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Record W2099838466 · doi:10.1109/ccece.1999.807240

Design and synthesis of an IEEE-754 exponential function

2003· article· en· W2099838466 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 institutionsConcordia University
Fundersnot available
KeywordsComputer scienceVHDLRoundingVerilogExponential functionLookup tableFloating pointHardware description languageTable (database)Function (biology)Multiplication (music)Integer (computer science)Parallel computingAlgorithmComputer hardwareField-programmable gate arrayProgramming languageMathematicsOperating system

Abstract

fetched live from OpenAlex

We have designed a floating-point exponential function using the table-driven method. The algorithm was first implemented using sequential VHDL and later translated to Concurrent Verilog. The main part of the work consisted of creating modules that would handle basic IEEE-754 single-precision number manipulation routines, such as addition, multiplication and rounding to the nearest integer. Using these routines, a model was implemented based on the table-driven algorithm. The VHDL design as well as the Verilog design were estimated, and the results proved to be satisfactory. Synthesis was performed using CMOSIS5 technology on the VHDL code and yielded a fairly large result.

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 score0.946
Threshold uncertainty score0.162

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 head0.030
GPT teacher head0.262
Teacher spread0.232 · 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

Citations27
Published2003
Admission routes1
Has abstractyes

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