment and local topology modification for tuning a bounded-skew clock tree
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Bibliographic record
Abstract
The need for incremental algorithms to implement engineering changes (ECs) in clock trees (CTs) is critical in the system-on-a-chip (SoC) design cycle. An algorithm, called adaptive wire adjustment (AWA), is proposed to minimize the clock skew iteratively to any given bound. In order to speed up AWA's convergence, a local topology-modification (LTM) technique is incorporated into AWA. Moreover, LTM incorporation into AWA results in total wire-length reduction as well. Also, the incorporation of the LTM technique into the deferred-merge embedding (DME) algorithm and Greedy-DME (GDME) helps reduce the total wire length by around 7.8% and 9.8%, respectively. Additionally, applying LTM to GDME reduces wire elongations and the standard deviation of the path lengths (SDPL) between clock pins by 96.4% and 51.5%, respectively.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it