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Record W2096783892 · doi:10.1109/iscas.2005.1464952

Effect of Traffic Localization on Energy Dissipation in NoC-based Interconnect

2005· article· en· W2096783892 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 institutionsUniversity of British Columbia
Fundersnot available
KeywordsDissipationInterconnectionComputer scienceModular designThroughputNetwork on a chipExploitSystem on a chipEfficient energy useEmbedded systemEnergy (signal processing)Routing (electronic design automation)LocalityMultiprocessingMetric (unit)Computer architectureParallel computingComputer networkEngineeringTelecommunicationsElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

Multiprocessor system-on-chip (MP-SoC) platforms are emerging as an important trend of SoC design. Scaleable communication-centric interconnect fabrics such as networks-on-chip (NoCs) possess many features that render them particularly attractive for enabling such platforms. In particular, due to their modular structure, NoCs can exploit locality in communication and reduce the need for long global wires, thereby significantly lowering the energy dissipation without compromising system throughput. In this paper, we study the effect of traffic localization on the energy dissipation of different NoC interconnect architectures. To quantify the degree of energy savings, we introduce the energy dissipation versus throughput as a useful metric. Through system level simulation, we show that energy reductions of up to 50% can be achieved by exploiting locality in communication.

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 score0.868
Threshold uncertainty score0.302

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 head0.007
GPT teacher head0.237
Teacher spread0.230 · 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

Citations35
Published2005
Admission routes1
Has abstractyes

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