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Record W2344960176 · doi:10.1109/rsp.2007.16

Codesign of a Computationally Intensive Problem in GF(3)

2007· article· en· W2344960176 on OpenAlex
Kenneth B. Kent, Beatriz C. Iaderoza, M. Serra

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

VenueProceedings · 2007
Typearticle
Languageen
FieldComputer Science
TopicCryptography and Residue Arithmetic
Canadian institutionsUniversity of VictoriaUniversity of New Brunswick
Fundersnot available
KeywordsComputer scienceField-programmable gate arrayGalois theoryComputer architectureSoftwareOverhead (engineering)Embedded systemParallelism (grammar)Reconfigurable computingTransformation (genetics)Parallel computingOperating systemMathematics

Abstract

fetched live from OpenAlex

A reprogrammable hardware platform is used for the co-design and implementation of a computational intensive mathematical problem, namely the listing of irreducible polynomials over Galois fields of order 3 (GF(3)), The main goal is to accelerate the performance compared to an existing software implementation. This project uses hardware/software co-design methodologies and techniques, and it is completely designed, implemented and evaluated on two distinct platforms, not simply by simulations. FPGAs are used as part of the reconfigurable hardware in both a PCI-based environment and in a more successful System-on-Chip (SOC) platform, which takes advantage of the closely-coupled interconnection between the hardware and software, thus minimizing the communication overhead. The case study, findings and general analysis lead to a possible ideal architecture for future approaches. Moreover, a more general detailed strategy can be seen for the transformation from software to a co-design paradigm, maximizing parallelism.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.506
Threshold uncertainty score0.284

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 communication0.0000.000
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 head0.010
GPT teacher head0.239
Teacher spread0.229 · 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