Scalable and Reliable Data Broadcast with Kascade

Stéphane Martin 1 Tomasz Buchert 1 Pierric Willemet 1 Olivier Richard 2 Emmanuel Jeanvoine 1 Lucas Nussbaum 1, *
* Auteur correspondant
1 ALGORILLE - Algorithms for the Grid
Inria Nancy - Grand Est, LORIA - NSS - Department of Networks, Systems and Services
2 MESCAL - Middleware efficiently scalable
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : Many large scale scientific computations or Big Data analysis require the distribution of large amounts of data to each machine involved. That distribution of data often has a key role in the overall performance of the operation. In this paper, we present Kascade, a solution for the broadcast of data to a large set of compute nodes. We evaluate Kascade using a set of large scale experiments in a variety of experimental settings, and show that Kascade: (1) achieves very high scalability by organizing nodes in a pipeline; (2) can almost saturate a 1~Gbit/s network, even at large scale; (3) handles failures of nodes during the transfer gracefully thanks to a fault-tolerant design.
Type de document :
Communication dans un congrès
HPDIC - International Workshop on High Performance Data Intensive Computing, in conjunction with IEEE IPDPS 2014, May 2014, Phoenix, United States. 2014
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https://hal.inria.fr/hal-00957671
Contributeur : Lucas Nussbaum <>
Soumis le : lundi 23 juin 2014 - 17:06:07
Dernière modification le : mercredi 29 novembre 2017 - 15:59:55
Document(s) archivé(s) le : mardi 11 avril 2017 - 08:12:46

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  • HAL Id : hal-00957671, version 3

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Stéphane Martin, Tomasz Buchert, Pierric Willemet, Olivier Richard, Emmanuel Jeanvoine, et al.. Scalable and Reliable Data Broadcast with Kascade. HPDIC - International Workshop on High Performance Data Intensive Computing, in conjunction with IEEE IPDPS 2014, May 2014, Phoenix, United States. 2014. 〈hal-00957671v3〉

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