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Record W4242199054 · doi:10.1109/dac.2003.1219139

Statistical estimation of leakage-induced power grid voltage drop considering within-die process variations

2004· article· en· W4242199054 on OpenAlex
I.A. Ferzli, F.N. Najm

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings 2003. Design Automation Conference (IEEE Cat. No.03CH37451) · 2004
Typearticle
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDie (integrated circuit)Power gridVoltageVoltage dropLeakage (economics)GridLeakage powerComputer scienceEnvironmental scienceElectrical engineeringElectronic engineeringPower (physics)EngineeringMechanical engineeringTransistorMathematicsPhysics

Abstract

fetched live from OpenAlex

Transistor threshold voltages Vth have been reduced as part of on-going technology scaling. The smaller Vth values feature increased fluctuations due to process variations, with a strong within-die component. Correspondingly, given the exponential dependence of leakage on.Vth, circuit leakage currents are increasing significantly and have strong within-die statistical variations. With these currents loading the power grid, the grid develops large voltage drops, which is an unavoidable background level of noise on the grid. We develop techniques for estimation of the statistics of the leakage-induced power grid voltage drop based on given statistics of the circuit leakage currents.

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.

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)0.004
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 score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
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 head0.043
GPT teacher head0.277
Teacher spread0.233 · 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