Crossbar based design schemes for switch boxes and programmable interconnection networks
Bibliographic record
Abstract
Crossbars have been considered one of the most standard switching modules in conventional communication networks due to its simplicity in routing algorithm and fabrication regularity. While in programmable on-chip interconnection networks such as the routing networks in field programmable gate arrays (FPGAs), switch boxes are often used for a better tradeoff between routability and area efficiency. Much work has been done on the topology design of switch boxes, e.g. universal switch boxes and hyper-universal switch boxes. However, the layout design of switch boxes tends to be difficult when the topology of switch boxes is less regular. In this paper we revisit the theoretical design aspects of the classic crossbar design schemes and further investigate a new design style, a so called meta-crossbar, which is obtained from a crossbar by adding the least number of switches and direct contacts to achieve the desired optimal routability. We show that a switch box can always be implemented by a meta-crossbar. This means that the layout design of switch boxes can be done almost like crossbars. As a result, we present a hyper-universal meta-crossbar design, and a three level meta-crossbar based interconnection network design, which is capable of routing all group communication requirements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".