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Record W2098038030 · doi:10.1109/newcas.2006.250915

RoC: A Scalable Network on Chip Based on the Token Ring Concept

2006· article· en· W2098038030 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsSTMicroelectronics (Canada)Polytechnique Montréal
Fundersnot available
KeywordsComputer scienceScalabilityComputer networkInterconnectionMultiprocessingToken ringNetwork on a chipNetwork packetEmbedded systemRing networkSecurity tokenChipComputer architectureDistributed computingNetwork topologyOperating systemTelecommunications

Abstract

fetched live from OpenAlex

A recent practice in the development of SoCs is the integration of interconnect networks, since integration offers significant bandwidth increases. This allows implementing multiprocessor systems that communicate more effectively than bus based architectures. This paper proposes a rotator-on-chip (RoC) architecture as a new network-on-chip based on the token ring concept. This scalable network has been integrated into a system level exploration platform for characterization. Increased performance is confirmed and improvements are proposed to decrease packet latency through the network. Results show that the RoC supports a working load of 82%, compared to 58% for the hot potato mesh network and 28% for the SPIN fat tree network

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.279

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)0.0000.000

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 head0.013
GPT teacher head0.204
Teacher spread0.192 · 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

Quick stats

Citations5
Published2006
Admission routes1
Has abstractyes

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