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Record W1933113402 · doi:10.1109/pacrim.1993.407275

Mobility based scheduling for the register-transfer synthesis of systolic arrays

2002· article· en· W1933113402 on OpenAlexafffund
William Robertson, Shalini Periyalwar, William Phillips

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsTechnical University of Nova Scotia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInterlacingMultiplexerComputer scienceParallel computingScheduling (production processes)Point (geometry)Real-time computingAlgorithmMultiplexingMathematicsMathematical optimizationArtificial intelligenceTelecommunications

Abstract

fetched live from OpenAlex

The authors present a novel scheduling and allocation algorithm for both one- and two-dimensional SUs (systolic units). This algorithm works across the PEs (processing elements) of an SU to reduce the number of FUs (functional units) required in an implementation. For the examples presented this technique results in fewer FUs and latches than if individual PEs were synthesized and then combined into an SU. In systolic arrays where the silicon area requirement of each PE is high, interlacing across PEs results in an implementation with a smaller design area. The interlacing (latch, controller, and multiplexer) area increases with interlacing up to a certain point. After this point, increased interlacing actually reduces the number of latches and multiplexers in the design, resulting in a drop in interlacing area. This is because in the proposed design strategy the latches are also interlaced in order to make the most efficient use of silicon.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.823
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.052
GPT teacher head0.260
Teacher spread0.208 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2002
Admission routes2
Has abstractyes

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