Mixed Data-Parallel Scheduling for Distributed Continuous Integration - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2012

Mixed Data-Parallel Scheduling for Distributed Continuous Integration

Résumé

In this paper, we consider the problem of schedul- ing a special kind of mixed data-parallel applications arising in the context of continuous integration. Continuous integration (CI) is a software engineering technique, which consists in re- building and testing interdependent software components as soon as developers modify them. The CI tool is able to provide quick feedback to the developers, which allows them to fix the bug soon after it has been introduced. The CI process can be described as a DAG where nodes represent package build tasks, and edges represent dependencies among these packages; build tasks themselves can in turn be run in parallel. Thus, CI can be viewed as a mixed data-parallel application. A crucial point for a successful CI process is its ability to provide quick feedback. Thus, makespan minimization is the main goal. Our contribution is twofold. First we provide and analyze a large dataset corresponding to a build DAG. Second, we compare the performance of several scheduling heuristics on this dataset.
Fichier principal
Vignette du fichier
buildsoumis.pdf (187.53 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00684220 , version 1 (30-03-2012)

Identifiants

  • HAL Id : hal-00684220 , version 1

Citer

Olivier Beaumont, Nicolas Bonichon, Ludovic Courtès, Xavier Hanin, Eelco Dolstra. Mixed Data-Parallel Scheduling for Distributed Continuous Integration. Heterogeneity in Computing Workshop, in IPDPS 2012, May 2012, Shangaï, China. ⟨hal-00684220⟩
230 Consultations
366 Téléchargements

Partager

Gmail Facebook X LinkedIn More