8.8 A 112Gb/s PAM-4 Low-Power 9-Tap Sliding-Block DFE in a 7nm FinFET Wireline Receiver
Bibliographic record
Abstract
Recent advances in ADCs have enabled DSP-based equalization (e.g. extensive FFE and DFE) of wireline channels. FFE and canonical DFE sizes scale linearly with the number of taps, however the computational complexity of an FFE is much greater than that of a DFE. The canonical DFE is challenged by timing closure, and necessary techniques to ease it result in exponential growth in size. As a result, the majority of state-of-the-art DFE implementations have been limited to only 1-2 taps [1-4]. In this paper, a sliding-block DFE (SB-DFE) is introduced that enables pipelining and breaks the barrier to implementing much longer DFEs. Consequently, the DFE length can be extended to encompass all postcursors. Unlike FFEs, DFEs do not amplify noise. Moreover, a long DFE can relax or even remove the postcursor equalization burden on the CTLE and FFE, saving area and power.
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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) | 0.001 | 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".