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Record W2082450393 · doi:10.1049/iet-cds.2008.0331

High-speed hardware implementation of a serial-in parallel-out finite field multiplier using reordered normal basis

2010· article· en· W2082450393 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

VenueIET Circuits Devices & Systems · 2010
Typearticle
Languageen
FieldComputer Science
TopicCryptography and Residue Arithmetic
Canadian institutionsUniversity of Windsor
FundersCMC Microsystems
KeywordsNormal basisMultiplier (economics)Elliptic curve cryptographyFinite fieldDomino logicNISTArithmeticComputer scienceClock rateVery-large-scale integrationParallel computingMathematicsComputer hardwareAlgorithmLogic synthesisDiscrete mathematicsGalois theoryChipEmbedded systemLogic gateEncryption

Abstract

fetched live from OpenAlex

A high-speed VLSI implementation of a 233-bit serial-in parallel-out finite field multiplier is presented. The proposed design performs multiplication using a reordered normal basis; a permutation of a type II optimal normal basis. The multiplier was realised in a 0.18-µm CMOS technology using multiples of a domino logic block. The multiplier was simulated, and functioned correctly up to a clock rate of 1.587 GHz, achieving greater performance while occupying less area compared to similar designs. The presented design methodology can also be used for other finite field multipliers possessing regular architectures. This multiplier's size of 233 bits is currently recommended by the National Institute of Standards and Technology (NIST) in their elliptic curve digital signature standard (ECDSS), and is used in practice for binary field multiplication in Elliptic Curve Cryptography (ECC).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.272
Teacher spread0.253 · 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