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Record W2062406289 · doi:10.1109/cjece.2003.1426068

Low-power single-bit full adder cells

2003· article· en· W2062406289 on OpenAlexafffundvenue
Arash Shoarinejad, S.A. Ung, Wael Badawy

Bibliographic record

VenueCanadian Journal of Electrical and Computer Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Calgary
KeywordsAdderCMOSSerial binary adderComputer scienceElectronic engineeringCarry-save adderLogic gatePower (physics)ArithmeticComputer hardwareElectrical engineeringEngineeringMathematicsPhysics

Abstract

fetched live from OpenAlex

The single-bit full adder is one of the main components in almost all logic structures. The performance of logic structures is highly dependent on the adder cells. This paper discusses the performance of single-bit full adders and presents a performance analysis for those cells in CMOS technology. Fourteen single-bit full adders and three new adders, a total of different adder cells, are analyzed in terms of power and delay using 0.35, 0.25 and 0.18 µm TSMC CMOS technology. In addition, this paper discusses the charging-capability parameter of the adder cells, which represents the fan-out of each cell. The charging-capability parameter is capable of describing the performance of the adder cell in a large, as yet unbuilt structure. Hence, the performance analysis of the single-bit full adder relates the design to power, delay, and charging capability of the logic components.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.004
GPT teacher head0.134
Teacher spread0.131 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2003
Admission routes3
Has abstractyes

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