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On the Root Causes of Cross-Application I/O Interference in HPC Storage Systems

机译:关于HPC存储系统跨应用I / O干扰的根本原因

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As we move toward the exascale era, performance variability in HPC systems remains a challenge. I/O interference, a major cause of this variability, is becoming more important every day with the growing number of concurrent applications that share larger machines. Earlier research efforts on mitigating I/O interference focus on a single potential cause of interference (e.g., the network). Yet the root causes of I/O interference can be diverse. In this work, we conduct an extensive experimental campaign to explore the various root causes of I/O interference in HPC storage systems. We use microbenchmarks on the Grid'5000 testbed to evaluate how the applications' access pattern, the network components, the file system's configuration, and the backend storage devices influence I/O interference. Our studies reveal that in many situations interference is a result of bad flow control in the I/O path, rather than being caused by some single bottleneck in one of its components. We further show that interference-free behavior is not necessarily a sign of optimal performance. To the best of our knowledge, our work provides the first deep insight into the role of each of the potential root causes of interference and their interplay. Our findings can help developers and platform owners improve I/O performance and motivate further research addressing the problem across all components of the I/O stack.
机译:随着我们走向ExaScale时代,HPC系统的性能变异仍然是一个挑战。 I / O干扰,这种变异性的主要原因,每天都变得越来越重要,越来越多的并发应用程序,这些应用程序共享更大的机器。早期的研究努力减轻I / O干扰专注于单一的干扰原因(例如,网络)。然而,I / O干扰的根本原因可能是多样的。在这项工作中,我们进行了广泛的实验活动,探讨了HPC存储系统中I / O干扰的各种根本原因。我们在Grid'5000上使用Microbenchmarks测试平台来评估应用程序的访问模式,网络组件,文件系统的配置和后端存储设备如何影响I / O干扰。我们的研究表明,在许多情况下,干扰是I / O路径中的错误控制的结果,而不是由其组件之一中的一些单个瓶颈引起的。我们进一步表明,无干扰行为不一定是最佳性能的迹象。据我们所知,我们的工作提供了第一次深入了解每个潜在根源的干扰和相互作用的作用。我们的调查结果可以帮助开发人员和平台所有者提高I / O性能,并激发进一步的研究解决I / O堆栈的所有组件的问题。

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