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Record W1615606959 · doi:10.1109/iscas.2006.1693227

A High-Speed Low-Energy Dynamic PLA Using an Input-Isolation Scheme

2006· article· en· W1615606959 on OpenAlexaff
Reza Molavi, Shahriar Mirabbasi, R. Saleh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCMOSApplication-specific integrated circuitPower–delay productComputer scienceIsolation (microbiology)Logic gateElectronic engineeringScheme (mathematics)Dynamic demandEnergy consumptionEnergy (signal processing)Power consumptionArchitectureEmbedded systemDynamic logic (digital electronics)Power (physics)EngineeringElectrical engineeringAdderTransistorVoltageMathematics

Abstract

fetched live from OpenAlex

Recently, there has been renewed interest in structured logic arrays due to a number of inherent advantages. However, before they will be more widely adopted, structured logic arrays must be able to compete with standard ASIC designs. This paper proposes a CMOS PLA based on a dynamic NOR architecture that uses an input-isolation technique along with a latch-based sense amplifier to achieve both high operating speed and low-energy consumption. The proposed architecture is designed and simulated in a 0.18mum CMOS technology. It improves the delay by 10% compared with the fastest reported PLA. It also achieves the lowest power-delay product of all other reported dynamic PLAs

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.232
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations4
Published2006
Admission routes1
Has abstractyes

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