P3PO: Parallel Processing For Priority Ordering In Programmable Schedulers
Bibliographic record
Abstract
Packet schedulers enable Programmable Data-plane (PDP) switches to schedule packets correctly according to their priority. Existing PDP implementations do not support priority-based scheduling mechanisms required by scheduling policies. Push-in First-out (PIFO) offers a priority queuing abstraction; however, it faces scalability challenges due to the need for packet sorting at line-rate. To address this, approximate schedulers trade scheduling accuracy for implementation simplicity, but suffer from priority inversions. This paper presents Parallel Processing for Priority Ordering (P3PO) architecture, which partitions a global priority queue into multiple smaller, independently sorted queues that operate concurrently. P3PO is implemented using the NetBench simulator, and its performance (FCTs, delays, packet drops) is measured for in-cast traffic patterns. P3PO has FCTs close to PIFO and performs 14-62% better compared to existing approaches for small-sized flows and 47-60% better for large-sized flows. P3PO also reduces the packet drops in the network by 66-95% across different flow sizes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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".