General models for optimum arbitrary-dimension FPGA switch box designs
Bibliographic record
Abstract
Abstract–An FPGA switch box is said to be hyper-universal if it is routable for all possible surrounding multi-pin net topolo-gies satisfying the routing resource constraints. It is desirable to design hyper-universal switch boxes with the minimum number of switches. A previous work, Universal Switch Module, consid-ered such a design problem concerning-pin net routings around a single FPGA switch box. However, as most nets are multi-pin nets in practice, it is imperative to study the problem that involves multi-pin nets. In this paper, we provide a new view of global routings and formulate the most general-sided switch box de-sign problem into an optimum-partite graph design problem. Applying a powerful decomposition theorem of global routings, we prove that, for a fixed, the number of switches in an opti-mum-sided switch box with terminals on each side is, by constructing some hyper-universal switch boxes with switches. Furthermore, we obtain optimum, hyper-universal-sided and-sided switch boxes, and propose hyper-universal-sided switch boxes with less than switches, which is very close to the lower bound obtained for pure 2-pin net models in [5]. 1
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".