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Record W2520705664 · doi:10.1145/2950067.2950076

A fully parallel approximate CORDIC design

2016· article· en· W2520705664 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

VenueInternational Symposium on Nanoscale Architectures · 2016
Typearticle
Languageen
FieldComputer Science
TopicNumerical Methods and Algorithms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCORDICComputer scienceRotation (mathematics)Transformation (genetics)Scheme (mathematics)AlgorithmTrigonometric functionsDiscrete cosine transformParallel computingArithmeticMathematicsField-programmable gate arrayComputer hardwareArtificial intelligenceImage (mathematics)

Abstract

fetched live from OpenAlex

This paper proposes a new approximate scheme for a coordinate rotation digital computer (CORDIC) design; this scheme is based on modifying the existing Para-CORDIC architecture with multiple approximations. These approximations make possible a relaxation of the CORDIC algorithm itself, such that a fully parallel approximate CORDIC (FPAX-CORDIC) scheme is designed. This scheme avoids the memory register of Para-CORDIC and makes fully parallel the generation of the rotation direction. A comprehensive analysis and the evaluation of the error introduced by the approximations together with different circuit-related metrics are pursued using HSPICE as simulation tool. The error analysis of this paper combines existing figures of merit for approximate computing (such as the Mean Error Distance (MED)) with CORDIC-specific parameters; a good agreement between expected and simulated error values is found. As an application to image processing, the Discrete Cosine Transformation (DCT) is investigated by utilizing the proposed approximate FPAX-CORDIC architecture with different accuracy requirements. The results confirm the viability of the proposed scheme.

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: Methods
Teacher disagreement score0.799
Threshold uncertainty score0.535

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 science0.0010.000
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 head0.018
GPT teacher head0.269
Teacher spread0.251 · 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