MétaCan
Menu
Back to cohort
Record W2785688695 · doi:10.1109/rtss.2017.00050

Work-in-Progress: Isochronous Execution Models for Mixed-Criticality Systems on Parallel Processors

2017· article· en· W2785688695 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
FieldEngineering
TopicScheduling and Optimization Algorithms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceCorrectnessMixed criticalityPredictabilityGeneralityScheduling (production processes)Parallel computingCriticalityJob shop schedulingProcessor schedulingRedundancy (engineering)Execution timeDistributed computingExecution modelEmbedded systemResource (disambiguation)AlgorithmOperating systemMathematical optimization

Abstract

fetched live from OpenAlex

We propose redundancy-based execution models to address the reliability and correctness of safety/time-critical applications, and in particular, mixed-criticality systems. In our models, every job has one or more (possibly identical) versions, and all versions of a job are to run isochronously on multiple parallel machines in a lockstep fashion. The redundant machines act as monitoring coprocessors, and the execution of a job is deemed successful as soon as one of its versions completes within its worst-case execution time estimate, at which point we may terminate all the other versions. Doing so e ectively increases the chance that a job completes successfully and thus provides timing guarantees in the form of increased predictability. We present several allocation and scheduling problems with varying levels of generality, with the objective of minimizing the maximum makespan across all processors.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score0.504

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 communication0.0000.000
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 head0.030
GPT teacher head0.277
Teacher spread0.247 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicScheduling and Optimization AlgorithmsFrench-language works237,207