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Record W2044257423 · doi:10.1109/asscc.2008.4708770

A 10Gb/s active-inductor structure with peaking control in 90nm CMOS

2008· article· en· W2044257423 on OpenAlexaff
Yen-Sung Michael Lee, Samad Sheikhaei, Shahriar Mirabbasi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInductorCMOSElectrical engineeringPMOS logicVoltageElectronic engineeringComputer scienceEngineeringTransistor

Abstract

fetched live from OpenAlex

A PMOS-based active inductor circuit for high-speed I/O applications is presented. The active inductor can operate with low voltage headroom and requires no voltage boosting. A prototype output driver circuit using the active inductor is implemented in 90 nm CMOS. The peaking frequency and its corresponding gain magnitude of the active-inductor circuit can be adjusted to facilitate channel loss compensation. Operating at 10 Gb/s over a 6-in FR4 channel, as compared to the case when the active-inductor structure is disabled, the use of active inductor circuit in the transmitter side increases the vertical eye opening at the receiver side by a factor of two and reduces the peak-to-peak jitter of the received data by 30%. By keeping the current of the active inductor above a certain value, impedance variations are minimized and appropriate impedance matching is achieved (S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">22</sub> less than -10 dB). The active-inductor circuit occupies 17 times 25 mum <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and has a low overhead power consumption of 0.8 mW, i.e., ~10% of the overall power of the prototype output driver.

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 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: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.383

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 head0.007
GPT teacher head0.187
Teacher spread0.180 · 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 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

Citations21
Published2008
Admission routes1
Has abstractyes

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Same topicAdvancements in PLL and VCO TechnologiesFrench-language works237,207