CSR: Small:Data Staging and Parallel Applications in Robust Desktop Grids

CSR：小型：稳健桌面网格中的数据分级和并行应用程序

• 批准号: 0916742
• 负责人: Peter Keleher
• 金额: $ 47.5万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0916742&HistoricalAwards=false
• 关键词: CSR; Small; Data; Staging; Parallel

This project is an investigation into algorithms and mechanisms that will allow sophisticated staging of input and output data in desktop grids. Data staging allows the system to store data semi-permanently in the underlying peer-to-peer structure, and to run multi-node jobs (applications) whether they be tightly-coupled parallel applications, arbitrary work-flows, or anything between.We are building support for these application types by extending our current desktop grid infrastructure in three distinct areas. We are developing cluster identification techniques that can define arbitrarily-sized virtual clusters through both passive and active network measurement. We are incorporating virtual cluster descriptions into the underlying peer-to-peer infrastructure to allow the scheduling algorithms to map multi-node jobs to the clusters. Finally, we are incorporating data placement into the underlying infrastructure; data is placed according to use and process binding.This work will impact several research areas, including that of distributed and decentralized scheduling, application description, network characterization, and storage networks. In all of these areas our work will explore the tension between local autonomy and global, aggregate objectives.The algorithms and techniques will have broad applicability across a wide range of emerging distributed and collaborative applications. However, the work described here will also explicitly and immediately impact the quality of research conducted by our collaborators in astronomy and elsewhere. The ability to run parallel applications, and those with more complicated inter-relationships, will enable whole new classes of scientific applications to be run on top of ad-hoc grid-like systems.

该项目是对算法和机制的调查，该算法和机制将允许在桌面网格中复杂地分期输入和输出数据。 数据分期可以使系统将数据半永久存储在基础的对等结构中，并运行多节点作业（应用程序），无论它们是紧密耦合的并行应用，任意工作流程还是我们之间的任何内容。 我们正在开发群集识别技术，可以通过被动和主动网络测量来定义任意尺寸的虚拟群集。 我们将虚拟群集描述纳入基础的点对点基础架构中，以允许调度算法将多节点作业映射到群集。 最后，我们将数据放置纳入了基础基础架构。数据根据使用和过程绑定放置。这项工作将影响几个研究领域，包括分布式和分散的调度，应用程序描述，网络表征和存储网络的研究领域。 在所有这些领域，我们的工作将探讨本地自治与全球，总体目标之间的张力。这些算法和技术将在各种新兴的分布式和协作应用程序中具有广泛的适用性。 但是，这里描述的工作也将明确，并立即影响我们的天文学和其他地方合作者进行的研究质量。 运行平行应用以及具有更复杂关系的人的能力将使全新的科学应用程序能够在类似于Ad-Hoc网格的系统之上运行。