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Record W2344622367 · doi:10.1109/tvlsi.2015.2496312

A Mismatch-Insensitive Skew Compensation Architecture for Clock Synchronization in 3-D ICs

2015· article· en· W2344622367 on OpenAlexafffund
Tejinder Singh Sandhu, Kamal El‐Sankary

Bibliographic record

VenueIEEE Transactions on Very Large Scale Integration (VLSI) Systems · 2015
Typearticle
Languageen
FieldEngineering
Topic3D IC and TSV technologies
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsJitterClock skewSkewComputer scienceElectronic engineeringNetwork topologySynchronization (alternating current)Clock domain crossingCompensation (psychology)CMOSStatic timing analysisTopology (electrical circuits)Clock signalDetectorSynchronous circuitEngineeringElectrical engineeringTelecommunications

Abstract

fetched live from OpenAlex

Traditional die-to-die (DTD) clock skew compensation topologies prerequisite matched delay lines or equal through-silicon via (TSV) delays. Unlike previous techniques, the proposed mismatch-insensitive skew compensation architecture can maintain a synchronous clock signal between two dies, while completely eliminating any skew arising from code-dependent mismatch in delay lines or unequal TSV delays. The performance of our design is verified in theory and simulation in light of mismatch/finite resolution of delay lines, clock jitter, phase detector dead zone, TSV delay, and buffer mismatch. Postsynthesis timing verification of this cell-based design was done in a 65-nm CMOS process. Under similar worse case mismatch conditions, the residual skew in the proposed architecture was delimited to 32 ps at 1 GHz, compared with 116 ps for a recent DTD topology, while consuming only 2.1 mW.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.017
GPT teacher head0.227
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations11
Published2015
Admission routes2
Has abstractyes

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Same venueIEEE Transactions on Very Large Scale Integration (VLSI) SystemsSame topic3D IC and TSV technologiesFrench-language works237,207