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Record W1998925396 · doi:10.1109/asap.2007.4429952

FPGA-Based Efficient Design Approach for Large-Size Two's Complement Squarers

2007· article· en· W1998925396 on OpenAlexaff
Shuli Gao, Noureddine Chabini, D. Al-Khalili, Pierre Langlois

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsPolytechnique MontréalRoyal Military College of Canada
Fundersnot available
KeywordsField-programmable gate arrayOperandLookup tableComputer scienceComplement (music)Realization (probability)Reduction (mathematics)Parallel computingArithmeticEmbedded systemComputer hardwareMathematicsOperating system

Abstract

fetched live from OpenAlex

This paper presents an optimized design approach of two's complement large-size squarers using embedded multipliers in FPGAs. The realization is based on Baugh-Wooley's algorithm, which partitions the multiplication into unsigned and signed sections. To achieve efficient implementation, a set of optimized schemes for the realization of multi-level additions of the partial products is proposed. Our approach has been evaluated through the implementation of squarers for operands with sizes ranging from 20 to 128 bits. The designs are synthesized and implemented on Xilinx' Spartan-3 with ISE 8.1 design platform and compared with the standard implementation, and with Xilinx' IP Core. The results indicate that our approach offers substantial LUT savings by up to 52% with an average delay reduction of 13%. The usage of the number of embedded multipliers is reduced by 38% compared with the standard schemes.

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.

How this classification was reachedexpand

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.676
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.249
Teacher spread0.226 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2007
Admission routes1
Has abstractyes

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