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Record W1727481168 · doi:10.1109/icecs.2000.911589

Behavioural synthesis of low power floating point CORDIC processors

2002· article· en· W1727481168 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNumerical Methods and Algorithms
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsCORDICComputer scienceVerilogImplementationComputer architectureDigital signal processingProcess (computing)Embedded systemField-programmable gate arrayComputer hardwareParallel computingProgramming language

Abstract

fetched live from OpenAlex

Modern DSP and graphical applications require fast and efficient implementations to meet the high demands of modern systems. The CORDIC process is a powerful candidate for these systems due to its ability to perform many basic functions using the same hardware. Recent research has led to the development of a daunting number of implementation options, each with its own application restrictions and operating characteristics. This paper introduces the development of a behavioral synthesis tool designed to automate and simplify the design and use of CORDIC processors in general applications. At the present time the tool produces 576 unique versions of a CORDIC processing element in the Verilog HDL. These processing elements, or modules, can then be instantiated for use in embedded systems or System-on-a-Chip applications.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.542

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 head0.027
GPT teacher head0.253
Teacher spread0.226 · 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

Quick stats

Citations1
Published2002
Admission routes1
Has abstractyes

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