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Record W2154013582 · doi:10.1109/fpl.2007.4380648

Embedded Programmable Logic Core Enhancements for System Bus Interfaces

2007· article· en· W2154013582 on OpenAlexaff
B.R. Quinton, Steven J. E. Wilton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceProgrammable logic deviceElectronic circuitEmbedded systemInterface (matter)Overhead (engineering)Focus (optics)System busLogic gateLogic synthesisComplex programmable logic deviceProgrammable logic arrayComputer architectureComputer hardwareEngineeringParallel computingElectrical engineeringOperating system

Abstract

fetched live from OpenAlex

Programmable logic cores (PLCs) offer a means of providing post-fabrication re-configurability to a SoC design. Circuits implemented in a PLC will inevitably have lower timing performance and logic density than fixed function circuits. This fundamental mismatch makes the design of the interface between the PLC and the rest of the SoC a challenging problem. In this paper we focus on interfaces between circuits implemented in PLCs and SoC system busses. We demonstrate problems with existing implementation options and then propose modifications to parts of the PLC architecture to enable more efficient system bus interfaces. Our results show that, on average, this modified architecture improves interface timing by 36.4%, reduces CLB usage by 7.9% and improves routability by 28.8% for circuits that require system bus interfaces. We show that the area overhead is less than 0.5% for circuits that do not require bus interfaces.

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)0.002
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.054
GPT teacher head0.333
Teacher spread0.279 · 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
Published2007
Admission routes1
Has abstractyes

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