8.6 A Highly Reconfigurable 40-97GS/s DAC and ADC with 40GHz AFE Bandwidth and Sub-35fJ/conv-step for 400Gb/s Coherent Optical Applications in 7nm FinFET
Bibliographic record
Abstract
Low power digital signal processing (DSP) and optical integration have fueled the development of high-performance optical pluggable modules due to their deployment flexibility and network disaggregation. In addition, the rapid growth of new technologies such as 5G, cloud computing, IoT and AR/VR has prompted the demand for even higher data rates, requiring optical modules to scale beyond 400Gb/s while targeting the best possible tradeoff between power efficiency and reach. This necessitates more complex equalization schemes and coding techniques such as probabilistic shaping (PS) [1] and drives ever higher the specifications of analog building blocks. These requirements, as a result, constantly push the envelope of traditional analog-front-end (AFE) bandwidth and the rates of companion data converters such as DACs and ADCs to the technology limits, making it challenging to address a diversity of DSP modulation needs and oversampling rates while maintaining low power consumption. In this paper, we present an energy efficient optical transceiver fully integrated in a 400G coherent DSP chip using 4 reconfigurable 40-97GS/s 8b DACs and ADCs with a 40GHz AFE bandwidth, fabricated in a 7nm FinFET process.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".