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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Lightweight Online Performance Monitoring and Tuning with Embedded Gossip
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Lightweight Online Performance Monitoring and Tuning with Embedded Gossip

机译：嵌入式八卦的轻量级在线性能监控和调整

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摘要

Understanding and tuning the performance of large-scale long-running applications is difficult, with both standard trace-based and statistical methods having substantial shortcomings that limit their usefulness. This paper describes a new performance monitoring approach called Embedded Gossip (EG) designed to enable lightweight online performance monitoring and tuning. EG works by piggybacking performance information on existing messages and performing information correlation online, giving each process in a parallel application a weakly consistent global view of the behavior of the entire application. To demonstrate the viability of EG, this paper presents the design and experimental evaluation of two different online monitoring systems and an online global adaptation system driven by Embedded Gossiping. In addition, we present a metric system for evaluating the suitability of an application to EG-based monitoring and adaptation, a general architecture for implementing EG-based monitoring systems, and a modified global commit algorithm appropriate for use in EG-based global adaptation systems. Together, these results demonstrate that EG is an efficient low-overhead approach for addressing a wide range of parallel performance monitoring tasks and that results from these systems can effectively drive online global adaptation.
机译：很难理解和调整大型长期运行的应用程序的性能，因为基于跟踪的标准方法和统计方法都存在严重缺陷，从而限制了它们的实用性。本文介绍了一种称为嵌入式八卦（EG）的新性能监视方法，旨在实现轻量级的在线性能监视和调整。 EG的工作原理是在现有消息上附带性能信息，并在线执行信息关联，从而为并行应用程序中的每个进程提供了整个应用程序行为的弱一致性全局视图。为了证明EG的可行性，本文介绍了两种不同的在线监测系统和由嵌入式闲聊驱动的在线全局适应系统的设计和实验评估。此外，我们提供了一种度量系统，用于评估应用程序对基于EG的监视和适应的适用性，用于实现基于EG的监视系统的通用体系结构，以及适用于基于EG的全局适应系统的改进的全局提交算法。这些结果加在一起表明EG是一种有效的低开销方法，可以解决各种各样的并行性能监视任务，并且这些系统的结果可以有效地推动在线全球适应。

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