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Record W4240011581 · doi:10.1109/aspdac.2010.5419877

Symmetry-aware TCG-based placement design under complex multi-group constraints for analog circuit layouts

2010· article· en· W4240011581 on OpenAlexafffund
Rui He, Lihong Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransitive closureComputer scienceRepresentation (politics)GraphIntegrated circuit layoutTime complexityAlgorithmSymmetry (geometry)Set (abstract data type)Topology (electrical circuits)Computational complexity theoryTheoretical computer scienceMathematicsDiscrete mathematicsIntegrated circuitCombinatoricsGeometry

Abstract

fetched live from OpenAlex

This paper presents a solution to handling complex multi-group symmetry constraints in the placement design using transitive closure graph (TCG) representation for analog layouts. We propose a set of symmetric-feasible conditions, which can automatically satisfy symmetry requirements. We also develop a new contour-based packing scheme with time complexity of O(g·n·lgn), where g is the number of symmetry groups and n is the number of the placed cells. Furthermore, we devise a set of perturbation operations with time complexity of O(n). Our experimental results show the effectiveness and superiority of this proposed scheme compared to the other state-of-the-art placement algorithms for analog layout design.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.852
Threshold uncertainty score1.000

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)0.0010.000

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 head0.076
GPT teacher head0.275
Teacher spread0.199 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreMethods

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

Citations6
Published2010
Admission routes2
Has abstractyes

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