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Record W2134616364 · doi:10.1109/iccd.1994.331890

Area efficient synthesis of asynchronous interface circuits

2002· article· en· W2134616364 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicFormal Methods in Verification
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsAsynchronous communicationComputer scienceDivide and conquer algorithmsGraphElectronic circuitInterface (matter)High-level synthesisDigital electronicsTheoretical computer scienceComputer engineeringComputer architectureAlgorithmParallel computingEmbedded systemComputer network

Abstract

fetched live from OpenAlex

Asynchronous circuits are widely used in many real time applications such as digital communication and computer systems. The design of complex asynchronous interface circuits is a difficult and error-prone task. We present an area and time efficient synthesis algorithm for general signal transition graph (STG) specifications. It utilizes a divide-and-conquer approach to significantly reduce the number of design constraints. We present a BDD constraint satisfaction algorithm that exploits the don't cares for area efficient synthesis. Experimental results with a large number of practical signal transition graph benchmarks are presented. These results show that compared to the existing techniques, the divide-and-conquer BDD technique is capable of achieving an average of 20% reduction in implementation area.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: Methods · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score0.278

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 head0.041
GPT teacher head0.265
Teacher spread0.225 · 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

Citations8
Published2002
Admission routes2
Has abstractyes

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