Adaptive packet switch with an optical core (demonstrator)
Bibliographic record
Abstract
In this paper, a three-stage packet switch architecture is implemented consisting of a reconfigurable optical center stage surrounded by two electronic buffering stages grouped into sectors to ease contention. A Flexible Bandwidth Provision algorithm is used to change the configuration of the optical center stage to form the requested bandwidth desired by incoming traffic. The switch is modeled by a bipartite graph built from the service matrix. The bipartite graph is decomposed by solving an edge-coloring problem and the resulting permutations are used to configure the central stage removing the requirement for a per-time slot scheduler. Flexible Bandwidth Provision (FBP) algorithm requires dynamically reconfigurable technology readily available in programmable logic devices. The designed packet switch being a collection of discrete entities is most easily implemented on separate programmable logic devices forming electronic “islands” interconnected by photonics technology. The demonstrator itself contains 64 inputs and 64 outputs with reconfigurable central stage crossbars. The switch is a collection of input and output sectors each implemented on a single FPGA. Each sector is an 8 x 8 sub-switch with shared buffer memory. The interface between the sectors and the central stage will use VCSEL technology for O-E-O conversion. The input sectors together with the central stage form the adaptive portion of the switch configured by an embedded soft-core processor implementing the FBP algorithm of which is entity are located on an Ethernet local area network. This switching architecture has also been simulated and results show that this architecture result in a dramatic reduction of complexity, at the price of only a modest spatial speed-up (<2).
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 | 0.001 | 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 | 0.001 |
| Open science | 0.002 | 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".