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Record W2171072232 · doi:10.1109/ccece.2007.379

Evaluating the Performance of CSB+-Trees on Multithreaded Architectures

2007· article· en· W2171072232 on OpenAlexaff
Layali Rashid, Wessam Hassanein

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceSpeedupMultithreadingPentiumParallel computingThread (computing)Simultaneous multithreadingYarnOperating systemDatabase

Abstract

fetched live from OpenAlex

Modern architectures have made considerable increases in processor speed and performance. However, database management systems (DBMSs) fall far short from achieving their ideal performance. DBMSs are widely used in almost every large organization. Therefore, it is important to achieve fast data retrieval and processing. Recent studies have shown that more than 50% of the execution time in database operations is spent waiting for data. CSB+-trees were introduced to speedup index structure operations, mainly the search and update. In this paper we propose a multithreading technique to utilize the two threads available in an Intel Pentium 4 Hyperthreaded (HT) platform. Our technique gains speedup ranging from 29% to 70% for dual-threaded CSB+-tree on an HT enabled platform compared to a single-thread version running on HT disabled architecture.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.512
Threshold uncertainty score0.181

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.049
GPT teacher head0.347
Teacher spread0.298 · 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 designSimulation or modeling
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

Citations1
Published2007
Admission routes1
Has abstractyes

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