MétaCan
Menu
Back to cohort
Record W1896247917 · doi:10.1109/icc.1996.535296

A growable large scale ATM multicast switch

2002· article· en· W1896247917 on OpenAlexaff
K. L. Eddie Law, Alberto Leon‐Garcia

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsUniversity of TorontoNortel (Canada)
Fundersnot available
KeywordsMulticastComputer scienceScalabilityComputer networkThroughputAsynchronous Transfer ModeRouting (electronic design automation)Distributed computingQueueing theorySortingCrossover switchInterconnectionMultistage interconnection networksTelecommunications

Abstract

fetched live from OpenAlex

This paper focuses on designing a large N/spl times/N high performance, broadband ATM switch. Despite advances in architectural designs, practical switch dimensions continue to be severely limited by both the technological and physical constraints of packaging. Here, we focus on augmentation in a "single-switch" design: we provide ways to construct arbitrarily large switches out of modest-size components and retain overall delay/throughput performance. We propose a growable switch architecture based on several key principles: (1) the knockout principle exploits the statistical behavior of cell arrivals and thereby reduces the interconnect complexity, (2) output queueing yields the best possible delay/throughput performance, (3) distributed control in routing (multicast) cells through the interconnect fabric without internal path conflicts and (4) simple basic building blocks facilitate scalability. Other attractive features of the proposed architecture include: (1) intrinsic broadcast and multicast capabilities, (2) built-in priority sorting functionality and (3) the guarantee of first-in-first-out cell sequence. To achieve 10/sup -14/ cell loss probability, only maximum-size 32/spl times/16 basic building modules are required, and no cross-over interconnects exist between modules in a three-dimensional configuration.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.019
GPT teacher head0.215
Teacher spread0.196 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicInterconnection Networks and SystemsFrench-language works237,207