MétaCan
Menu
Back to cohort
Record W2329594518 · doi:10.1109/tns.2014.2369417

On Extra Delays Affecting I/O Blocks of an SRAM-Based FPGA Due to Ionizing Radiation

2014· article· en· W2329594518 on OpenAlexaff
Fatima Zahra Tazi, Claude Thibeault, Yvon Savaria, Simon Pichette, Yves Audet

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2014
Typearticle
Languageen
FieldEngineering
TopicRadiation Effects in Electronics
Canadian institutionsPolytechnique MontréalÉcole de Technologie Supérieure
Fundersnot available
KeywordsField-programmable gate arrayEmulationStatic random-access memoryFault injectionVirtexIrradiationEmbedded systemComputer scienceSingle event upsetPhysicsComputer hardwareSoftware

Abstract

fetched live from OpenAlex

This paper aims at characterizing additional delays induced by ionizing radiation in Input/Output Blocks (IOBs) of Static Random-Access Memory Based Field Programmable Gate Arrays (SRAM-Based FPGAs), using measurement techniques based on ring oscillators (ROs). This characterization effort includes experiments performed with proton irradiation at TRIUMF on Xilinx devices (Virtex-5 and Artix-7). Results from these irradiation experiments show that RO period variations, up to 6.2 ns for Virtex-5 and 3.8 ns for Artix-7, could be induced. These results also reveal that the occurrence rate of events (namely delays and breaks) affecting ROs implemented in IOBs is approaching the rate observed when ROs are implemented in the FPGA core, even if the number of configuration bits dedicated to IOBs is significantly lower than for the FPGA core. These radiation test experiments are supported by emulation using similar RO-based measurement techniques and Xilinx SEU Controller as a fault injector. The fault injection experiments allow a better understanding of the behaviour of IOBs affected by additional delays due to configuration bit flips, which in many cases is similar to what can be observed with an incorrect parameter setting. Emulation experiments also reveal that many of the events modifying IOB behaviour are found to require multiple bit fault injection.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.218
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations13
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Nuclear ScienceSame topicRadiation Effects in ElectronicsFrench-language works237,207