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Monitoring High Performance Networks in Large-scale Clusters

机译:监视大型集群中的高性能网络

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The number of large-scale clusters is rising. They are included into Grids or become key components o f large structures. As more users and projects rely 071 HPC clusters, high availability and security are requirements for a fast growing adoption and use. I n this paper, ute focus o n high performance networks. All HPC clusters are built o n top of them. We demonstrate that classical instrumentation are ineficient in HPC environment, they do not scale or cause a significant loss of performance. Based 071. this fact, we highlight clusters properties: nodes have assigned roles and are coupled at various levels. Moreover, we study the main characteristics of resource usage for each type of node and propose a n instrumentation that can be effectively deployed. It results in fine-grained mechanisms adapted to system architecture and performance constraints.. Relevant information is collected over time. Two properties are verified online and dynamically: coherency and containment. Each induces a type of verification and both aim at reducin,g recovery time from failure and security risk of a whole cluster. We illustrate our. rnethodology o n QsNet network and provide a way t o increase safety of high performance networks and clusters.
机译:大规模集群的数量正在上升。它们包含在网格中或成为大型结构的关键组件。随着更多用户和项目依靠071 HPC集群,高可用性和安全性是快速增长的采用和使用的要求。我本文侧重于高性能网络。所有HPC集群都建立在其中的顶部。我们证明,古典仪器在HPC环境中均有,它们不扩展或导致损失的性能。基于071.这一事实,我们突出了群集属性:节点已分配角色并以各个级别耦合。此外,我们研究了每种节点的资源用法的主要特征,并提出了可以有效地部署的N仪器。它导致适用于系统架构和性能约束的细粒度机制。相关信息将随时间收集。两个属性在线验证并动态验证:一致性和遏制。每个每个验证类型和旨在从整个群集的故障和安全风险的reducin,g恢复时间。我们说明了我们的。 RNeTodology O N QSNet网络,提供了一种提高高性能网络和集群的安全性。

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    《》|2006年|P.32|共1页
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    Gadaud; F.;

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