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Compact thermal model for microprocessor package based on one-dimensional thermal network with average temperature nodes

2015· article· en· W1832894156 on OpenAlexaff
Koji Nishi, Tomoyuki Hatakeyama, Shinji Nakagawa, Masaru Ishizuka

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsHeat sinkMicroprocessorThermal conductionThermalIsothermal processInterconnectionResistorThermal resistanceMaterials scienceSiliconMechanical engineeringThermal conductivityComputer scienceElectronic engineeringEngineeringElectrical engineeringThermodynamicsPhysicsOptoelectronicsComposite materialTelecommunications

Abstract

fetched live from OpenAlex

This paper proposes a new compact thermal model (CTM) for the microprocessor package based on a one-dimensional thermal network with average temperature nodes. Different from the two-resistor model and the DELPHI model, the proposed CTM doesn't assume an isothermal surface, but sets plate heat sources along the top surface of the silicon die and the bottom surface of the solder balls layer. It is found that the temperature prediction result by a thermal network with the proposed CTM matches the three-dimensional heat conduction simulation result closely through a numerical experiment of a microprocessor system with a heat sink fan.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.510
Threshold uncertainty score0.585

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 head0.019
GPT teacher head0.212
Teacher spread0.193 · 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 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
Published2015
Admission routes1
Has abstractyes

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