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Scalability limits of Bag-of-Tasks applications running on hierarchical platforms

机译:在分层平台上运行的任务袋应用程序的可伸缩性限制

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Bag-of-Tasks applications are parallel applications composed of independent (i.e., embarrassingly parallel) tasks, which do not communicate with each other, may depend upon one or more input files, and can be executed in any order. Each file may be input for more than one task. Examples of Bag-of-Tasks (BoT) applications include Monte Carlo simulations, massive searches (such as key breaking), image manipulation applications and data mining algorithms. A common framework to execute BoT applications is the master-slave topology, in which the user machine is used to control the execution of tasks. In this scenario, a large number of concurrent tasks competing for resources (e.g., CPU and communication links) severely limits application execution scalability. This paper is devoted to study the scalability of BoT applications running on multi-node systems (such as clusters and multi-clusters) organized as hierarchical platforms, considering several communication paradigms. Our study employs a set of experiments that involves the simulation of various large-scale platforms. The results presented provide important guidelines for improving the scalability of practical applications.
机译:任务袋应用程序是由独立(即令人尴尬的并行)任务组成的并行应用程序,这些任务彼此不通信,可能依赖一个或多个输入文件,并且可以按任何顺序执行。每个文件可以输入多个任务。任务袋(BoT)应用程序的示例包括蒙特卡洛模拟,大规模搜索(例如密钥破解),图像处理应用程序和数据挖掘算法。执行BoT应用程序的常见框架是主从拓扑,其中用户计算机用于控制任务的执行。在这种情况下,大量并发任务争夺资源(例如,CPU和通信链接)严重限制了应用程序执行的可伸缩性。本文致力于研究在组织为分层平台的多节点系统(例如集群和多集群)上运行的BoT应用程序的可伸缩性,同时考虑了几种通信范例。我们的研究采用了一组涉及各种大型平台仿真的实验。给出的结果为提高实际应用的可伸缩性提供了重要的指导。

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