CPS: Small: Low-Impact Monitoring of Streaming Systems

CPS：小型：流媒体系统的低影响监控

• 批准号: 0931693
• 负责人: Roger Chamberlain
• 金额: $ 54.35万
• 依托单位: Washington University
• 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: 2009-10-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0931693&HistoricalAwards=false
• 关键词: CPS; Small; Low; Impact; Monitoring

The objective of this research is to enable improved performance and application development efficiency for streaming applications. The approach is to use architecturally diverse computing engines, such as field programmable gate arrays and graphics processing units, to execute portions of an application. This approach is especially well suited to applications that process streaming data, such as from a sensor array like a telescope or other scientific instrument.Intellectual merit. While the use of architecturally diverse systems has a long history in the world of performance-critical systems that interact with the physical world, application development has always been a challenge. This proposal seeks to improve application development by making significant progress in two essential areas: performance monitors and debuggers. The approach has the following properties: it is non-intrusive with respect to the application being monitored and it supports data collection concerning rare events. In particular, it allows correlation of the cyber portion of an application with the physical portion in which the rare events occur.Broader impacts. Impact on society: The research can have a dramatic impact on cyber-physical computing applications, from scientific instrumentation to medical imaging. Improvements in power efficiency, weight, and volume are all achievable through the use of architectural diversity. Education: The proposed research will be carried out by graduate and undergraduate students, both furthering their education and increasing the nation's trained workforce. Underrepresented groups: Washington University's Chancellor's Fellowship and Olin Fellowship programs will be leveraged to attract the participation of individuals from underrepresented groups.

这项研究的目的是使流媒体应用程序的性能和应用程序开发效率的提高。 该方法是使用架构上不同的计算引擎，例如现场可编程门阵列和图形处理单元，来执行应用程序的部分。 这种方法特别适合处理流数据的应用，例如来自望远镜或其他科学仪器等传感器阵列的数据。虽然在与物理世界交互的性能关键系统的世界中，使用架构多样的系统有着悠久的历史，但应用程序开发一直是一个挑战。 该提案旨在通过在两个重要领域取得重大进展来改进应用程序开发：性能监视器和调试器。该方法具有以下属性：它是非侵入性的应用程序被监视，它支持有关罕见事件的数据收集。特别是，它允许将应用程序的网络部分与发生罕见事件的物理部分相关联。对社会的影响：这项研究可能会对网络物理计算应用产生巨大影响，从科学仪器到医学成像。 功率效率、重量和体积的改进都可以通过使用架构多样性来实现。 学历：这项拟议中的研究将由研究生和本科生进行，既促进了他们的教育，也增加了国家训练有素的劳动力。代表性不足的群体：华盛顿大学的校长奖学金和奥林奖学金计划将被用来吸引代表性不足的群体的个人参与。