Collaborative Research: Integrated HPC Systems Usage and Performance of Resources Monitoring and Modeling (SUPReMM)

协作研究：集成 HPC 系统资源使用和性能监控和建模 (SUPReMM)

• 批准号: 1203560
• 负责人: Abani Patra
• 金额: $ 45.86万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1203560&HistoricalAwards=false
• 关键词: Collaborative; Research; Integrated; HPC; Systems

Todays high-performance computing systems are a complex combination of software, processors, memory, networks, and storage systems characterized by frequent disruptive technological advances. In this environment, system managers, users and sponsors find it difficult if not impossible to know if optimal performance of the infrastructure is being realized, or even if all subcomponents are functioning properly. Users of such systems are often engaged in science at the extreme where system uncertainties can significantly delay or even confound the scientific investigations. Critically, for systems based on open source software systems which includes a large fraction of XSEDE resources, the data and information necessary to use and manage these complex systems is not available. HPC centers and their users, are to some extent flying blind, without a clear understanding of system behavior. Anomalous behavior has to be diagnosed and remedied with incomplete and sparse data. It is difficult for users to assess the effectiveness with which they are using the available resources to generate knowledge in their sciences. NSF lacks a comprehensive knowledge base to evaluate the effectiveness of its investments in HPC systems.This award will address this problem through the creation of a comprehensive set of tools for developing the needed knowledge bases. This will be accomplished by building on and combining work on HPC systems monitoring and reporting currently underway at the University at Buffalo under the Technology Audit Service (TAS) of the XSEDE project and University of Texas/ Texas Advance Computing Center (TACC) as part of the Ranger Technology Insertion effort with many elements of existing monitoring and analysis tools. The PIs will provide the knowledge bases required to understand the current operations of XSEDE, to enhance and increase the productivity of all of the stakeholders of XSEDE (service providers, users and sponsors), and ultimately to provide open source tools to greatly increase the operational efficiency and productivity of HPC systems in general.

今天的高性能计算系统是软件、处理器、内存、网络和存储系统的复杂组合，其特征是频繁的颠覆性技术进步。在这种环境下，系统管理员、用户和赞助商很难(如果不是不可能)知道是否实现了基础设施的最佳性能，或者甚至知道所有子组件是否正常运行。这类系统的用户经常从事极端的科学工作，系统的不确定性可能会大大推迟甚至扰乱科学调查。关键的是，对于基于开放源码软件系统的系统，其中包括很大一部分XSEDE资源，无法获得使用和管理这些复杂系统所需的数据和信息。HPC中心及其用户在某种程度上是盲目的，对系统行为没有明确的理解。异常行为必须用不完整和稀疏的数据来诊断和补救。用户很难评估他们利用现有资源在其科学领域产生知识的有效性。NSF缺乏全面的知识库来评估其在HPC系统中投资的有效性。该奖项将通过创建一套全面的工具来开发所需的知识库来解决这一问题。这将通过在布法罗大学XSEDE项目的技术审计处(TAS)和德克萨斯大学/德克萨斯大学高级计算中心(TACC)目前正在进行的高性能计算系统监测和报告工作的基础上进行，并将其结合起来，作为Ranger技术插入工作的一部分，与现有监测和分析工具的许多要素相结合。PIS将提供所需的知识库，以了解XSEDE的当前业务，以加强和提高XSEDE所有利益攸关方(服务提供商、用户和赞助商)的生产力，并最终提供开放源码工具，以极大地提高HPC系统的总体业务效率和生产力。