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Record W2025747518 · doi:10.1155/2013/454392

Ultra-Low Leakage Arithmetic Circuits Using Symmetric and Asymmetric FinFETs

2013· article· en· W2025747518 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Electrical and Computer Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsAdderLeakage (economics)Topology (electrical circuits)Electronic circuitNetwork topologyTransistorElectronic engineeringGas compressorReduction (mathematics)Computer scienceElectrical engineeringMathematicsEngineeringCMOSVoltage

Abstract

fetched live from OpenAlex

We are examining different configurations and circuit topologies for arithmetic components such as adder and compressor circuits using both symmetric and asymmetric work-function FinFETs. Based on extensive characterization data, for the carry generation of a mirror full adder using symmetric devices, both leakage current and delay are decreased by 25% and 50%, respectively, compared to results in the literature. For the 14-transistor (14T) full adder topology, both leakage and delay are decreased by 23% and 29%, respectively, compared to the mirror topology. The 14T adder topology, using asymmetric devices without any additional power supply, achives reduction in leakage current by 85% with a small degradation of 7% in delay. The compressor circuits, using asymmetric devices for one of the proposed configurations, achieve reduction in both leakage current and delay by 86% and 4%, respectively. All simulations are based on a 25 nm FinFET technology using the University of Florida UFDG model.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.168
Teacher spread0.162 · 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