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Record W1898554878 · doi:10.1109/acssc.1988.754650

RAM-JET: Towards The Removal Of Multiplicative Compleidty In Digital Signal Processingvlst Arclutectures

2005· article· en· W1898554878 on OpenAlexaff
G.A. Jullien, B W Erickson, William C. Miller

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCoding theory and cryptography
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsComputer scienceOverhead (engineering)AdderDigital signal processingPipeline (software)Very-large-scale integrationParallel computingMultiplication (music)Systolic arrayDot productBinary numberThroughputComputer hardwareAlgorithmArithmeticEmbedded systemMathematicsLatency (audio)

Abstract

fetched live from OpenAlex

The concept of a programmable systolic cell is introduced that allows finite ring arithmetic to be performed using bit-level systolic arrays. The motivation for this work is the recent introduction of a fixed coefficient bit-level inner product step processor operating over a finite ring (BIPSPm). From design and fabrication experiments performed on this cell, it is clear that it represents a major step forward in the implementation of very high speed fine-grained DSP algorithms. The remarkable properties of the cell are the ability to implement fixed product multiplication with only twice the area overhead of a bit-level binary adder, and yet provide operation at slightly higher throughput rates. The cell also has low overhead associated with error detection, and an entire array of an arbitrary number of cells in a linear pipeline, can be tested with only 32 test vectors in the time taken to pass the vectors through the array. This paper discusses a programmable system that will operate with a modified cell, to allow arbitrary algorithms to be implemented without incurring the overhead associated with general multiplication. Rather than seek algorithms that minimize multiplication, we can rather seek algorithms that provide a homogeneous VLSI structure.

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.807
Threshold uncertainty score0.299

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.252
Teacher spread0.230 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations0
Published2005
Admission routes1
Has abstractyes

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