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Record W2364718996

Parallel computation of a high-order discontinuous Galerkin method on unstructured grids

2011· article· en· W2364718996 on OpenAlexaboutno aff
Song Jiang-yong

Bibliographic record

VenueKongqi donglixue xuebao · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsnot available
Fundersnot available
KeywordsDiscontinuous Galerkin methodEuler equationsSpeedupConvergence (economics)Applied mathematicsComputationRate of convergenceBackward Euler methodMathematicsComputer scienceParallel computingFinite element methodAlgorithmMathematical analysisPhysics
DOInot available

Abstract

fetched live from OpenAlex

Based on the METIS mesh partition technique,a parallel high-order Discontinuous Galerkin(DG) method is developed for the solution of the 2D Euler equations on unstructured grids.The developed parallel method is used to compute the compressible flows for test problems of different scales.The numerical flux of Euler equations is calculated by using Local Lax-Friedrichs(LLF) scheme;and a parallel Newton-Block GS method is devised to accelerate convergence.The numerical results obtained show that it has rapid convergence rate and solution of high accuracy.The performance analysis indicates that it has satisfying speedup and parallel efficiency.Overall,the parallel high-order DG method is proved to reduce computational time dramatically and allocate memory reasonably,which makes it promising to compute more complex problems.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.031
GPT teacher head0.287
Teacher spread0.256 · 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
GenreMethods

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
Published2011
Admission routes1
Has abstractyes

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