Bounding buffer space requirements for real-time priority-aware networks
Why this work is in the frame
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Bibliographic record
Abstract
One implementation alternative for network interconnects in modern chip-multiprocessor systems is priority-aware arbitration networks. To enable the deployment of real-time applications to priority-aware networks, recent research proposes worst-case latency (WCL) analyses for such networks. Buffer space requirements in priority-aware networks, however, are seldom addressed. In this work, we bound the buffer space required for valid WCL analyses and consequently optimize router design for application specifications by computing the required buffer space at each virtual channel in priority-aware routers. In addition to the obvious advantage of bounding buffer space while providing valid WCL bounds, buffer space reduction decreases chip area and saves energy in priority-aware networks. Our experiments show that the proposed buffer space computation reduces the number of unfeasible implementations by 42% compared to an existing buffer space analysis technique. It also reduces the required buffer space in priority-aware routers by up to 79%.
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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 | 0.000 |
| 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 | 0.000 |
| 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