可扩展和可靠的数据广播与Kascade

Stéphane Martin, Tom Buchert, Pierric Willemet, Olivier Richard, E. Jeanvoine, L. Nussbaum
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引用次数: 0

摘要

许多大规模的科学计算或大数据分析需要将大量数据分布到相关的每台机器上。数据的分布通常在操作的整体性能中起着关键作用。在本文中,我们提出了Kascade,一种将数据广播到大型计算节点集的解决方案。我们在各种实验设置中使用一组大规模实验来评估Kascade,并表明Kascade:(1)通过在管道中组织节点实现非常高的可扩展性;(2)即使在大规模情况下,也几乎可以使1 Gbit/s的网络饱和;(3)采用容错设计,优雅地处理传输过程中节点的故障。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scalable and Reliable Data Broadcast with Kascade
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.
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