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Record W2142395333 · doi:10.1109/fpl.2006.311357

Architecture and CAD for FPGA Clock Networks

2006· article· en· W2142395333 on OpenAlexaff
Julien Lamoureux, Steven J. E. Wilton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsField-programmable gate arrayDigital clock managerClock networkClock skewComputer scienceClock gatingEmbedded systemSkewProcess (computing)CADCPU multiplierFPGA prototypeComputer hardwareComputer architectureClock signalEngineeringJitterTelecommunicationsOperating system

Abstract

fetched live from OpenAlex

Scaling of process technologies and innovations in FPGA architecture and CAD are allowing increasingly more sophisticated applications to be implemented on FPGAs. These applications include system-level designs consisting of many subcomponents that use separate clocks. To support a wide range of applications with different clocking schemes, commercial devices have incorporated high-speed, low-skew clock networks that supply multiple clock signals to logic, memory, and arithmetic elements in the FPGA. The design of these programmable clock networks and of the CAD tools that support them is of utmost importance. Not only does the clock network itself dissipate a significant amount of power, since it connects to every latch on the FPGA and toggles every cycle. But, the design of clock network also affects how efficiently the rest of the circuit can be implemented, since it imposed constraints on the CAD tools that map applications onto the FPGA.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.004

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 head0.004
GPT teacher head0.177
Teacher spread0.174 · 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 designNot applicable
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

Citations2
Published2006
Admission routes1
Has abstractyes

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