TOWARDS GENERIC SYSTEM OBSERVATION MANAGEMENT

Едно от най-големите предизвикателства на информатиката е да създава правилно работещи компютърни системи. За да се гарантира коректността на една система, по време на дизайн могат де се прилагат формални методи за моделиране и валидация. Този подход е за съжаление труден и скъп за приложение при мнозинството компютърни системи. Алтернативният подход е да се наблюдава и анализира поведението на системата по време на изпълнение след нейното създаване. В този доклад представям научната си работа по въпроса за наблюдение на копютърните системи. Предлагам един общ поглед на три основни страни на проблема: как трябва да се наблюдават компютърните системи, как се използват наблюденията при недетерминистични системи и как се работи по отворен, гъвкав и възпроизводим начин с наблюдения.One of the biggest challenges in computer science is to produce correct computer systems. One way of ensuring system correction is to use formal techniques to validate the system during its design. This approach is compulsory for critical systems but difficult and expensive for most computer systems. The alternative consists in observing and analyzing systems' behavior during execution. In this thesis, I present my research on system observation. I describe my contributions on generic observation mechanisms, on the use of observations for debugging nondeterministic systems and on the definition of an open, flexible and reproducible management of observations.Un des plus grands défis de l'informatique est de produire des systèmes corrects. Une manière d'assurer la correction des systèmes est d'utiliser des méthodes formelles de modélisation et de validation.Obligatoire dans le domaine des systèmes critiques, cette approche est difficile et coûteuse à mettre en place dans la plupart des systèmes informatiques.L'alternative est de vérifier le comportement des systèmes déjà développés en observant et analysant leur comportement à l'exécution.Ce mémoire présente mes contributions autour de l'observation des systèmes. Il discute de la définition de mécanismes génériques d'observation, de l'exploitation des observations pour le débogage de systèmes non déterministes et de la gestion ouverte, flexible et reproductible d'observations

Automatic benchmark profiling through advanced workflow-based trace analysis

International audienceBenchmarking has proven to be crucial for the investigation of the behavior and performances of a system. However, the choice of relevant benchmarks still remains a challenge. To help the process of comparing and choosing among benchmarks, we propose a solution for automatic benchmark profiling. It computes unified benchmark profiles reflecting benchmarks' duration, function repartition, stability, CPU efficiency, parallelization, and memory usage. Our approach identifies the needed system information for profile computation and collects it from execution traces captured without benchmark code modifications. It structures profile computation as a reproducible workflow for automatic trace analysis, which efficiently manages important trace volumes. In this paper, we report on the design and the implementation of our approach, which involves the collection and analysis of about 500 GB of trace data coming from 2 different platforms (an x86 desktop machine and the Juno SoC board). The computed benchmark profiles provide valuable insights about the benchmarks' behavior and help compare different benchmarks on the same platform as well as the behavior of the same benchmark on different platforms