Characterizing the temporal I/O behavior of an HPC application is a challenging task, but informing the system about it can be valuable for techniques such as I/O scheduling, burst buffer management, and many more, especially if provided online. In this work, we focus on the most commonly discussed temporal I/O behavior aspect: the periodicity of I/O. Specifically, we propose to examine the periodicity of the I/O phases using a signal processing technique, namely the Discrete Fourier Transform (DFT). Our approach, named FTIO, also provides metrics that quantify how far from being periodic the signal is, and hence represent yield confidence in the DFT-obtained period. We validate our approach with large-scale experiments on a productive system and examine its limitations extensively.

翻译：表征高性能计算应用中I/O的时间行为是一项具有挑战性的任务，但向系统通报此类信息（尤其是提供在线信息）对I/O调度、突发缓冲管理等多种技术具有重要价值。本研究聚焦于最常被讨论的I/O时间行为特征——I/O周期性。具体而言，我们提出采用信号处理技术——即离散傅里叶变换（DFT）——来检测I/O阶段的周期性。所提方法（命名为FTIO）同时提供量化指标，用以衡量信号偏离周期性的程度，进而表示对DFT获取周期的可信度。我们在生产系统上通过大规模实验验证了该方法，并对其局限性进行了深入探讨。