网格工作负载中的管道和批处理共享

High Performance Distributed Computing, 2003. Proceedings. 12th IEEE International Symposium on Pub Date : 2003-06-22 DOI:10.1109/HPDC.2003.1210025

D. Thain, John Bent, A. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau, M. Livny

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引用次数: 67

摘要

我们提出了六个批处理管道科学工作负载的研究，这些工作负载是在计算网格上执行的候选者。尽管其他研究关注单个应用程序的行为，但本研究描述了由使用文件存储进行通信的顺序进程管道组成的工作负载，并且还共享内存、CPU和单个组件的I/O需求的测量，以及完整批处理中I/O共享的分析。最后，我们将讨论这些工作负载对端到端可伸缩性和整体系统设计的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Pipeline and batch sharing in grid workloads

We present a study of six batch-pipeline scientific workloads that are candidates for execution on computational grids. Whereas other studies focus on the behavior of single applications, this study characterizes workloads composed of pipelines of sequential processes that use file storage for communication and also share measurements of the memory, CPU, and I/O requirements of individual components as well as analyses of I/O sharing within complete batches. We conclude with a discussion of the ramifications of these workloads for end-to-end scalability and overall system design.

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High Performance Distributed Computing, 2003. Proceedings. 12th IEEE International Symposium on

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