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Record W7006122241

Single event transient modeling and mitigation techniques for mixed-signal delay locked loop (DLL) and clock circuits

2014· dissertation· en· W7006122241 on OpenAlexfundno aff

Bibliographic record

VenueDiscover Archive (Vanderbilt University) · 2014
Typedissertation
Languageen
FieldEngineering
TopicRadiation Effects in Electronics
Canadian institutionsnot available
FundersDefense Threat Reduction AgencyInnovation, Science and Economic Development CanadaVanderbilt University
KeywordsJitterClock domain crossingElectronic circuitTiming failureSynchronous circuitDigital clock managerClock driftClock signalClock skewClock gating
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this PhD work has been to investigate, model, test, develop and provide hardening techniques and guidelines for the mitigation of single event transients (SETs) in analog mixed-signal (AMS) delay locked loops (DLLs) for radiation-hardened applications.Delay-locked-loops (DLLs) are circuit substructures that are present in complex ASIC and system-on-a-chip designs.These circuits are widely used in on-chip clock distribution systems to reduce clock skew, to reduce jitter noise, and to recover clock signals at regional points within a global clock distribution system.DLLs are critical to the performance of many clock distribution systems, and in turn, the overall performance of the associated integrated system; as such, complex systems often employ multiple DLLs for clock deskew and distribution tasks.In radiation environments such as on-orbit, these critical circuits represent at-risk points of malfunction for large sections of integrated circuits due to vulnerabilities to radiation-generated transients (i.e.single event transients) that fan out across the system.

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 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: none
Teacher disagreement score0.597
Threshold uncertainty score1.000

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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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