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Record W2100792281 · doi:10.1109/iscas.1992.230699

A constructive matching algorithm for cell generator based technology mapping

2003· article· en· W2100792281 on OpenAlex
Cliff Liem, Martin Lefebvre

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
TopicVLSI and Analog Circuit Testing
Canadian institutionsCarleton University
FundersCMC Microsystems
KeywordsConstructiveCompilerComputer scienceGenerator (circuit theory)Matching (statistics)Context (archaeology)AlgorithmConstraint (computer-aided design)Standard cellCMOSTheoretical computer scienceComputer engineeringIntegrated circuitProgramming languageElectronic engineeringMathematicsEngineeringProcess (computing)

Abstract

fetched live from OpenAlex

The authors present a new approach to technology mapping targeting for CMOS complex cell generators. The approach improves on current mapping techniques by introducing a constraint-driven module whose parameters are defined by the capabilities of a cell compiler. This constructive matching technique allows mapping of networks for very large cell families. The module is placed in a context which ensures that the mappings are also of high quality. Using this platform for an experiment, a study of the impact of different sized cell families is presented. The study shows that larger cell families offer a savings in the area and delay of technology mapped circuits.< <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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.796
Threshold uncertainty score0.423

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 head0.014
GPT teacher head0.216
Teacher spread0.201 · 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

Citations7
Published2003
Admission routes2
Has abstractyes

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