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Record W7095818716

To appear in Canadian Journal of Electrical and Computer Engineering Two High Performance and Low Power Serial Communication Interfaces for On-chip Interconnects

2013· article· en· W7095818716 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsnot available
Fundersnot available
KeywordsFrame (networking)TransmitterSerial communicationData transmissionPower (physics)Bandwidth (computing)Transmission (telecommunications)Decoding methodsData recoveryPower-line communication
DOInot available

Abstract

fetched live from OpenAlex

Abstract: This paper presents two novel methods for on-chip serial communication whereby the clocks of the transmitter and the receiver are generated with two separate ring oscillators. These oscillators are identical although they can have some a small frequency difference. In the first method, a strobe line, which toggles exactly once with every frame of n-bit data, is used to activate the oscillators. Local counters are used to count the number of bits in the data frame and to stop the local oscillators when the frame is processed. In the second method, a single physical line is used to transmit both data and (inband) control information, further reducing the power dissipation. The data transmission is controlled by the output of a starter flip-flop, indicating the empty/full status of an input buffer whereas the data reception is controlled by decoding a ‘1 ” start bit and a ‘0 ’ end bit which have been added to the n-bit data word to form a frame. Our circuit simulation results demonstrate that both communication methods result in high bandwidth and low power dissipation.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.276
Threshold uncertainty score0.923

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2760.094

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 head0.005
GPT teacher head0.184
Teacher spread0.179 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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