MétaCan
Menu
Back to cohort
Record W2158447309 · doi:10.1109/pacrim.1999.799579

DSP-RAM: A logic-enhanced memory architecture for communication signal processing

2003· article· en· W2158447309 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
TopicAdvanced Data Compression Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceDigital signal processingSIMDComputer architectureDigital signal processorKey (lock)Very long instruction wordCoding (social sciences)Computer hardwareSignal processingEmbedded systemParallel computingOperating system

Abstract

fetched live from OpenAlex

In this paper a new parallel computational RAM (C/spl middot/RAM) architecture, called DSP-RAM, is proposed to speed up a class of digital signal processing (DSP) algorithms in telecommunications. The proposed architecture integrates memory and single instruction stream, multiple data stream (SIMD) parallel processing into a single chip. Key elements of the architecture were designed to verify their cost in silicon area. A software simulator was written in C++ to evaluate the performance of DSP-RAM implementations of critical components in the ITU G.728 voice coding standard.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.802
Threshold uncertainty score0.484

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 science0.0010.000
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 head0.027
GPT teacher head0.306
Teacher spread0.279 · 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

Citations8
Published2003
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Data Compression TechniquesFrench-language works237,207