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Record W2167845685 · doi:10.1109/tc.2015.2401024

Comments on “Low-Latency Digit-Serial Systolic Double Basis Multiplier over $GF(2^{m})$ Using Subquadratic Toeplitz Matrix-Vector Product Approach”

2015· article· en· W2167845685 on OpenAlexafffund
Arash Reyhani-Masoleh

Bibliographic record

VenueIEEE Transactions on Computers · 2015
Typearticle
Languageen
FieldComputer Science
TopicCoding theory and cryptography
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsToeplitz matrixArithmeticMatrix multiplicationMultiplier (economics)Computer scienceMultiplication (music)Numerical digitLatency (audio)Parallel computingGF(2)Basis (linear algebra)MathematicsAlgorithmDiscrete mathematicsCombinatoricsFinite fieldPure mathematicsTelecommunications

Abstract

fetched live from OpenAlex

The digit-serial systolic double basis multiplier architecture proposed in the above paper does not generate the correct multiplication results as it requires more latches to process digits of inputs in appropriate clock cycles. In this comment, we present the corrected architecture and obtain its time and area complexities. More importantly, we show that the claims made by the authors regarding having significantly lower time and area complexities than its counterpart are not valid.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.764
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.047
GPT teacher head0.272
Teacher spread0.225 · 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 designSimulation or modeling
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

Citations5
Published2015
Admission routes2
Has abstractyes

Explore more

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