Bibliographic record
Abstract
This work investigates the minimum layout area of multiplexers, a fundamental building block of Field-Programmable Gate Arrays (FPGAs). In particular, we investigate the minimum layout area of 4:1 multiplexers, which are the building blocks of 2-input Look-Up Tables (LUTs) and can be recursively used to build higher order LUTs and multiplexer-based routing switches. We observe that previous work routes all four data inputs of 4:1 multiplexers on a single metal layer resulting in a wiring-area-dominated layout. In this work, we explore the various transistor-level placement options for implementing the 4:1 multiplexers while routing multiplexer data inputs through multiple metal layers in order to reduce wiring area. Feasible placement options with their corresponding data input distributions are then routed using an automated maze router and the routing results are then further manually refined. Through this systematic approach, we identified three 4:1 multiplexer layouts that are smaller than the previously proposed layouts by 30% to 35%. In particular, two larger layouts of the three are only 33% to 45% larger than layout area predicted by the two widely used active area models from previous FPGA architectural studies, and the smallest of the three layouts is 1% to 11% larger than the layout area predicted by these models.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".