Scalable and Reliable Data Broadcast with Kascade

Stéphane Martin; Tomasz Buchert; Pierric Willemet; Olivier Richard; Emmanuel Jeanvoine; Lucas Nussbaum

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, *}

* Corresponding author

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.

Document type :

Conference papers

Domain :

Computer Science [cs] / Distributed, Parallel, and Cluster Computing [cs.DC]

Complete list of metadatas

https://hal.inria.fr/hal-00957671
Contributor : Lucas Nussbaum <>
Submitted on : Monday, June 23, 2014 - 5:06:07 PM
Last modification on : Monday, July 8, 2019 - 3:09:15 PM
Long-term archiving on : Tuesday, April 11, 2017 - 8:12:46 AM

Scalable and Reliable Data Broadcast with Kascade

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Scalable and Reliable Data Broadcast with Kascade

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