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Record W2481610175 · doi:10.1142/s0218126616501498

Modified Operand Decomposition Multiplication for High Performance Parallel Multipliers

2016· article· en· W2481610175 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Circuits Systems and Computers · 2016
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsCanadian Nuclear LaboratoriesDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOperandAdderMultiplier (economics)NAND logicNAND gateArithmeticMultiplication (music)TransistorComputer sciencePower consumptionParallel computingPower–delay productTransistor countDissipationMathematicsLogic gatePower (physics)Electronic engineeringAlgorithmElectrical engineeringEngineeringCMOSVoltagePhysics

Abstract

fetched live from OpenAlex

A low power operand decomposition multiplication architecture implementation is modified to further reduce its power dissipation and delay. First, the multiplier’s implementation was modified to generate the partial products using NAND gates instead of AND and OR gates in order to reduce the number of transistors (area utilized) and to reduce the delay. Then, new types of adders and (4:2) compressors, that accept negatively weighted bits are used to reduce the number of inverters. Therefore, the resulting multiplier architecture reduces the number of transistors significantly. These modifications result in 20% and 36% reduction in power consumption and energy delay product (EDP), respectively.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.457

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 communication0.0000.001
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 head0.012
GPT teacher head0.212
Teacher spread0.200 · 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