Development of Stencil-Based Mesh Partitioning for Parallel Unstructured CFD Solvers
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Bibliographic record
Abstract
A study evaluating unstructured mesh partitioning for computational uid dynamics (CFD) simulations on parallel computers is presented. Considerations for eectiv e partitioning of computational unstructured meshes for a family of implicit time-integration methods using the line-relaxation algorithm are outlined. Mesh partitioning using the Metis library is evaluated for two- and three-dimensional meshes. Dieren t combinations of computational stencil information provided to the partitioning library are outlined and comparison of the resulted load balance and communication volume measures are presented. An augmentation to the existing mesh partitioning method via a heuristic algorithm is proposed. The heuristic algorithm relies on an initial partitioning of the mesh, which is then rened iteratively. Results using the new method are compared with the standard partitioning methods. This is done both from a theoretical perspective and by running the CFD code. Elapsed time results of the CFD code are presented from simulations on a parallel computer. Results show that the improved partitioning using the stencil information and the heuristic algorithm result in faster turn-around times. The stencil-based partitioning and the proposed heuristic algorithm are simple modications to existing codes and are applicable to general simulations employing domain decomposition.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it