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Record W2591853747 · doi:10.1109/cjece.2016.2638962

New Systolic Array Architecture for Finite Field Inversion

2017· article· en· W2591853747 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Electrical and Computer Engineering · 2017
Typearticle
Languageen
FieldComputer Science
TopicCoding theory and cryptography
Canadian institutionsUniversity of Victoria
FundersKing Abdulaziz City for Science and Technology
KeywordsArchitectureInversion (geology)RangingSystolic arrayApplication-specific integrated circuitPower consumptionComputer scienceEuclidean geometryFinite fieldParallel computingAlgorithmComputer engineeringPower (physics)MathematicsEmbedded systemDiscrete mathematicsTelecommunicationsVery-large-scale integrationGeometry

Abstract

fetched live from OpenAlex

This paper proposes a new systolic array architecture to perform inversion operation in GF(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sup> ) based on a previously modified extended Euclidean algorithm. This architecture has low area and power complexities and it achieves a moderate speed. This architecture is explored by applying a regular technique to the inversion algorithm. The systolic architecture obtained has simple structure with processing elements that have local communication with each other. ASIC implementation of the proposed design and comparable published designs shows that the proposed design saves more area (ranging from 14.1% to 63.4%) and saves more energy (ranging from 22.9% to 81.9%) over the compared efficient designs that makes it more suitable for resource-constrained embedded applications that impose more constraints on area and power consumption.

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 score0.918
Threshold uncertainty score0.311

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 head0.007
GPT teacher head0.183
Teacher spread0.176 · 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