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Record W2155043146 · doi:10.1109/imtc.2004.1351351

Hardware and software co-design in space compaction of cores-based digital circuits

2004· article· en· W2155043146 on OpenAlexaff
Mansour H. Assaf, S.R. Das, Emil M. Petriu, Liwu Jin, Chuan Jin, Dwaipayan Biswas, Voicu Groza, Mehmet Şahinoglu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceBenchmark (surveying)Digital electronicsEmbedded systemDesign for testingComputer architectureTestabilitySoftwareCombinational logicElectronic circuitComputer engineeringComputer hardwareReliability engineeringLogic gateEngineeringOperating system

Abstract

fetched live from OpenAlex

The implementation of a fault testing environment for embedded cores-based digital circuits is a challenging endeavor. The subject paper aims at developing techniques in design verification and test architecture, utilizing well-known concepts of hardware and software co-design. There are available methods to ensure correct functionality, in both hardware and software, for embedded cores-based systems but one of the most used and acceptable approaches to realize this is through the use of design for testability. Specifically, applications of the built-in self-test (BIST) methodology in testing embedded cores are considered in the paper, with specific implementations being targeted towards ISCAS 85 combinational benchmark circuits.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.360

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 head0.033
GPT teacher head0.252
Teacher spread0.219 · 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 designObservational
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

Citations7
Published2004
Admission routes1
Has abstractyes

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