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Record W2097232115 · doi:10.1109/newcas.2004.1359116

Carry free, bit parallel approximate squarers with linear complexity and constant delay

2004· article· en· W2097232115 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

VenueThe 2nd Annual IEEE Northeast Workshop on Circuits and Systems, 2004. NEWCAS 2004. · 2004
Typearticle
Languageen
FieldComputer Science
TopicNumerical Methods and Algorithms
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsParameterized complexityConstant (computer programming)Function (biology)Boolean functionBit (key)Computer scienceSimple (philosophy)AlgorithmMathematicsLookup tableArithmetic

Abstract

fetched live from OpenAlex

This paper presents two simple combinational logic design approaches for bit-parallel approximate squarers of unsigned numbers. The design approaches are suitable for squarers of any bit length, and are particularly well suited for implementation in LUT-based FPGAs. It is shown that the hardware requirements grow linearly with the input bit width, as opposed to recent work where the complexity grows quadratically. This is a consequence of the optimized function selection algorithm which limits the number of input variables to each bit function. It is also shown that the critical path delay is independent of the input bit width. The proposed sets of Boolean equations are very simple to use and lend themselves very well to a parameterized HDL description. For a 7-bit input squarer, the maximum relative error (MRE) and average relative error (ARE) are as low as 9.44% and 2.47%, respectively. For very wide input, the MRE and ARE asymptotically approach 11.3% and 4.5%.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.894
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.279
Teacher spread0.231 · 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