A 1.5V 20/30 Gb/s CMOS backplane driver with digital pre-emphasis
Bibliographic record
Abstract
A high-speed input comparator and output driver with adjustable pre-emphasis for applications in serial interchip communications over backplanes at 20 Gb/s is presented. The circuit was implemented in 130-nm CMOS and consumes 140 mW from a 1.5-V supply. It has over 30 dB dynamic range with a sensitivity of 20 mVp-p and a differential output swing of 700 mVp-p at 20 Gb/s. The output driver features a novel digital pre-emphasis circuit with independent pulse height and width control. Other features include 30%-70% eye-crossing control and adjustable output swing between 170 mVp-p and 350 mVp-p per side at data rates up to 30 Gb/s.
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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".