Calligrapher: a new layout migration engine based on geometric closeness
Bibliographic record
Abstract
As the foundries accelerate their update of advanced processes with increasingly complex design rules, the cost of hard intellectual property (IP) development becomes prohibitively high. Automated layout migration techniques used today, which are based on layout compaction developed a decade ago, corrupt advanced design considerations by honoring only design rules. In this paper, we present two new theoretical results: First, we propose a fast constraint generation algorithm proven to be linear, a step forward from the worst case quadratic complexity achieved in the literature. Second, we propose a new optimization metric, called geometric closeness, that can help retain advanced design intention. A layout migration engine based on these two results is implemented and integrated into a comprehensive hard IP development framework, under which the Berkeley low power libraries, originally developed for 1.2/spl mu/m MOSIS process, are successfully migrated into TSMC 0.25/spl mu/m and 0.18/spl mu/m technologies.
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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 | 0.001 | 0.001 |
| 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".