Measuring the Accuracy of Layout Area Estimation Models of Tile-Based FPGAs in FinFET Technology
Bibliographic record
Abstract
This work presents the layout area of encoded and decoded multiplexers, two essential building blocks of modern FPGAs, in FinFET. Layouts with both 2 and 3 metal layers based on ASAP7 Predictive Design Kit are presented. The layout area is then compared with the prediction of two equation-based models: the VPR area model and the COFFE area model. We found that, with the original model parameters which are adjusted for planar technologies, these two equation-based models are not accurate in predicting FinFET layout area with error ranges of -2.3% to +86.5% and -32.7% to +19.3% for the VPR and COFFE models, respectively. Furthermore, when the model parameters are specifically adjusted for FinFET, the error ranges remain to be large with -19% to +31% and -26.6% to +25% for the VPR and COFFE models, respectively. These data underline the importance of verifying equation-based models against actual layout areas in FPGA architectural studies, especially when there are significant changes in the underlining process technologies.
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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 | 0.000 | 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 | 0.000 | 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".