Bibliographic record
Abstract
Global routing is an important and time consuming step in the VLSI physical design cycle. In order to solve this problem effectively, we present two standard cell global routing approaches: a heuristic approach and an integer linear program (ILP) based approach. The objective of the heuristic approach is to find the minimum cost path for each net by enumerating a set of possible two-bend routes. It is also parallelized by using the Message Passing Interface (MPI) library to speed up the running time and achieve better performance. The ILP based approach formulates the global routing problem as an ILP problem and then relaxes it as a linear programming (LP) problem to reduce the computation complexity. All the algorithms are evaluated on Sun-blade 2000; the experimental results show high performance from both global routers. Good speedups and solution qualities are obtained from the parallel implementation. The average speedup achieved is five times on six processors, and the total density is reduced by an average of 2.45% as well.
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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".