Parallel Hierarchical Tetrahedral-Octahedral Subdivision Mesh Refinement: Performance Modeling, Simulation and Validation
Bibliographic record
Abstract
Designing parallel finite element methods is a complex task that can benefit by simulating models of them first. However, such simulations are useful only if they can accurately predict the performance of the parallel system being modeled. We have developed an approach utilizing Petri nets (PN) for modeling and simulating hierarchical tetrahedral-octahedral (HTO) subdivision in parallel 3-D unstructured mesh refinement. A model is implemented based on a detailed software prototype and parallel system architecture parameters, and simulates the behavior of the algorithm. Subsequently, estimates for performance measures are derived from the simulations. The potential benefits of this approach for developing high performance parallel mesh refinement algorithms are validated with MPI benchmark results obtained using McGill University's CLUMEQ Supercomputer Centre facilities
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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)
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".