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Record W4327738655 · doi:10.1142/s0218126623502596

A Memristive-Based Design of a Core Digital Circuit for Elliptic Curve Cryptography

2023· article· en· W4327738655 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.

Bibliographic record

VenueJournal of Circuits Systems and Computers · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsCarleton UniversityUniversity of Windsor
Fundersnot available
KeywordsMemristorCMOSComputer scienceElliptic curve cryptographyMemistorElectronic engineeringDiode-or circuitCircuit designTransistorEmbedded systemElectrical engineeringComputer hardwareEngineeringDiscrete circuitResistive random-access memoryEncryptionPublic-key cryptography

Abstract

fetched live from OpenAlex

The new emerging non-volatile memory (NVM) devices known as memristors could be the promising candidate for future digital architecture, owing to their nanoscale size and its ability to integrate with the existing CMOS technology. The device has involved in various applications from memory design to analog and digital circuit design. In this paper, a combination of memristor devices and CMOS transistors is working together to form a hybrid CMOS-memristor circuit for XAX- Module, a core element used as digital circuit for elliptic curve cryptography. The proposed design was implemented using Pt/TaOx/Ta memristor device and simulated in Cadence Virtuoso. The simulation results demonstrate the design functionality. The proposed module appears to be efficient in terms of layout area, delay and power consumption since the design utilizes the hybrid CMOS/memristor gates.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.759
Threshold uncertainty score0.537

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 science0.0000.000
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 head0.057
GPT teacher head0.246
Teacher spread0.189 · 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