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Record W1780371484 · doi:10.5555/1960475.1960478

Capo: recapitulating storage for virtual desktops

2011· article· en· W1780371484 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
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceOperating systemVirtual machineComputer data storageFile systemEmbedded system

Abstract

fetched live from OpenAlex

Shared storage underlies most enterprise VM deployments because it is an established technology that administrators are familiar with and because it good job of protecting data. However, shared storage is also very expensive to scale. This paper describes Capo 1, a transparent and persistent block request proxy for virtual machine disk images. Capo reduces the load on shared storage by using local disks as persistent caches, using multicastbased preloading to broadcast read results across a cluster, and by imposing differential durability – dividing a VM’s file system into regions of varying writeback frequency. We motivate the system’s design through the analysis of a week-long trace of 55 production virtual desktops and then describe and evaluate our implementation. Capo is particularly well suited for virtual desktop deployments, in which large numbers of VMs boot from a small number of “gold master ” images and are refreshed on a periodic basis. 1

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.380
Threshold uncertainty score0.415

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 communication0.0000.001
Open science0.0010.000
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 head0.059
GPT teacher head0.262
Teacher spread0.203 · 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

Citations42
Published2011
Admission routes1
Has abstractyes

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