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Record W2133323787 · doi:10.1504/ijhpsa.2011.040467

A RISC architecture for 2DLNS-based signal processing

2011· article· en· W2133323787 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

VenueInternational Journal of High Performance Systems Architecture · 2011
Typearticle
Languageen
FieldComputer Science
TopicNumerical Methods and Algorithms
Canadian institutionsUniversity of Windsor
FundersCMC Microsystems
KeywordsComputer scienceDigital signal processingArchitectureComputer architectureParallel computingComputationSignal processingRepresentation (politics)Multiplication (music)CoprocessorReduced instruction set computingEmbedded systemInstruction setComputer hardwareAlgorithm

Abstract

fetched live from OpenAlex

The multi-dimensional logarithmic number system (MDLNS) provides a reduction in the size of the number representation and promises a lower cost realisation of arithmetic operations. The non-linear nature of the representation and independency of the parallel-based computations combined with multi-digit extensions of the MDLNS representations along with simplified arithmetic operations, make MDLNS suitable for some multiplication intensive DSP applications. The work presented in this paper is the design and implementation of a 2DLNS-based processor architecture. This CPU takes advantage of a relatively simple architecture and a well designed organisation which greatly improves the implementation of many DSP algorithms. An assembly programme is also written to implement a 2DLNS-based filterbank architecture. This implementation demonstrates the efficiency and ease of use of 2DLNS CPU in real applications.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score0.674

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 science0.0020.000
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 head0.021
GPT teacher head0.271
Teacher spread0.250 · 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