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Record W2113863982 · doi:10.1002/cpe.3659

Dekker's mutual exclusion algorithm made RW‐safe

2015· article· en· W2113863982 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueConcurrency and Computation Practice and Experience · 2015
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThread (computing)Mutual exclusionCorrectnessAlgorithmComputer scienceTournamentParallel computingMathematicsTheoretical computer scienceOperating systemCombinatorics

Abstract

fetched live from OpenAlex

Summary Dekker's algorithm was thought to be safe in an environment without atomic reads or writes where bits flicker or scramble during simultaneous operations. A counter‐example is presented showing Dekker's algorithm is unsafe without atomic read. A modification to the original algorithm is presented making it RW‐safe, allowing threaded systems to be built on low cost/power hardware without atomic read/write. Correctness is verified by means of invariants and UNITY logic. A performance comparison is made for several two‐thread software mutual‐exclusion algorithms to see if the RW‐safe Dekker is competitive. A subset of the two‐thread solutions are then compared in two N ‐thread tournament algorithms. The performance results show that the additional checks in the RW‐safe Dekker do not disadvantage the algorithm in comparison with other two‐thread algorithms. The RW‐safe N ‐thread tournament algorithms are competitive with the hardware‐assisted Mellor‐Crummey and Scott algorithm. Copyright © 2015 John Wiley & Sons, Ltd.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.614

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 communication0.0000.002
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 head0.034
GPT teacher head0.325
Teacher spread0.291 · 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