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首页> 外文会议>Grids meet autonomic computing workshop 2009 >Developing Autonomic Distributed Scientific Applications: A Case Study From History Matching Using Ensemble Kalman-Filters
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Developing Autonomic Distributed Scientific Applications: A Case Study From History Matching Using Ensemble Kalman-Filters

机译：开发自主分布的科学应用程序：使用集成卡尔曼滤波器进行历史匹配的案例研究

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摘要

The development of a simple effective distributed applications that can utilize multiple distributed resources remains challenging. Therefore, not surprisingly, it is difficult to implement advanced application characteristics - such as autonomic behaviour for distributed applications. Notwithstanding, there exist a large class of applications which could benefit immensely with support for autonomic properties and behaviour. For example, many applications have irregular and highly variable resource requirements which are very difficult to predict in advance. As a consequence of irregular execution characteristics, dynamic resource requirements are difficult to predict a priori thus rendering static resource mapping techniques such as workflows ineffective; in general the resource utilization problem can be addressed more efficiently using autonomic approaches. This paper discusses the design and development of a prototype framework that can support many of the requirements of Autonomic applications that desire to use Computational Grids. We provide here an initial description of the features and the architecture of the Lazarus framework developed using SAGA, integrate it with an Ensemble Kalman Filter application, and demonstrate the advantages - performance and lower development cost, of the framework. As proof of concept we deploy Lazarus on several different machines on the TeraGrid, and show the effective utilization of several heterogeneous resources and distinct performance enhancements that autonomies provides. Careful analysis provides insight into the primary reason underlying the performance improvements, namely a late-binding and an optimal choice of the configuration of resources selected.
机译：可以利用多个分布式资源的简单有效的分布式应用程序的开发仍然具有挑战性。因此，毫不奇怪，很难实现高级应用程序特性-例如分布式应用程序的自主行为。尽管如此，仍然存在大量的应用程序，它们可以通过支持自主特性和行为而大大受益。例如，许多应用程序具有不规则且高度可变的资源需求，这很难预先预测。由于执行特性不规则，动态资源需求很难先验地预测，从而使静态资源映射技术（例如工作流）无效。通常，使用自主方法可以更有效地解决资源利用问题。本文讨论了一个原型框架的设计和开发，该框架可以支持希望使用计算网格的自动应用程序的许多要求。我们在这里提供使用SAGA开发的Lazarus框架的功能和体系结构的初步说明，将其与Ensemble Kalman Filter应用程序集成，并演示该框架的优点-性能和较低的开发成本。作为概念验证，我们将Lazarus部署在TeraGrid上的几台不同计算机上，并展示了对多种异构资源的有效利用以及自治能力所提供的显着性能增强。仔细的分析可以洞悉性能改进的根本原因，即后期绑定和对所选资源配置的最佳选择。

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