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META: A Layout Based Tool to Estimate the Vulnerability of Digital Circuits to Multiple Event Transient

2022· article· en· W4292070376 on OpenAlexaff
Vivek Bansal, Otmane Aı̈t Mohamed, Sowmith Nethula

Bibliographic record

Venue2022 20th IEEE Interregional NEWCAS Conference (NEWCAS) · 2022
Typearticle
Languageen
FieldEngineering
TopicRadiation Effects in Electronics
Canadian institutionsConcordia University
Fundersnot available
KeywordsTransient (computer programming)Soft errorDigital electronicsComputer scienceEvent (particle physics)Electronic circuitDesign flowSet (abstract data type)Vulnerability (computing)Satisfiability modulo theoriesElectronic design automationMixed-signal integrated circuitElectronic engineeringComputer engineeringIntegrated circuitReliability engineeringAlgorithmEngineeringEmbedded systemElectrical engineeringProgramming language

Abstract

fetched live from OpenAlex

In this paper, an Electronic Design Automation tool to estimate the vulnerability of digital circuits (META) against transient faults is presented. META analyses both single event transient (SET) and single event multiple transient (SEMT) faults considering the layout of the circuit and the fabrication technology. Unlike simulation based tool, META uses satisfiability modulo theory to calculate soft error rate of the analyzed circuits. The complete analysis flow is automated and our results outperform those obtained by simulation by a average factor of four.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.300
Teacher spread0.251 · 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
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

Citations1
Published2022
Admission routes1
Has abstractyes

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