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Record W2981413263 · doi:10.1145/3341301.3359640

An analysis of performance evolution of Linux's core operations

2019· article· en· W2981413263 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 Toronto
Fundersnot available
KeywordsComputer scienceLinux kernelScalabilityOperating systemOverhead (engineering)Multi-core processorSystem callWorkloadKernel (algebra)Context switchLatency (audio)Simple (philosophy)Context (archaeology)Distributed computingTelecommunications

Abstract

fetched live from OpenAlex

This paper presents an analysis of how Linux's performance has evolved over the past seven years. Unlike recent works that focus on OS performance in terms of scalability or service of a particular workload, this study goes back to basics: the latency of core kernel operations (e.g., system calls, context switching, etc.). To our surprise, the study shows that the performance of many core operations has worsened or fluctuated significantly over the years. For example, the select system call is 100% slower than it was just two years ago. An in-depth analysis shows that over the past seven years, core kernel subsystems have been forced to accommodate an increasing number of security enhancements and new features. These additions steadily add overhead to core kernel operations but also frequently introduce extreme slowdowns of more than 100%. In addition, simple misconfigurations have also severely impacted kernel performance. Overall, we find most of the slowdowns can be attributed to 11 changes.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.666
Threshold uncertainty score0.170

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.268
Teacher spread0.253 · 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

Citations29
Published2019
Admission routes1
Has abstractyes

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