Dynamic Data Stability in Low-power SRAM Design
Bibliographic record
Abstract
SRAM cell stability measurement is traditionally based on static criteria of data stability requiring 3 coincident points in butterfly curves. We introduce <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dynamic criteria</i> of stability for the cell knowing that the cell operates in a dynamic environment. It reveals that the true noise margin of the cell can be made considerably higher than the SNM once the cell access time is sufficiently shorter than the cell time-constant. This behavior enables enhancing SRAM yield as well as reducing cell operating voltage without compromising reliability. A 40Kb SRAM designed using SVGND scheme exploits the dynamic behavior of the cell in order to increase the stability and reduce the static and dynamic power consumption. The SRAM unit realized in 0.13μm CMOS consumes 702μW at 100MHz during write operation and offers a 27pA/Cell leakage current.
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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 | 0.002 | 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) | 0.001 | 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 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".