Scalable architecture and low-latency scheduling schemes for next generation photonic datacenters
Bibliographic record
Abstract
Photonic packet switches potentially provide high switching capacity for next-generation datacenters at low cost, low power, and low footprint. In this paper, we address the scalability and packet scheduling for intra-connectivity of next generation photonic datacenters. We first propose a scalable photonic packet fabric based on a stack of small buffer-less silicon photonic switches which are timeslot synchronized by a central controller. We introduce a photonic fabric interface which offers both data path connectivity to the photonic fabric and control path connectivity to the controller. Then, we present centralized scheduling and control methods for photonic packet switching. Our scheduling methods are low complexity iterative algorithms equipped with starvation avoidance capability to meet the latency requirement for packet transmission through the photonic fabric. Simulation results indicate that our scalable scheduling schemes are capable of controlling average and maximum end-to-end packet delay for intra-connectivity in next generation datacenters which are based on buffer-less photonic switching fabrics.
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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 | 0.000 | 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".