Déploiement à la volée de réseaux d'acteurs dataflow dynamiques sur plateforme multiprocesseurs hétérogène
Bibliographic record
Abstract
Dans ce papier, nous presentons un algorithme de deploiement d'un reseau d'acteurs dataflow dynamiques sur une plate-forme multiprocesseurs heterogenes. En plus de prendre en compte les temps d'execution des acteurs, notre algorithme repose sur un modele de communication pour estimer le delai de transmission des donnees. L'algorithme est compare avec l'outil METIS pour plusieurs reseaux d'acteurs generes aleatoirement et deux decodeurs video, MPEG4-SP et HEVC, deployes sur des plates-formes multiprocesseurs heterogenes composees de 4 a 8 processeurs et 6 accelerateurs. Les resultats sur une plate-forme Zynq montrent que notre algorithme est environ 40 fois plus rapide que METIS pour un meme debit video sur une plate-forme avec 8 processeurs et 6 accelerateurs.
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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 | 0.017 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".