MétaCan
Menu
Back to cohort
Record W1556756884 · doi:10.1109/isqed.2005.21

Analysis of Wave-Pipelined Domino Logic Circuit and Clocking Styles Subject to Parametric Variations

2005· article· en· W1556756884 on OpenAlexafffund
Wei Ling, Yvon Savaria

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsPolytechnique Montréal
FundersCMC Microsystems
KeywordsDominoDomino logicPipeline (software)Computer scienceParametric statisticsLogic gateElectronic circuitBlocking (statistics)Electronic engineeringLogic synthesisSequential logicLogic familyElectrical engineeringAlgorithmEngineeringMathematics

Abstract

fetched live from OpenAlex

In recent years, wave-pipelined domino logic has received much attention as a means to implement high-speed circuits. However, this logic is vulnerable to parametric variations and the situation will degrade as technology scales down. In this paper, statistical timing relations are developed for characterizing performance impacts of parametric variations in different wave-pipelined domino circuits and clocking styles. Analytic results show that a wave pipeline built with a footless nonblocking domino cell accumulates timing variations due to parametric variation along the pipeline. Thus performance reduces with pipeline size as variations accumulate. On the other hand, wave pipelined footed blocking domino logic is less sensitive to parametric variations. Simulation results of a 6-stage wave pipeline using footed blocking domino cells in 130 nm technology also demonstrate the advantages of this logic style both in performance and power consumption.

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 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: Empirical
Teacher disagreement score0.272
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
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 head0.021
GPT teacher head0.226
Teacher spread0.205 · 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 teacher head, 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

Citations2
Published2005
Admission routes2
Has abstractyes

Explore more

Same topicLow-power high-performance VLSI designFrench-language works237,207