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Record W2099019121 · doi:10.1109/iscas.2007.378651

Asynchronous Adiabatic Logic

2007· article· en· W2099019121 on OpenAlexaff
Muhammad Arsalan, Maitham Shams

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsCarleton University
Fundersnot available
KeywordsAsynchronous circuitAsynchronous communicationAdiabatic circuitAsynchronous systemComputer scienceClock domain crossingClock gatingSynchronous circuitLogic gateClock signalElectronic engineeringLogic synthesisElectronic circuitLogic familyEngineeringElectrical engineeringComputer networkAlgorithm

Abstract

fetched live from OpenAlex

Power clock generators (PCGs) are the prevalent overhead for the adiabatic systems and mutilate all the low-power advantage from the adiabatic logic part by consuming a large portion of the total power in the clock generation circuitry (Arsalan and Shams, 2005). In addition to the PCG issues, routing multiple clock phases for adiabatic circuits is not very convenient and raises a number of cost, performance and viability issues. To get rid of the problems related to clock generation and synchronous clock routing, a new solution namely asynchronous adiabatic logic (AAL) is proposed to combing the benefits of the adiabatic logic circuits with that of asynchronous logic systems. Going asynchronous not only eliminates the need of PCGs, hence all the problems associated with the generation and routing of the clocks, it also bring all the advantages intrinsically associated with an asynchronous design such as low power and reliable logical operation.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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 designTheoretical or conceptual
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

Citations20
Published2007
Admission routes1
Has abstractyes

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