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Record W3150180001 · doi:10.1109/famcad.2007.39

Circuit Level Verification of a High-Speed Toggle

2007· article· en· W3150180001 on OpenAlexaff
Chao Yan, Mark R. Greenstreet

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicFormal Methods in Verification
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceDigital electronicsProjection (relational algebra)SolverVery-large-scale integrationElectronic circuitComputer engineeringAlgorithmElectronic engineeringEmbedded systemElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

As VLSI fabrication technology progresses to 65nm feature sizes and smaller, transistors no longer operate as ideal switches. This motivates verifying digital circuits using continuous models. This paper presents the verification of the high-speed, toggle flip-flop proposed by Yuan and Svensson [1]. Our approach builds on the projection based methods originally proposed by Greenstreet and Mitchell [2], [3]. While they were only able to demonstrate their approach with two- and threedimensional systems, we apply projection based analysis to a seven-dimensional model for the flip-flop. We believe that this is the largest verification to date of a digital circuit using non-linear circuit-level models. In this paper, we describe how we overcame problems of numerical errors and instability associated with the original projection based methods. In particular, we present a novel linear-program solver and new methods for constructing accurate linear approximations of non-linear dynamics. We use the toggle flip-flop as an example and consider how these methods could be extended to verify a standard cell library for digital 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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.096
GPT teacher head0.312
Teacher spread0.217 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2007
Admission routes1
Has abstractyes

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