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Record W2406137460

Integrating SSD Caching into Database Systems.

2014· article· en· W2406137460 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

VenueIEEE Data(base) Engineering Bulletin · 2014
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceCachePage cacheCache algorithmsCache pollutionCache coloringCache invalidationSmart CacheOperating systemWrite bufferDatabaseParallel computingCPU cache
DOInot available

Abstract

fetched live from OpenAlex

Flash-based solid state storage devices (SSDs) are now becoming commonplace in server environments. In this paper, we consider the use of SSDs as a persistent second-tier cache for database systems. We argue that it is desirable to change the behavior of the database system’s buffer cache when a second-tier SSD cache is used, so that the buffer cache is aware of which pages are in the SSD cache. We propose such an SSD-aware buffer cache manager, called GD2L. An interesting side effect of SSD-aware buffer cache management is that the rate with which a page will be evicted or written from the buffer cache will change when that page is moved into or out of the second-tier SSD cache. We also propose a technique, called CAC, for managing the contents of the second-tier cache. CAC is aware that moving pages into or out of the SSD cache will change their physical read and write rates. It anticipates these changes when making decisions about which pages to cache at the second tier.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.300
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0050.002
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 head0.017
GPT teacher head0.235
Teacher spread0.217 · 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