A new parallel link interface with current-mode incremental signaling and per-pin skew compensation
Bibliographic record
Abstract
This paper proposes a new current-mode incremental signaling parallel link interface with per-pin skew compensation. Per-pin skew compensation is carried out in a training phase where clock-like training data are sent to all channels along with a reference clock of the same frequency. Training data are deskewed with respect to the common reference clock using DLLs such that all channels are skew-compensated simultaneously. New encoding and decoding scheme have been proposed to reduce the signal critical path at the transmitter. Transimpedance amplifiers with replica biasing are used to perform current-to-voltage conversion at the receiving end with a minimum sensitivity to supply voltage fluctuation. To evaluate the performance of the proposed skew compensating technique, a parallel link interface consisting of two data channels and one reference clock channel has been implemented with UMC 0.13 mum 1.2 V CMOS technology and analyzed using SpectreRF from cadence design systems with BIM3V3 device models. The channels are modeled as 50 Omega microstrip lines. Simulation results have demonstrated that the proposed parallel link interface is capable of deskewing the channel signals at 1 Gbytes/s.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".