Fault Tolerance in Cluster Computing System

Ashwini B. Patil, Ankit Shah, Sheetal Gaikwad, Akassh A. Mishra, S. S. Kohli, Sudhir N. Dhage
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引用次数: 3

Abstract

With advancement in technology, the needs for high performance computing are increasing tremendously. Cluster computing has developed due to the availability of high performance cost effective processors and high speed networks. The long-term trend in High performance computing requires increasing number of nodes in parallel computing platforms. This however entails a higher failure probability. The Message Passing Paradigm (MPI) is currently the programming paradigm and communication library most commonly used on parallel computing platforms. MPI applications may get stopped at any time due to unpredictable failures during execution. In our paper we propose an efficient fault tolerant approach for MPI system in an asymmetric cluster computing environment. In this paper, we use centralized logging process. In the approach proposed, we use message logging for message losses. The process has three main parts failure detection, failure recovery and overload detection. Our System maintains monitor nodes for all nodes in cluster, the difference being all monitor nodes can work as a cluster node even when the system is functioning properly and not just at the time of node failure.
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集群计算系统中的容错
随着技术的进步,对高性能计算的需求正在急剧增加。由于高性能、低成本的处理器和高速网络的可用性,集群计算得到了发展。高性能计算的长期发展趋势要求并行计算平台中的节点数量不断增加。然而,这需要更高的失败概率。消息传递范式(Message Passing Paradigm, MPI)是目前并行计算平台上最常用的编程范式和通信库。MPI应用程序可能在任何时候由于执行过程中不可预测的故障而停止。本文提出了一种非对称集群计算环境下MPI系统的高效容错方法。在本文中,我们使用集中式日志记录流程。在建议的方法中,我们使用消息日志记录消息丢失。该过程主要包括故障检测、故障恢复和过载检测三个部分。我们的系统为集群中的所有节点维护监视节点,不同之处在于,即使系统正常运行,所有监视节点也可以作为集群节点工作,而不仅仅是在节点故障时。
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