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Record W2982075356 · doi:10.1109/iceaa.2019.8879172

Efficient Electromagnetic Modeling of On-Chip Interconnects with a Hybrid 2D-3D Differential Surface Admittance Approach

2019· article· en· W2982075356 on OpenAlexaff
Shashwat Sharma, Piero Triverio

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsElectrical conductorInterconnectionSkin effectDiscretizationElectronic engineeringAdmittanceComputer scienceSignal integrityChipElectromagnetic field solverPrinted circuit boardComputational electromagneticsFinite element methodElectromagnetic fieldPhysicsElectrical engineeringEngineeringElectrical impedanceTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

Full-wave electromagnetic simulation is a crucial yet challenging step in the design of on-chip interconnect networks. Accurate characterization of signal propagation and crosstalk requires modeling skin effect inside lossy conductors, as well as electromagnetic coupling between conductors. Volume-based techniques such as the finite element method are computationally expensive at high frequencies, due to the need for an extremely fine mesh within conductors. Although surface integral equation methods reduce the dimensionality of the problem by requiring only a surface discretization of the conductors [1], simulating modern interconnect networks of increasing size and intricacy still poses a significant computational challenge.

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: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.746

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)0.0010.000

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 head0.006
GPT teacher head0.193
Teacher spread0.188 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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