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FPGA Implementation for the Multiplexed and Pipelined Building Blocks of Higher Radix-2<sup>k</sup> FFT

2020· article· en· W3016874168 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
TopicDigital Filter Design and Implementation
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsFast Fourier transformComputer scienceThroughputField-programmable gate arrayMultiplexingLatency (audio)Signal processingParallel computingOrthogonal frequency-division multiplexingComputer hardwareComputationDigital signal processingWirelessAlgorithmTelecommunications

Abstract

fetched live from OpenAlex

Fast Fourier transform (FFT) is one of the fundamental processing block used in many signal processing applications (i.e. for orthogonal frequency division multiplexing in wireless telecommunication). Therefore, every proposal to reduced latency, resources or accuracy errors of FFT implementation counts. This paper proposes the implementation of the butterfly processing elements (BPE) where the concept of the radix-r butterfly computation has been formulated as the combination of α radix-2 butterflies implemented in parallel. An efficient FFT implementation is feasible using our proposed multiplexed and pipelined BPE. Compared to a state-of-the-art reference based on pipelined and parallel structure FFTs, and FPGA based implementation reveals that the maximum throughput is improved by a factor of 1.3 for a 256-point FFT and reach a throughput of 2680 MSps on Virtex-7. The analysis extends to touch on key performance measurements metrics such as throughput, latency and resource utilization.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.899
Threshold uncertainty score0.302

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 head0.049
GPT teacher head0.313
Teacher spread0.264 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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