MétaCan
Menu
Back to cohort
Record W2140736088 · doi:10.1109/newcas.2006.250901

On the Design of a Double Precision Logarithmic Number System Arithmetic Unit

2006· article· en· W2140736088 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 institutionsPolytechnique Montréal
Fundersnot available
KeywordsCORDICComputer scienceArithmeticLogarithmFloating-point unitMicroprocessorLatency (audio)Clock rateParallel computingComputer hardwareFloating pointInterpolation (computer graphics)Series (stratigraphy)Saturation arithmeticArbitrary-precision arithmeticCacheTable (database)Double-precision floating-point formatMathematicsAlgorithmField-programmable gate arrayTelecommunications

Abstract

fetched live from OpenAlex

This paper investigates the integration of a 64-bit LNS arithmetic unit into a conventional microprocessor. The goals are to devise an LNS unit that can be faster than an FPU for a broad range of applications, and to minimize the added hardware. Two ways of implementing the logarithmic sum and difference functions are studied. One way uses higher-order Taylor series implemented by look-up tables and interpolation, while the other is based on a CORDIC engine. It is shown that a look-up table based implementation is fairly competitive to a floating-point unit in terms of clock rate, overall latency and repeat rate, at the expense of some cache pressure, while the CORDIC-based implementation is fast, has a repeat rate of one clock cycle, and supports complex operations but at the cost of a higher gate count

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: Methods · Consensus signal: Methods
Teacher disagreement score0.834
Threshold uncertainty score0.252

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 science0.0010.000
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 head0.041
GPT teacher head0.281
Teacher spread0.240 · 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

Citations4
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicNumerical Methods and AlgorithmsFrench-language works237,207