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Record W2149339590 · doi:10.1109/cicc.1993.590578

Advantages of heterogeneous logic block architecture for FPGAs

2002· article· en· W2149339590 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLookup tableField-programmable gate arrayComputer scienceBenchmark (surveying)Programmable logic arrayLogic blockLogic synthesisProgrammable logic deviceParallel computingLogic gateHomogeneousProgrammable Array LogicBlock (permutation group theory)Table (database)Logic optimizationLogic familyReduction (mathematics)Computer architectureComputer hardwareAlgorithmMathematics

Abstract

fetched live from OpenAlex

The authors consider field programmable gate arrays (FPGAs) that use two different sizes of lookup table (LUT) logic blocks and investigate the area-efficiency of different mixtures of different sizes of LUTs. Experimental results on a set of benchmark circuits indicate that several heterogeneous architectures achieve significant reduction in the number of programming bits and logic block pins compared to the industry standard 4-input LUTs. A 6-LUT/4-LUT combination will likely exhibit better performance with nearly equivalent area than a homogeneous 4-LUT 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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.256

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 science0.0000.000
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 head0.031
GPT teacher head0.246
Teacher spread0.214 · 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

Quick stats

Citations32
Published2002
Admission routes1
Has abstractyes

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