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Record W1543756834

Simulating DB2 buffer pool management

2000· article· en· W1543756834 on OpenAlexaff
Wenguang Wang, Richard B. Bunt

Bibliographic record

VenueConference of the Centre for Advanced Studies on Collaborative Research · 2000
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsComputer scienceBuffer (optical fiber)Storage managementTRACE (psycholinguistics)CacheDisk bufferDatabaseCircular bufferChannel (broadcasting)Operating systemComputer networkTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Storage management is an important part of any DBMS. The buffer pool in DB2 is used to cache the disk pages of the database, and its management algorithm can significantly affect performance. In order to investigate performance issues relating to the buffer pool management algorithm, a trace of buffer pool requests was collected and a trace-driven simulator was developed so that the impact of various parameters of the buffer pool management algorithm could be investigated under controlled circumstances. Relationships among different activities competing for storage space and the I/O channel are examined, and some issues affecting performance are identified.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.104
GPT teacher head0.406
Teacher spread0.302 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2000
Admission routes1
Has abstractyes

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