Load Balancing for Optimistic Parallel Simulation on Multi-core Platform
Why this work is in the frame
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Bibliographic record
Abstract
For the optimistic parallel simulation implemented through multi-threading programming on the multi-core computer,though the operating system could schedule the threads so as to balance the load among cores,it can't balance the local virtual time advancement of logical processes.A four-layer load distributing model for the optimistic parallel simulation on the multi-core platform and a load balancing scheme that combined both static partitioning and dynamic load balancing were proposed.The model instances were partitioned using a graph partitioning package called Metis in the static partitioning,while the logical processes with a lower local virtual time were given higher priority to be scheduled in the dynamic load balancing scheme.The dynamic load scheme need not migrate model instances,and is easier to implement.The effect of the proposed load balancing scheme was verified through a series of experiments.
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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 | 0.002 |
| 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 | 0.001 |
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 it