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Record W2246496525 · doi:10.1049/el.2015.0786

Area and power efficient decimal carry‐free adder

2015· article· en· W2246496525 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueElectronics Letters · 2015
Typearticle
Languageen
FieldComputer Science
TopicNumerical Methods and Algorithms
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAdderCarry (investment)ArithmeticDecimalCarry-save adderSerial binary adderPower (physics)Computer scienceMathematicsTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

As decimal floating‐point (DFP) is better than binary floating‐point in commercial and financial computing including billing systems, currency conversion, tax calculation and banking, many research activities have been focused on improving the performance of the DFP arithmetic unit recently. To achieve the high performance of the DFP arithmetic unit, a fast decimal fixed‐point adder is the most important building block. The conventional three steps carry‐free signed digit (SD) addition algorithm is first investigated. A new method for the decimal SD addition and subtraction based on the digit set [−9, 9] is proposed. Additionally, a digit‐set converter which can directly generate the absolute value of the result is proposed. A model of the proposed decimal SD adder is implemented in VHDL. After exhaustive tests to ensure the correctness, the proposed design was synthesised in STM 90 nm technology. The results show that the proposed adder has a lower power and area consumption compared with previous designs.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.473
Threshold uncertainty score0.485

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 communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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