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dCache with tape storage for High Energy Physics applications

2010· article· en· W2089778585 on OpenAlexafffundabout
Arun Agarwal, R Enge, K Fransham, Edward W. Kolb, Colin Leavett-Brown, D Leske, K Lewall, H Reitsma, E Rempel, R. Sobie

Bibliographic record

VenueJournal of Physics Conference Series · 2010
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsInstitute of Particle PhysicsUniversity of Victoria
FundersSLAC National Accelerator LaboratoryDeutsches Elektronen-SynchrotronFermilabCERNUniversity of Victoria
KeywordsInterface (matter)Computer data storageComputer scienceOperating systemConsistency (knowledge bases)Energy storageDatabaseStorage area networkNode (physics)Magnetic tapeComputer hardwarePhysics

Abstract

fetched live from OpenAlex

An interface between dCache and the local Tivoli Storage Manager (TSM) tape storage facility has been developed at the University of Victoria (UVic) for High Energy Physics (HEP) applications. The interface is responsible for transferring the data from disk pools to tape and retrieving data from tape to disk pools. It also checks the consistency between the PNFS filename space and the TSM database. The dCache system, consisting of a single admin node with two pool nodes, is configured to have two read pools and one write pool. The pools are attached to the TSM storage that has a capacity of about 100TB. This system is being used in production at UVic as part of a Tier A site for BaBar Tau analysis. An independent dCache system is also in production for the storage element (SE) of the ATLAS experiment as a part of Canadian Tier-2 sites. This system does not currently employ a tape storage facility, however, it can be added in the future.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0040.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0380.015

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 head0.242
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

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Citations1
Published2010
Admission routes3
Has abstractyes

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