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Record W1967423732 · doi:10.1145/1508128.1508181

Customizable bit-width in an OpenMP-based circuit design tool

2009· article· en· W1967423732 on OpenAlexaff
Timothy F. Beatty, Eric Aubanel, Kenneth B. Kent

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsComputer scienceCompilerBenchmark (surveying)AbstractionComputer architectureSet (abstract data type)ImplementationRegister-transfer levelAbstraction layerParallel computingProgramming languageLogic synthesisSoftwareLogic gateAlgorithm

Abstract

fetched live from OpenAlex

As transistor density grows, increasingly complex hardware designs are implemented. In order to manage this complexity, hardware design can be performed at a higher level of abstraction. High level synthesis enables the automatic conversion of algorithms into hardware implementations, abstracting away the underlying complexities of hardware from the designer. A number of high level synthesis tools have recently been developed, including an OpenMP to Handel-C translator. Improvements to the translator, including a new compiler directive allowing customizable register width, are described. Using a set of benchmark tests, the OpenMP to Handel-C translator is evaluated on several criteria, with the goal of evaluating the variable bit-width effects and identifying further areas for improvement.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.435
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.043
GPT teacher head0.278
Teacher spread0.235 · 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 designSimulation or modeling
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

Citations3
Published2009
Admission routes1
Has abstractyes

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