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Record W2744966218 · doi:10.1109/newcas.2017.8010168

FPGA implementation of Token-based Self-timed processors: A case study

2017· article· en· W2744966218 on OpenAlex
Mickael Fiorentino, Yvon Savaria, Claude Thibeault

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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsÉcole de Technologie SupérieurePolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsField-programmable gate arrayComputer scienceSecurity tokenEmbedded systemAsynchronous communicationFPGA prototypeDigital signal processingComputer architectureComputer hardwareOperating systemComputer network

Abstract

fetched live from OpenAlex

This paper describes an on-going work aiming at using FPGAs as a fast prototyping environment for Token-based Self-timed processors, inspired by the Octasic asynchronous design technique. Originally developed for Digital Signal Processing, this design technique is adapted here for an FPGA-based general purpose processor. The paper emphasizes improvements to existing FPGA implementation methodologies that address the incompatibilities between self-timed timing schemes and synchronous oriented place and route engines. It also presents a prototyping platform based on a Xilinx ZC706 board that enables functional verification, as well as runtime performance and power consumption measurements, of the reported Token-based Self-timed processor.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.482

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 communication0.0000.001
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 head0.037
GPT teacher head0.370
Teacher spread0.334 · 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

Citations2
Published2017
Admission routes2
Has abstractyes

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