复调:用于云计算的工作流编排框架

K. Shams, M. Powell, T. Crockett, J. Norris, Ryan A. Rossi, T. Söderström
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引用次数: 26

摘要

云计算以可承受的价格为NASA的任务提供了前所未有的计算能力。像火星探测漫游者(MER)和火星科学实验室(MSL)这样的任务正在享受弹性,这使他们能够在短时间内利用数百台(如果不是数千台的话)机器,而无需购买任何硬件。在本文中,我们描述了Polyphony,这是一个弹性的、可扩展的、模块化的框架,它有效地利用了大量的计算资源来执行并行计算。Polyphony可以使用云上的资源、本地机器上的过剩容量以及超级计算中心上的备用资源,并且它使这些资源能够协同工作以实现共同的目标。Polyphony对节点故障具有弹性,即使它们发生在事务的中间。最后,我们将评估构建在Polyphony之上的生产就绪应用程序,以执行来自太阳系周围的图像处理操作,包括火星,土星和土卫六。
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Polyphony: A Workflow Orchestration Framework for Cloud Computing
Cloud Computing has delivered unprecedented compute capacity to NASA missions at affordable rates. Missions like the Mars Exploration Rovers (MER) and Mars Science Lab (MSL) are enjoying the elasticity that enables them to leverage hundreds, if not thousands, or machines for short durations without making any hardware procurements. In this paper, we describe Polyphony, a resilient, scalable, and modular framework that efficiently leverages a large set of computing resources to perform parallel computations. Polyphony can employ resources on the cloud, excess capacity on local machines, as well as spare resources on the supercomputing center, and it enables these resources to work in concert to accomplish a common goal. Polyphony is resilient to node failures, even if they occur in the middle of a transaction. We will conclude with an evaluation of a production-ready application built on top of Polyphony to perform image-processing operations of images from around the solar system, including Mars, Saturn, and Titan.
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