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Record W2122035961 · doi:10.1109/tcad.2006.882595

Dual-Threshold CAD Framework for Subthreshold Leakage Power Aware FPGAs

2007· article· en· W2122035961 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

VenueIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 2007
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsField-programmable gate arrayComputer scienceSubthreshold conductionDual (grammatical number)CADEmbedded systemLeakage (economics)Computer architectureTransistorEngineeringElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

Managing leakage power in field programmable gate arrays (FPGAs) has become critical for the FPGA industry to remain competitive in the semiconductor market and enter the mobile applications domain. This paper proposes and evaluates several dual-Vt-based designs of FPGA architecture for reducing the leakage power. A dual-Vt FPGA computer-aided design (CAD) framework has been proposed, which is used to develop and evaluate different dual-Vt FPGA architectures. The logic elements and the routing resources are considered as candidates for dual-Vt assignment. The authors estimate the number of the logic elements that can be assigned as high-Vt in the ideal case by using a dual-Vt assignment algorithm in the CAD framework. Based upon this estimate, the authors develop and evaluate two kinds of architectures, homogenous and heterogenous. The results indicate that an average leakage-power savings of up to 50% can be obtained from these architectures. This CAD framework can also be used for developing and evaluating different dual-Vt FPGA architectures other than the ones proposed in this paper

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.028
GPT teacher head0.239
Teacher spread0.210 · 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