Linux Computational Cluster

Linux计算集群

• 批准号: 6731404
• 负责人: MAHMUD MICHAEL BARMADA
• 金额: $ 45.81万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-04-01 至 2005-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6731404
• 关键词: automated data processing; biomedical equipment purchase; computer data analysis; computer network; computer program /software; computer system hardware; data management; information retrieval; information systems; mathematics

DESCRIPTION (provided by applicant): Analysis needs of rapidly expanding fields of science have pushed the required computational burden to a point beyond the abilities of standard workstations. Novel computational and analytical methods often require many days of computing power, and data storage and integration needs increase with each passing month. To address these needs, we propose to create a shared computational resource comprised of 200 processors (100 2-processor workstations) running the Linux operating system and a storage system with -2 Tb of disk space. These compute nodes will be merged with our existing cluster resources to create a heterogeneous computing environment encompassing approximately 232 processors with a storage capacity of 2.5Tb. This resource can be partitioned to accommodate the needs of a number of individual groups, but also allows the entire resource to be utilized at times of increased need or availability. The resource will be specially targeted to the needs of small- to medium-sized compute-intensive jobs and the development of parallel scientific algorithms, but will also have the required hardward and software resources to allow development of distributed databases, data-warehouses, and parallel database tools for scientific data integration and data mining. Initially, the major user group will be comprised of investigators with primary and secondary appointments from the Department of Human Genetics at the University of Pittsburgh. Additional users will be granted access to the machine on a temporary, proposal-oriented basis, unless they choose to become major users by supporting expansion of the resource.

描述（由申请人提供）： 迅速扩展的科学领域的分析需求将所需的计算负担推向了标准工作站的能力之外。新颖的计算方法和分析方法通常需要数天的计算能力，并且每个月的数据存储和集成需求都会增加。为了满足这些需求，我们建议创建一个共享的计算资源，该计算资源由运行Linux操作系统的200个处理器（100个2个配件工作站）组成，并具有-2 TB磁盘空间的存储系统。这些计算节点将与我们现有的群集资源合并，以创建一个异质的计算环境，其中包含大约232个处理器，存储容量为2.5TB。可以对此资源进行分区，以满足许多单个组的需求，但也允许在需求增加或可用性时使用整个资源。该资源将专门针对中小型计算密集型工作以及平行科学算法的开发，但还将拥有所需的硬性和软件资源，以允许开发分布式数据库，数据软件以及并行数据库工具以进行科学数据集成和数据挖掘。最初，主要用户组将由匹兹堡大学人类遗传学系的主要和次要任命的调查人员组成。除非他们选择通过支持资源的扩展来成为主要用户，否则将授予其他用户访问机器的访问。