No abstract

13/01/15 meb. Accepted version, Ok to add

This paper is devoted to scheduling a large collection of independent tasks onto heterogeneous clusters. The tasks depend upon (input) files which initially reside on a master processor. A given file may well be shared by several tasks. The role of the master is to distribute the files to the processors, so that they can execute the tasks. The objective for the master is to select which file to send to which slave, and in which order, so as to minimize the total execution time. The contribution of this paper is twofold. On the theoretical side, we establish complexity results that assess the difficulty of the problem. On the practical side, we design several new heuristics, which are shown to perform as efficiently as the best heuristics in [H. Casanova, A. Legrand, D. Zagorodnov, F. Berman, Heuristics for scheduling parameter sweep applications in Grid environments, in: Ninth Heterogeneous Computing Workshop, IEEE Computer Society Press, Silver Spring, MD, 2000, pp. 349-363; Berman, Using simulation to evaluate scheduling heuristics for a class of applications in Grid environments, Research Report RR-1999-46, LIP, ENS Lyon, France, 1999 although their cost is an order of magnitude lower.

In this paper, we revisit traditional checkpointing and rollback recovery strategies, with a focus on silent data corruption errors. Contrarily to fail-stop failures, such latent errors cannot be detected immediately, and a mechanism to detect them must be provided. We consider two models: (i) errors are detected after some delays following a probability distribution (typically, an Exponential distribution); (ii) errors are detected through some verification mechanism. In both cases, we compute the optimal period in order to minimize the waste, i.e., the fraction of time where nodes do not perform useful computations. In practice, only a fixed number of checkpoints can be kept in memory, and the first model may lead to an irrecoverable failure. In this case, we compute the minimum period required for an acceptable risk. For the second model, there is no risk of irrecoverable failure, owing to the verification mechanism, but the corresponding overhead is included in the waste. Finally, both models are instantiated using realistic scenarios and application/architecture parameters.

This work provides an analysis of checkpointing strategies for minimizing expected job execution times in an environment that is subject to processor failures. In the case of both sequential and parallel jobs, we give the optimal solution for exponentially distributed failure inter-arrival times, which, to the best of our knowledge, is the first rigorous proof that periodic checkpointing is optimal. For non-exponentially distributed failures, we develop a dynamic programming algorithm to maximize the amount of work completed before the next failure, which provides a good heuristic for minimizing the expected execution time. Our work considers various models of job parallelism and of parallel checkpointing overhead. We first perform extensive simulation experiments assuming that failures follow Exponential or Weibull distributions, the latter being more representative of real-world systems. The obtained results not only corroborate our theoretical findings, but also show that our dynamic programming algorithm significantly outperforms previously proposed solutions in the case of Weibull failures. We then discuss results from simulation experiments that use failure logs from production clusters. These results confirm that our dynamic programming algorithm significantly outperforms existing solutions for real-world clusters.

No abstract

In this article, we present a unified model for several well-known checkpoint/restart protocols. The proposed model is generic enough to encompass both extremes of the checkpoint/restart space, from coordinated approaches to a variety of uncoordinated checkpoint strategies (with message logging). We identify a set of crucial parameters, instantiate them and compare the expected efficiency of the fault tolerant protocols, for a given application/platform pair. We then propose a detailed analysis of several scenarios, including some of the most powerful currently available HPC platforms, as well as anticipated Exascale designs. The results of this analytical comparison are corroborated by a comprehensive set of simulations. Altogether, they outline comparative behaviors of checkpoint strategies at very large scale, thereby providing insight that is hardly accessible to direct experimentation. Un modèle unifié pour l'évaluation des protocoles de checkpointà très largeéchelle Résumé :Nous présentons ici un modèle unifié de plusieurs protocoles de sauvegarde de points de reprise (checkpoints) et de redémarrage. Le modèle proposé est suffisamment générique pour contenir les deux extrêmes des techniques de checkpoint/restart, d'une approche coordonnéeà toute une famille de stratégies non-coordonnées (avec enregistrement de messages).Nous identifions un ensemble de paramètres cruciaux, les instancions et comparons l'espérance de l'efficacité des protocoles de tolérance aux pannes, pour un couple donné application/plate-forme. Nous proposons une analyse détaillée de plusieurs scénarios, incluant certaines des plates-formes de calcul existantes les plus puissantes, ainsi que des anticipations sur les futures plates-formes exascale. Les résultats de cette analyse sont corroborés par un ensemble de simulations. Ensemble, ces résultats illustrent le comportement relatif des différentes stratégiesà largeéchelle, fournissant des enseignements qu'il serait très difficile, voire impossible, d'obtenir par l'expérimentation directe.

This paper deals with the impact of fault prediction techniques on checkpointing strategies. We extend the classical first-order analysis of Young and Daly in the presence of a fault prediction system, characterized by its recall and its precision. In this framework, we provide an optimal algorithm to decide when to take predictions into account, and we derive the optimal value of the checkpointing period. These results allow to analytically assess the key parameters that impact the performance of fault predictors at very large scale.Comment: Supported in part by ANR Rescue. Published in Journal of Parallel and Distributed Computing. arXiv admin note: text overlap with arXiv:1207.693