Optimal Placement of Pipeline Applications on Grid

S. Ngamsuriyaroj, E. Kijsipongse
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Abstract

Computation and communication intensive applications such as scientific data analysis and data visualization are commonly found in grid computing environment.These applications can be divided into a sequence of pipeline stages which could be executed concurrently on different grid resources to achieve high performance. Finding the optimal placement of pipeline stages on grid is a difficult problem due to the aggregation of computation and communication cost involved. This paper proposes a solution to such problem that allows the maximum application throughput by the integration of pipeline placement and data routing. The proposed solution, on one hand, minimizes the computation bottleneck of a pipeline and, on the other hand, prevents the communication cost between successive stages from dominating the entire processing time. Our proposed solution consists of two novel methods. The first method is the single path pipeline execution that fully exploits temporal parallelism and the second method is the multipath pipeline execution which can leverage both temporal and spatial parallelism inherent in any pipeline applications. We evaluate our proposed methods using a set of experiments running in a real grid environment. When compared with the results from several traditional placement methods, our proposed methods give the highest throughput.
网格上管道应用的优化布局
在网格计算环境中,科学数据分析和数据可视化等计算和通信密集型应用十分普遍。这些应用程序可以分成一系列的流水线阶段,这些阶段可以在不同的网格资源上并发执行,以实现高性能。由于涉及计算量和通信成本的总和,在网格上寻找管道级的最优位置是一个难题。本文提出了一种集成管道放置和数据路由的解决方案,以实现最大的应用吞吐量。提出的解决方案一方面最大限度地减少了管道的计算瓶颈,另一方面防止了连续阶段之间的通信成本主导整个处理时间。我们提出的解决方案包括两种新颖的方法。第一种方法是单路径管道执行,它充分利用了时间并行性;第二种方法是多路径管道执行,它可以利用任何管道应用程序固有的时间和空间并行性。我们使用一组在真实网格环境中运行的实验来评估我们提出的方法。与几种传统放置方法的结果相比,我们提出的方法具有最高的吞吐量。
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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