Leakage reduction techniques in a 0.13 um SRAM cell
Bibliographic record
Abstract
SRAM standby leakage is very becoming critical with technology scaling to meet the industry's demanding low power requirements. This paper discusses some of the leakage reduction techniques in a 0.13 um SRAM cell in a standard foundry process. Varying the cell bias voltages (VDD, VSS, well biases, bit-line pre-charge, and wordline off) to different standby levels helps achieve reduced leakage. Variation of these bias voltages by 0.3 v from normal voltage levels reduces the leakage to 10 pA/Cell at room temperature. The VDD and bit-line pre-charge levels need to be restored to at least 95% of the normal level before an active cycle for reliable noise margin. Depending on the bias voltage (VDD or VSS or both) variation, the access time and the static noise margin will be affected. This paper studies the details of critical SRAM cell parameters for different bias voltages variations to reduce standby leakage and their impact to the overall design.
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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".