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Record W1986921363 · doi:10.1504/ijhpcn.2005.007863

Optimal all-to-all personalised exchange in a novel optical multistage interconnection network

2005· article· en· W1986921363 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of High Performance Computing and Networking · 2005
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsComputer scienceComputer networkGigabitNode (physics)InterconnectionLow latency (capital markets)Bandwidth (computing)Multistage interconnection networksDistributed computingLatency (audio)Transmission (telecommunications)Telecommunications

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.277
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it