Ultra low leakage structures for logic circuits using symmetric and asymmetric FinFETs
Bibliographic record
Abstract
In this paper, FinFET devices are analyzed with emphasis on sub-threshold leakage current control. This is achieved through proper biasing of the back gate, and through use of asymmetric work functions for the four terminal FinFET devices. We are also examining various transistor configurations and circuit topologies for logic gates using both symmetric and asymmetric work function transistors. Based on extensive characterization data, the logic gates using symmetric devices with one additional supply voltage have the best tradeoff between leakage current and performance. However, with asymmetric devices the leakage current drops by an average of 95% with degradation in delay of 8%. For a carry generation complex gate, our configuration, using symmetric devices, both leakage current and delay are improved by 35% and 47% respectively compared to results in the literature. Using asymmetric devices without additional supply achieves average improvements in leakage and delay of 81% and 5% respectively. All simulations are based on 25nm FinFET technology using the University of Florida UFDG model.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".