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Record W3103925037

237 Gbit/s unrolled hardware polar decoder

2015· article· en· W3103925037 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

VenueEspace ÉTS (ETS) · 2015
Typearticle
Languageen
FieldComputer Science
TopicError Correcting Code Techniques
Canadian institutionsÉcole de Technologie SupérieureMcGill University
Fundersnot available
KeywordsDecoding methodsPolarPolar codeComputer scienceField-programmable gate arraySoft-decision decoderThroughputGigabitComputer hardwareArchitectureCode (set theory)Parallel computingAlgorithmTelecommunicationsSet (abstract data type)Physics
DOInot available

Abstract

fetched live from OpenAlex

In this letter we present a new architecture for a polar decoder using a reduced complexity successive cancellation decoding algorithm. This novel fully-unrolled, deeply-pipelined architecture is capable of achieving a coded throughput of over 237 Gbps for a (1024,512) polar code implemented using an FPGA. This decoder is two orders of magnitude faster than state-of-the-art polar decoders.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.771
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.026
GPT teacher head0.280
Teacher spread0.255 · 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