MétaCan
Menu
Back to cohort
Record W2134015534 · doi:10.1109/newcas.2007.4488016

A single-chip ring-based multiprocessor with region-level filtering of coherence traffic

2007· article· en· W2134015534 on OpenAlexafffund
Edmond Cote, Naraig Manjikian

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceCache coherenceMultiprocessingMESI protocolMESIF protocolCacheBus sniffingDirectoryEmbedded systemCoherence (philosophical gambling strategy)Parallel computingComputer hardwareComputer architectureCache algorithmsCPU cacheOperating system

Abstract

fetched live from OpenAlex

This paper presents the architecture and prototype hardware implementation of a single-chip shared-memory multiprocessor based on a ring interconnect with support for adaptive filtering of coherence traffic. Our implementation is suitable for application-specific designs and avoids the complexity associated with directory-based cache coherence by limiting writes to addresses that are local to the requesting node while maintaining cache coherence for shared data throughout the system. In addition, we seek to adaptively restrict the scope of coherence operations by employing filter structures in hardware with modest storage requirements. To characterize the logic utilization of the proposed filters relative to other system components, a prototype multiprocessor system has been described in 4250 lines of synthesizable SystemVerilog code and implemented in field-programmable logic. Synthesis results are presented to characterize the logic overhead of the filter structures, and operational results are presented to demonstrate their behavior.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.514
Threshold uncertainty score0.429

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 head0.051
GPT teacher head0.259
Teacher spread0.207 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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
Published2007
Admission routes2
Has abstractyes

Explore more

Same topicParallel Computing and Optimization TechniquesFrench-language works237,207