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Record W2153610244 · doi:10.1109/iscas.2008.4541679

VLSI implementation of a shift-enabled reconfigurable array

2008· article· en· W2153610244 on OpenAlexaff
Scott W. Miller, Mihai Sima, Michael McGuire

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMultiplexerComputer scienceVery-large-scale integrationInterconnectionShift registerOverhead (engineering)Parallel computingPoint (geometry)Array data structurePower (physics)Electronic engineeringEmbedded systemComputer networkEngineeringMultiplexingTelecommunicationsMathematicsPhysics

Abstract

fetched live from OpenAlex

We describe the implementation of a coarse-grain reconflgurable array that implements shift operations within its interconnection network. The connection point of such an array is a triangular matrix of switches. The reconflgurable array is geared toward the implementation of sequential Shift-and- Add algorithms. We show that a triangular switch-box that uses a level-restoring buffer with an unfolded multiplexer exhibits improved propagation delay and power consumption against prior art. This leads to a coarse-grain reconflgurable array that efficiently implements transcendental functions.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score0.488

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 head0.024
GPT teacher head0.258
Teacher spread0.234 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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