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Record W2014410358 · doi:10.1587/elex.9.1550

A gate sizing and transistor fingering strategy for subthreshold CMOS circuits

2012· article· en· W2014410358 on OpenAlexaff
Morteza Nabavi, Maitham Shams

Bibliographic record

VenueIEICE Electronics Express · 2012
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsCarleton University
Fundersnot available
KeywordsNMOS logicPMOS logicCMOSSubthreshold conductionTransistorInverterComparatorElectronic engineeringElectronic circuitRing oscillatorElectrical engineeringPass transistor logicComputer scienceEngineeringVoltage

Abstract

fetched live from OpenAlex

Parallel Transistor Stacks (PTS) has been shown to be an effective technique for improving the speed of digital circuits operating in the subthreshold region which comes at the cost of power consumption and area. However, our experience shows that using PTS is not beneficial in all cases. In this paper, we present a methodology to identify whether using PTS is beneficial (or not) in a particular CMOS technology and what transistor sizing can be employed to maximize the circuit speed. Our technique is based on analyzing the Current-Over-Capacitance (COC) ratio of PMOS and NMOS transistors. The results of incorporating the proposed methodology in a 4-bit comparator and a 19-stage inverter ring oscillator, using 90nm CMOS technology, illustrate 26% and 40% extra improvement compared to the blind use of PTS, respectively.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.223
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2012
Admission routes1
Has abstractyes

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