A performance evaluation of the conservative DEVS protocol in parallel simulation of DEVS-based models
Bibliographic record
Abstract
We present the performance evaluation of the Conservative DEVS protocol. This conservative algorithm is based on the classical Chandy-Misra-Bryant (CMB) synchronization mechanism, and extends the DEVS abstract simulator by providing means for lookahead computation and null message distribution. The protocol is integrated into the CD++ simulation toolkit, providing a conservative simulator (named CCD++) for running large-scale DEVS and Cell-DEVS models in parallel and distributed fashion. Throughout the experiments, we analyze four types of metrics, the total execution time, the average blocked time per node, the average number of positive events executed on each node, and the average number of null messages per node. We show a study on three environmental Cell-DEVS models, which shows that CCD++ provides considerable speedups, showing its ability for simulating large and complex DEVS-based models. 1.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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)
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".