用于资源感知应用程序的便携式网格基础设施

Michal Wegiel, G. Czajkowski, L. Daynès, K. Palacz
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引用次数: 1

摘要

现代的资源密集型企业和科学应用程序越来越多地使用部署在网格平台上的并行和分布式组件来构建。网格环境通常是异构的,并且受较大负载变化的影响。这些特性需要可移植的编程基础设施和对资源管理的全面支持,以及对不同资源可用性的动态适应。资源感知应用程序主动监控并动态调整其行为,以适应不断变化的资源消耗约束。内部负载平衡和作业重新提交等策略可以纠正次优调度决策,从而提高性能。由于利用资源感知的潜力需要与资源管理子系统进行密切的交互,因此实现通常依赖于低级的、特定于平台的特性,这损害了可移植性。我们需要的是网格系统中资源管理的所有方面不受损害的可移植性。我们演示了配备了用于分布式资源管理的api的Java平台可以用于构建可移植的网格基础设施。特别地,我们描述了一个集群管理系统的设计和实现,该系统能够控制并行的、资源感知的Java应用程序的执行。我们的经验表明,我们的解决方案支持高效、细粒度的资源管理,足以利用资源密集型应用程序所承诺的性能优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A portable grid infrastructure for resource-aware applications
Modern, resource-intensive enterprise and scientific applications are increasingly architected using parallel and distributed components deployed on grid platforms. Grid environments are typically heterogeneous and subject to large load variations. Such characteristics require a portable programming infrastructure and comprehensive support for resource management as well as dynamic adaptation to varying resource availability. Resource-aware applications pro-actively monitor and dynamically adapt their behavior to accommodate to changing resource consumption constraints. Strategies such as internal load-balancing and job re-submission can correct sub-optimal scheduling decisions and thus enhance performance. As utilizing the potential of resource awareness requires close interaction with resource management subsystems, implementations often rely on low-level, platform-specific features, which impair portability. What is needed is uncompromised portability of all aspects of resource management in grid systems. We demonstrate that the Java platform, equipped with the APIs for distributed resource management, can be used for building a portable grid infrastructure. In particular, we describe the design and implementation of a cluster management system capable of controlled execution of parallel, resource-aware Java applications. We empirically show that our solution allows for efficient, fine-grained resource management, sufficient for tapping the performance benefits promised by the resource-conscious applications.
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