A 65 nm Sub-$V_{t}$ Microcontroller With Integrated SRAM and Switched Capacitor DC-DC Converter
Bibliographic record
Abstract
Aggressive supply voltage scaling to below the device threshold voltage provides significant energy and leakage power reduction in logic and SRAM circuits. Consequently, it is a compelling strategy for energy-constrained systems with relaxed performance requirements. However, effects of process variation become more prominent at low voltages, particularly in deeply scaled technologies. This paper presents a 65 nm system-on-a-chip which demonstrates techniques to mitigate variation, enabling sub-threshold operation down to 300 mV. A 16-bit microcontroller core is designed with a custom sub-threshold cell library and timing methodology to address output voltage failures and propagation delays in logic gates. A 128 kb SRAM employs an 8 T bit-cell to ensure read stability, and peripheral assist circuitry to allow sub-Vtreading and writing. The logic and SRAM function in the range of 300 mV to 600 mV, consume 27.2 pJ/cycle at the optimalVDDof 500 mV, and 1 muW standby power at 300 mV. To supply variable voltages at these low power levels, a switched capacitor DC-DC converter is integrated on-chip and achieves above 75% efficiency while delivering between 10 muW to 250 muW of load power.
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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) | 0.003 | 0.001 |
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".