Design and implementation of a scalable switch architecture for efficient high‐speed data multicasting
Bibliographic record
Abstract
Abstract This paper presents the design and implementation of a new scalable cell‐based multicast switch fabric for broadband communications. Using distributed control and modular design, the multicast balanced gamma switch features a scalable, high performance architecture for unicast, multicast and combined traffic under both uniform and non‐uniform traffic conditions. The important design characteristic of the switch is that a distributed cell replication function for multicast cells is integrated into the functionality of the switch element with the self‐routing and contention resolution functions. Thus, no dedicated copy network is required. In the paper, we discuss in detail the design issues associated with the multicast functionality of the switch using 0.18 µm CMOS technology and discuss the scalability of the switch in terms of architectural, implementation, and performance scalability. Synthesized results are provided for measures of circuit complexity and timing. Copyright © 2006 John Wiley & Sons, Ltd.
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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 | 0.002 | 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 | 0.002 | 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".