A High-Performance Scheduling Algorithm for Buffered Crossbar Switch
Bibliographic record
Abstract
The limitations in complexity and scalability of current combined input and cross-point queuing switching scheduling policies are first analyzed. To overcome the deficiencies in supporting fair and QOS scheduling, we propose a fair and simple high-performance scheduling algorithm for Combined Input-Cross-point-Queued Switches, which is called Fair Service and Group Smoothed Round Robin (FGSR). The main idea of FGSR is that it first groups flows according to their weight, then decides which group to be scheduled by SRR and finally decides which flow from the selected group to be scheduled. FGSR is based on round robin mechanism, whose complexity is only O(1). FGSR groups and schedules flows according to the weight of flows, thus it has good fairness and can adapt to the need of real-time performance. Theoretical analysis and simulation results show that FGSR exhibits good delay, throughput and anti-burst performance.
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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 | 0.002 | 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 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".