Area Optimization of Delay-Optimized Structures Using Intrinsic Constraint Graphs
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Bibliographic record
Abstract
In this paper, we present a new methodology for structure optimization of block-based design. Instead of merging area and delay criteria, we segregate them into two independent steps. Solutions optimized for delay in the first step are optimized for area with a block-sizing algorithm in the second step. The fully optimized solutions eventually return to the first optimization step, if the user constraints are not met, using a structure-extraction module. A condition to this approach is that the area optimization phase does not alter the quality reached during delay optimization. We propose a framework for area optimization of delay-optimized structures based on structure similarities. We present a new model to represent block placements that share the same qualities for global routing. Using this model, we formally define the relation of similarity and exhibit several properties and theorems to validate our approach. The modules composing the area optimization phase are presented and experimental results confirm the validity of our methodology.
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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 | 0.001 | 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