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Record W4231097844 · doi:10.1109/aspdac.2005.1466550

Register-transfer level functional scan for hierarchical designs

2005· article· en· W4231097844 on OpenAlexaff
Ho Fai Ko, Qiang Xu, N. Nicolici

Bibliographic record

VenueProceedings of the ASP-DAC 2005. Asia and South Pacific Design Automation Conference, 2005. · 2005
Typearticle
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRegister-transfer levelScan chainDesign for testingComputer scienceAbstractionTestabilityTransfer (computing)Shift registerHigh-level synthesisRegister (sociolinguistics)Logic synthesisParallel computingComputer architectureLogic gateEmbedded systemReliability engineeringAlgorithmIntegrated circuitEngineeringField-programmable gate array

Abstract

fetched live from OpenAlex

This paper discusses the potential benefits of inserting scan chains (SCs) in hierarchical designs at the register-transfer level (RTL) of design abstraction. Using new algorithms for functional scan chain design, it is shown how tight timing constraints for design-for-test (DFT) planning at RTL can improve the performance of a circuit, when compared to its gate level counterpart, without any loss in testability.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.089
GPT teacher head0.247
Teacher spread0.158 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2005
Admission routes1
Has abstractyes

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