Input/Output Characteristics of Scalable Parallel Applications

Phyllis E. Crandall, R. Aydt, A. Chien, D. Reed
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引用次数: 210

Abstract

Rapid increases in computing and communication performance are exacerbating the long-standing problem of performance-limited input/output. Indeed, for many otherwise scalable parallel applications. input/output is emerging as a major performance bottleneck. The design of scalable input/output systems depends critically on the input/output requirements and access patterns for this emerging class of large-scale parallel applications. However, hard data on the behavior of such applications is only now becoming available. In this paper, we describe the input-output requirements of three scalable parallel applications (electron scattering, terrain rendering, and quantum chemistry, on the Intel Paragon XP/S. As part of an ongoing parallel input/output characterization effort, we used instrumented versions of the application codes to capture and analyze input/output volume, request size distributions, and temporal request structure. Because complete traces of individual application input/output requests were captured, in-depth, off-line analyses were possible. In addition, we conducted informal interviews of the application developers to understand the relation between the codes' current and desired input/output structure. The results of our studies show a wide variety of temporal and spatial access patterns, including highly read-intensive and write-intensive phases, extremely large and extremely small request sizes, and both sequential and highly irregular access patterns. We conclude with a discussion of the broad spectrum of access patterns and their profound implications for parallel file caching and prefetching schemes.
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可扩展并行应用程序的输入/输出特性
计算和通信性能的快速增长加剧了长期存在的性能限制输入/输出的问题。事实上,对于许多其他可伸缩的并行应用程序来说。输入/输出正在成为主要的性能瓶颈。可伸缩输入/输出系统的设计主要取决于这类新兴的大规模并行应用程序的输入/输出需求和访问模式。然而,关于这类应用程序的行为的硬数据直到现在才变得可用。在本文中,我们描述了三个可扩展的并行应用程序(电子散射、地形渲染和量子化学)在英特尔Paragon XP/S上的输入输出需求。作为正在进行的并行输入/输出表征工作的一部分,我们使用应用程序代码的仪器化版本来捕获和分析输入/输出量、请求大小分布和临时请求结构。由于捕获了单个应用程序输入/输出请求的完整跟踪,因此可以进行深入的脱机分析。此外,我们对应用程序开发人员进行了非正式访谈,以了解代码当前和期望的输入/输出结构之间的关系。我们的研究结果显示了各种各样的时间和空间访问模式,包括高度读密集型和写密集型阶段,非常大和非常小的请求大小,顺序和高度不规则的访问模式。最后,我们讨论了广泛的访问模式及其对并行文件缓存和预取方案的深刻影响。
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