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Record W1978745493 · doi:10.1109/ccece.2008.4564695

High-level specification and logic implementation of single-chip multiprocessor systems based on a configurable router

2008· article· en· W1978745493 on OpenAlexafffundvenue
Ronny Pau, Naraig Manjikian

Bibliographic record

VenueConference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceRouterMultiprocessingStratixNetwork on a chipEmbedded systemSystem on a chipField-programmable gate arrayNetwork topologyParallel computingComputer network

Abstract

fetched live from OpenAlex

This paper describes prototype implementations of single-chip multiprocessor systems with a configurable router intended for dedicated, embedded network-on-chip support within field-programmable gate arrays in order to provide performance and flexibility for system-on-chip applications. The router supports ring, octagon, and mesh network topologies. Implementation in an Altera Stratix EP1S80 chip is supported with a tool chain that combines custom high-level system specification software with commercial Altera software to generate single-chip multiprocessors using multiple instances of the configurable router and the Altera Nios II soft processor. A 16-node multiprocessor using a mesh topology occupies up to two-thirds of an Altera Stratix EP1S80 chip, and the aggregate communication bandwidth for a mesh is experimentally shown to be at least 11.5 Gbytes/sec with an 80-MHz system clock and 64-bit-wide connections.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.045
GPT teacher head0.214
Teacher spread0.168 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2008
Admission routes3
Has abstractyes

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