MétaCan
Menu
Back to cohort
Record W2110678168 · doi:10.1145/1531542.1531658

Reliability aware NoC router architecture using input channel buffer sharing

2009· article· en· W2110678168 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 institutionsMcGill University
Fundersnot available
KeywordsRouterVirtual channelNetwork on a chipComputer scienceComputer networkNetwork packetLatency (audio)TransposeOne-armed routerReliability (semiconductor)Channel (broadcasting)

Abstract

fetched live from OpenAlex

To address the increasing demand for reliability in on-chip networks, we proposed a novel Reliability Aware Virtual channel (RAVC) NoC router micro-architecture that enables both dynamic virtual channel allocations and the rational sharing among the buffers of different input channels. In particular, in the case of failure in routers, the virtual channels of routers surrounding the faulty routers can be totally recaptured and reassigned to other input ports. Moreover, our proposed RAVC router isolates the faulty router from occupying network bandwidth. Experimental result shows that proposed micro-architecture provides 7.1% and 3.1 % average latency decrease under uniform and transpose traffic pattern. Considering the existence of failures in routers of on-chip network, RAVC provides 28% and 16% decrease in the average packet latency under the uniform and transpose traffic pattern respectively.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score0.494

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 science0.0010.000
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 head0.024
GPT teacher head0.254
Teacher spread0.231 · 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

Citations49
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicInterconnection Networks and SystemsFrench-language works237,207