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Record W1605823078 · doi:10.1109/iscas.1994.409265

Current input TSPC latch for high speed, complex switching trees

2002· article· en· W1605823078 on OpenAlexafffund
Pizeng Zhou, J.C. Czilli, G.A. Jullien, William C. Miller

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsBiCMOSBlock (permutation group theory)Computer scienceCMOSLookup tableTree (set theory)Binary treeComputer hardwareEmbedded systemElectronic engineeringElectrical engineeringTransistorEngineeringAlgorithmMathematicsVoltage

Abstract

fetched live from OpenAlex

This paper discusses new techniques for obtaining high clock rates with complex n-blocks in True-Single-Phase dynamic latch structures. In this paper we present new dynamic current steering latch structures, and apply them to both CMOS and BiCMOS technologies. In the latter case, we exploit the superior properties of the available bipolar devices to achieve substantial speed increases. The latching technique allows complex n-FET blocks (fan-in between 10 and 20) to be used with the TSPC latch at high data rates (over 150 MHz for a 1.2 /spl mu/ CMOS process). The n-FET block is built as a minimized binary tree, which we have termed a switching tree, and interpreted as a general look-up table for use in a variety of bit-level systolic array processors.>

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.241
Teacher spread0.203 · 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

Citations2
Published2002
Admission routes2
Has abstractyes

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