Simulation-based Schedulability Assessment for Real-Time Systems
Why this work is in the frame
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Bibliographic record
Abstract
Real-time systems not only require functional correctness, but also specific timing properties. Correct timing is especially challenging for hard real-time systems such as in medicine, avionics, and space industries, where missing a deadline can lead to catastrophic failure. A number of theories tackled this issue to determine whether a set of tasks running on a given architecture meets its timing constraints. One technique is schedulability analysis, which can provide guarantees for the timing behavior for a set of tasks. However, the use of schedulability tests involve an intrinsic amount of pessimism, which greatly reduces the number of configurations that can be considered as schedulable. This removes potentially promising system configurations from the task allocation optimization process, thereby reducing the quality of the final result. The aim of this paper is to overcome this limitation in the context of heterogeneous multiprocessor architectures. We propose a simulation-based approach to assess solutions discarded by a schedulability test, and include them in the optimization process. We tested our method on the optimization of the communication cost of a set of tasks scheduled on a quad core architecture, showing an improvement of up 11% when compared to the use of a schedulability test.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 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 it