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Record W2513352037 · doi:10.1109/jssc.2016.2596773

A 0.3 pJ/bit 20 Gb/s/Wire Parallel Interface for Die-to-Die Communication

2016· article· en· W2513352037 on OpenAlexaff
Behzad Dehlaghi, Anthony Chan Carusone

Bibliographic record

VenueIEEE Journal of Solid-State Circuits · 2016
Typearticle
Languageen
FieldEngineering
Topic3D IC and TSV technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDie (integrated circuit)TransceiverCMOSInterposerTransmitterElectrical engineeringElectronic circuitSilicon on insulatorComputer scienceMaterials scienceOptoelectronicsElectronic engineeringComputer hardwareChannel (broadcasting)SiliconEngineeringNanotechnologyLayer (electronics)

Abstract

fetched live from OpenAlex

A high-density low-power parallel I/O for die-to-die communication is presented. The proposed interface includes a low-power transceiver and a high-density low-cost silicon interposer. The link architecture exploits single-sided and capacitive termination, passive equalization in the transmitter, and CMOS logic-style circuits to reduce the power consumption. To achieve a high bump/wire efficiency, single-ended signaling is used. A 4-layer Aluminum silicon interposer is fabricated providing 2.5 mm and 3.5 mm links between prototype transceivers. The transceiver prototype includes 3 transmitters and 3 receivers fabricated in 28 nm STM FD-SOI CMOS technology. The parallel interface operates at 20 Gb/s/wire and 18 Gb/s/wire data rates over the 2.5 mm and 3.5 mm channels with 5.9 and 7.7 dB of loss relative to DC (10.7 and 13.5 dB total loss) at fbit/2 while consuming 0.30 and 0.32 pJ/bit excluding clocking circuits, respectively.

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 score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.003

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 head0.027
GPT teacher head0.274
Teacher spread0.247 · 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

Citations41
Published2016
Admission routes1
Has abstractyes

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