Design of Static Single-Phase Flip-Flops for Energy-Efficient Near-Threshold Voltage Operation
Bibliographic record
Abstract
Flip-flops (FFs) and clock distribution networks, two core parts of the clocking system, are becoming increasingly important in chip design. They consume 60% of the overall dynamic power because of the constant clock transition and a large number of clock transistors in each FF. FFs and latches dissipate 50% of the overall dynamic power. They also have a significant impact on the performance, robustness, and size of the circuit in the near-threshold voltage (NTV) region. Thus, static and energy-efficient FFs are required in sequential circuits for NTV operation. In this paper, we propose two static contention-free single-phase negative edge-triggered flip-flops: a Low Transistor Count FF (LTCFF) and an Ultra-Low Power FF (ULPFF). Both designs reduce the number of clock transistors to just four. In the LTCFF, the transistor count is reduced to 16 by using a merging and sharing approach, while the static behavior of the FF is kept. The ULPFF, consisting of only 22 transistors, is extended from the LTCFF by eliminating redundant internal transitions to ensure ultra-low power operation. Designed in a 65-nm technology using Cadence Virtuoso, the proposed LTCFF and ULPFF achieve a reduction of 68.77% (or 67.05%) and 74.22% (or 70.58%) in the power-delay product (PDP), compared to the widely used transmission gate flip-flop (TGFF) at a supply voltage of 1 V and 1 GHz clock frequency (or 0.4 V and 25 MHz) with 10% data activity. These designs are simulated with different voltages from 0.4 V to 1 V and process corners to ensure good performance in near-threshold operation and that there are no floating nodes for any input combination.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".