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Record W2013961570 · doi:10.1109/icecs.2012.6463517

Power efficiency of digit level polynomial basis finite field multipliers in GF(2<sup>283</sup>)

2012· article· en· W2013961570 on OpenAlexaff
Shoaleh Hashemi Namin, Huapeng Wu, Majid Ahmadi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCoding theory and cryptography
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsFinite fieldVery-large-scale integrationElliptic curve cryptographyGF(2)Multiplier (economics)Critical path methodComputer scienceField (mathematics)ArithmeticMathematicsAlgorithmDiscrete mathematicsEmbedded systemEngineeringEncryptionPublic-key cryptographyPure mathematics

Abstract

fetched live from OpenAlex

Several digit level finite field multiplier architectures have been proposed in the literature. Some of them are with power estimation with different VLSI technology for different field sizes which makes it difficult to compare their power efficiency. In this paper, we perform VLSI simulation for several existing digit level field multipliers in the same field, GF(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">283</sup> ), and with the same 0.18μm VLSI technology so that an effective comparison of their power efficiency along with other IC features such as area and critical path delay can be made. Recommendations of the most efficient finite field multiplier are given for the different application constraints. Detailed discussion is provided for power constrained mobile and wireless applications. The comparison results obtained in this paper are expected to be useful for those who design and/or implement elliptic curve cryptography for wireless and portable systems.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.231
Teacher spread0.213 · 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 designTheoretical or conceptual
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

Citations3
Published2012
Admission routes1
Has abstractyes

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