CI-P: Computer System Failure Data Repository to Enable Data-Driven Dependability Research

CI-P：计算机系统故障数据存储库，支持数据驱动的可靠性研究

• 批准号: 1405906
• 负责人: Saurabh Bagchi
• 金额: $ 4.99万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-15 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1405906&HistoricalAwards=false
• 关键词: CI; Computer; System; Failure; Data

Dependability is a requirement for computer systems; however, researchon dependable systems is hampered by a lack of real and publiclyavailable failure data. This can result in productive paths ofresearch being closed to most researchers and, conversely,unproductive research being performed due to faulty assumptions aboutthe manner in which real systems fail. The goal of this project is toplan a collaborative effort to collect, curate, and provide publicaccess to failure data for large scale computer systems through acommunity repository. One challenge is that failure data isconsidered sensitive by the owners. The ultimate goal of this projectis to collect the data from some of the NSF-funded largecyberinfrastructure projects, such as NEES, LIGO, XSEDE, and NRAO.The specific goal of this planning project is to collect requirementsfrom potential praticipants (both users and contributors of data sets)and seed a prototype repository with data sets from two of the largestand latest clusters at Purdue. The data sets will comprise staticinformation, dynamic information about the workloads, and failureinformation, for both planned and unplanned outages.The broader impact in the project will be achieved through thedissemination of the data sets to a wide variety of researchers, andperhaps even, practitioners. The datasets will let people run theircampus clusters more efficiently, i.e., with fewer failures, at higherutilization and energy efficiency.

可靠性是计算机系统的一个要求，然而，可靠系统的研究受到缺乏真实的和公开的故障数据的阻碍。 这可能导致生产路径的研究被关闭，以大多数研究人员，相反，非生产性的研究正在进行，由于错误的假设方式，其中真实的系统失败。 这个项目的目标是计划一个合作的努力，收集，策展，并提供公共访问的大型计算机系统的故障数据，通过accompanyity存储库。 一个挑战是故障数据被所有者认为是敏感的。 该项目的最终目标是收集来自NSF资助的一些大型基础设施项目的数据，如NEES，LIGO，XSEDE和NRAO。该规划项目的具体目标是收集潜在参与者（数据集的用户和贡献者）的需求，并使用来自Purdue的两个大型和最新集群的数据集播种原型存储库。这些数据集将包括静态信息、关于工作负载的动态信息以及计划内和计划外停机的故障信息。通过将这些数据集分发给各种各样的研究人员，甚至可能是从业人员，将实现项目中更广泛的影响。数据集将让人们更有效地运行他们的校园集群，即，更少的故障，更高的利用率和能源效率。