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Record W2515101082 · doi:10.1109/iscas.2016.7527472

Memristor-based 4:2 compressor cells design

2016· article· en· W2515101082 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
KeywordsMemristorMemistorBottleneckCMOSComputer scienceScalabilityVon Neumann architectureResistive random-access memoryGas compressorElectronic engineeringElectronic circuitComputer architectureElectrical engineeringEmbedded systemEngineeringVoltage

Abstract

fetched live from OpenAlex

Memristor-based arithmetic circuits promise new alternatives for their conventional CMOS-based peers due to memristor' s scalability and non-volatility features. In-memory memristor-based calculations become extensively attractive as it can be a solution to tackle memory bottleneck problems and also an ingredient for future beyond Von-Neumann computer architectures. In this paper material implication-based designs for 4:2 compressor cells using memristor devices are presented. A physical model is applied to determine real switching speed of memristive device. The proposed parallel design promises good speed performance with considerably less area than conventional CMOS designs. Finally a comparison has been made between the proposed memristor-based and CMOS-based designs in terms of number of applied devices per cell and delay.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.211

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 head0.026
GPT teacher head0.203
Teacher spread0.178 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

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