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Record W2736699952 · doi:10.1145/3087801.3087837

Randomized Abortable Mutual Exclusion with Constant Amortized RMR Complexity on the CC Model

2017· preprint· en· W2736699952 on OpenAlexaff
George Giakkoupis, Philipp Woelfel

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMutual exclusionConstant (computer programming)DeadlockBinary logarithmAmortized analysisMathematicsComputer scienceTheoretical computer scienceComputational complexity theoryCombinatoricsAlgorithmDiscrete mathematicsData structureDistributed computing

Abstract

fetched live from OpenAlex

We present an abortable mutual exclusion algorithm for the cache-coherent (CC) model with atomic registers and CAS objects. The algorithm has constant expected amortized RMR complexity in the oblivious adversary model and is deterministically deadlock-free. This is the first abortable mutual exclusion algorithm that achieves o(\log n/\log\log n) RMR complexity.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0030.002
Research integrity0.0000.001
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 head0.070
GPT teacher head0.291
Teacher spread0.221 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations10
Published2017
Admission routes1
Has abstractyes

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