Design and Comparison of Resilient Scheduling Heuristics for Parallel Jobs - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Rapport (Rapport De Recherche) Année : 2019

Design and Comparison of Resilient Scheduling Heuristics for Parallel Jobs

Résumé

This paper focuses on the resilient scheduling of parallel jobs on highperformance computing (HPC) platforms to minimize the overall completion time, or makespan. We revisit the problem by assuming that jobs are subject to transient or silent errors, and hence may need to be re-executed each time they fail to complete successfully. This work generalizes the classical framework where jobs are known offline and do not fail: in this classical framework, list scheduling that gives priority to longest jobs is known to be a 3-approximation when imposing to use shelves, and a 2-approximation without this restriction. We show that when jobs can fail, using shelves can be arbitrarily bad, but unrestricted list scheduling remains a 2-approximation. The paper focuses on the design of several heuristics, some list-based and some shelf-based, along with different priority rules and backfflling options. We assess and compare their performance through an extensive set of simulations, using both synthetic jobs and log traces from the Mira supercomputer.
Fichier principal
Vignette du fichier
rr9296.pdf (1.14 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02317464 , version 1 (16-10-2019)
hal-02317464 , version 2 (21-02-2020)

Identifiants

  • HAL Id : hal-02317464 , version 1

Citer

Anne Benoit, Valentin Le Fèvre, Padma Raghavan, Yves Robert, Hongyang Sun. Design and Comparison of Resilient Scheduling Heuristics for Parallel Jobs. [Research Report] RR-9296, Inria - Research Centre Grenoble – Rhône-Alpes. 2019, pp.1-29. ⟨hal-02317464v1⟩
90 Consultations
253 Téléchargements

Partager

Gmail Facebook X LinkedIn More