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Record W4242994262 · doi:10.7873/date.2013.283

Explicit Transient Thermal Simulation of Liquid-Cooled 3D ICs

2013· article· en· W4242994262 on OpenAlexaff
Alain Fourmigue, Giovanni Beltrame, Gabriela Nicolescu

Bibliographic record

VenueDesign, Automation & Test in Europe Conference & Exhibition (DATE), 2013 · 2013
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsOverheating (electricity)Computer coolingTransient (computer programming)ThermalThermal management of electronic devices and systemsThree-dimensional integrated circuitDissipationHeat sinkComputer scienceElectronic circuitHeat fluxMechanical engineeringIntegrated circuitMaterials scienceNuclear engineeringElectronic engineeringHeat transferMechanicsEngineeringElectrical engineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

The high heat flux and compact structure of three-dimensional circuits (3D ICs) make conventional air-cooled devices more subsceptible to overheating. Liquid cooling is an alternative that can improve heat dissipation, and reduce thermal issues. Fast and accurate thermal models are needed to appropriately dimension the cooling system at design time. Several models have been proposed to study different designs, but generally with low simulation performance. In this paper, we present an efficient model of the transient thermal behaviour of liquid-cooled 3D ICs. In our experiments, our approach is 60 times faster and uses 600 times less memory than state-of-the-art models, while maintaining the same level of accuracy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.044
GPT teacher head0.250
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2013
Admission routes1
Has abstractyes

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Same venueDesign, Automation & Test in Europe Conference & Exhibition (DATE), 2013Same topicHeat Transfer and OptimizationFrench-language works237,207