VLFF — A very low-power flip-flop with only two clock transistors
Bibliographic record
Abstract
Flip-flops (FFs) are an essential component of digital circuits, yet they use a lot of power and energy. This paper introduces the VLFF, an extremely low-power flip-flop that operates with just two single-phase clock transistors. The extracted simulation results show that VLFF is the most power-efficient FF amongst all examined FFs for the data activity (DA) range of 0% to 45%. Test-chip measurement results for the test-chip designed in TSMC CMOS 65 nm gp PDK demonstrate that at VDD = 1 V, power consumption is reduced by 63% and 16% with 12.5% DA, and 52% and 6% with 25% DA in comparison to TGFF and 18TSPC, respectively. • This paper proposed a very low-power flip-flop with only two single-phase clock transistors. • Proposed flip-flop is the most power-efficient amongst all considered. state-of-the-art flip-flops for data activities in the range of 0 – 45%. • Test-chip implemented in TSMC 65nm GP PDK validates the power savings of the proposed flip-flop over 18TSPC, and TGFF.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".