Technology portable delay model for DSM CMOS inverters
Bibliographic record
Abstract
A closed form expression to accurately estimate the delay of a CMOS deep submicron (DSM) inverter is presented in this paper. This model does not depend on any extracted or fitting parameters. Instead it depends on the device model parameters. This model exhibits a good accuracy when compared with Spectre simulations using BSIM3v3 model, for a wide range of device sizes, capacitive loads, transition times, and aspect ratios (W/sub p//W/sub n/). Since this model is independent of extracted and fitting parameters, it is technology portable. The model is validated for three DSM technologies (UMC's 0.13 /spl mu/m, and TSMC's 0.18 /spl mu/m and 0.25 /spl mu/m). For all, the model shows good accuracy with on average error of about 4%. The maximum error is less than 10%.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".