MétaCan
Menu
Back to cohort
Record W1972270193 · doi:10.5555/1404595.1404620

Improving the performance of Apache web server

2007· article· en· W1972270193 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

VenueSpring Simulation Multiconference · 2007
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer scienceOperating systemInstruction prefetchWeb serverCachePage cacheWeb pageStatic web pageDatabaseWorld Wide WebCache algorithmsCPU cacheThe Internet

Abstract

fetched live from OpenAlex

The purpose of this research is to improve the performance of the Apache HTTP Server for serving web pages which include embedded objects, such as images or multimedia components. By prefetching the embedded objects of a web page from server disk to its cache memory, we reduce page load latency without modifying current web protocols.We have implemented this strategy within the Apache HTTP Server that is referred to in this paper as modified Apache. Apache HTTP Server is a popular open source web server. In this paper, we present the strategy that we used to prefetch embedded objects in modified Apache from disk into main memory, and report on the performance achieved in trace driven simulations.The performance was measured by processing a log file from IRCache to simulate realistic fetches on an object-by-object basis. The memory cache hit ratio and byte hit ratio were recorded for each object accessed through normal and modified Apache, and compared.

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)0.000
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: Empirical
Teacher disagreement score0.560
Threshold uncertainty score0.359

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 communication0.0000.001
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 head0.029
GPT teacher head0.276
Teacher spread0.247 · 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