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Low Power Memristor-Based Shift Register Design

2020· article· en· W3114847385 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMemristorCMOSShift registerMemistorComputer scienceElectronic engineeringTransistorResistive random-access memoryElectrical engineeringEngineeringTelecommunicationsVoltageChip

Abstract

fetched live from OpenAlex

The use of memristors is considered to be an appropriate alternative solution to Complementary Metal Oxide Semiconductor (CMOS) technology's scaling limitation. In digital design, shift registers are widely used and considered to be basic memory devices. In this paper, a fast and efficient area memristor-only-based shift register, as well as a hybrid CMOS/memristor-based shift register are proposed. Specifically, a 4-bit shift register with only 8 memristor devices and a hybrid CMOS /memristor with 64 memristor devices and 64 CMOS transistors were implemented and simulated using Cadence Virtuoso. The simulation results demonstrate the design's efficient functionality. Compared to the implementation of a CMOS-memristor based shift register, the implementation of the proposed design is more efficient when concerning area and speed with respect to the implementation of the Memristor Based-Material-Implication (IMPLY) memristive shift register. In addition, the shift register with only memristor-based has a significant power reduction of over 30% compared to a CMOS design shift register.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.964
Threshold uncertainty score0.368

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 head0.036
GPT teacher head0.220
Teacher spread0.183 · 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

Quick stats

Citations9
Published2020
Admission routes1
Has abstractyes

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