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Record W2005309768 · doi:10.1049/el.2013.2320

Improved design of high‐frequency sequential decimal multipliers

2014· article· en· W2005309768 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 · 2014
Typearticle
Languageen
FieldComputer Science
TopicNumerical Methods and Algorithms
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDecimalArithmeticComputer scienceMathematicsElectronic engineeringEngineering

Abstract

fetched live from OpenAlex

Hardware implementation of decimal arithmetic operations has become a hot topic for research during the last decade. Among various operations, decimal multiplication is considered as one of the most complicated dyadic operations, which requires high‐cost hardware implementation. Therefore, the processor industry has opted to use the sequential decimal multipliers to reduce the high cost of parallel architectures. However, the main drawback of iterative multipliers is their high latency. In this reported work, the focus has been on reducing the latency of decimal sequential multipliers while maintaining a low cost of area. Consequently, a high‐frequency sequential decimal multiplier is proposed whose cycle time is reduced to the latency of a binary half‐adder plus that of a decimal multiply‐by‐two operation, which overall is less than that of a decimal carry‐save adder. The synthesis results reveal that the proposed sequential multiplier works with a higher clock frequency than the fastest previous decimal multiplier which in turn leads to overall latency advantage.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.625
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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