Optimal all-to-all personalised exchange in a novel optical multistage interconnection network
Bibliographic record
Abstract
An all-to-all personalised exchange is one of the most dense collective communication operations in parallel and distributed computing and communication applications. Each node in the network needs to send a different message to each of the other nodes. Advances in electro-optic switches have made optical communication a good networking choice that can satisfy the high channel bandwidth, low communication latency, low error rate, and gigabit transmission requirements of high performance computing and communication applications. Previously proposed optical multistage interconnection networks (MINs) require at least two passes to send a message from each node to a different node (to realise a permutation) in the network. In this paper, we propose an MIN that requires only one pass to realise a permutation. That is, the new MIN requires n–1 passes instead of 2n passes, the requirement for other optical MINs, for an all-to-all personalised exchange. The new network is optimal in terms of the number of passes that is required for an all-to-all personalised exchange.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".