Collaborative Research: CSR: Autonomic Power and Performance Management in Distributed Computing Systems

合作研究：CSR：分布式计算系统中的自主电源和性能管理

• 批准号: 0615047
• 负责人: Ishfaq Ahmad
• 金额: $ 3万
• 依托单位: University of Texas at Arlington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0615047&HistoricalAwards=false
• 关键词: Collaborative; Research; CSR; Autonomic; Power

The objective of this project is to develop a theoretic framework and a hierarchical methodology for autonomic power and performance management of distributed computing centers through (a) online modeling, monitoring, and analysis of power consumption and performance; (b) adaptive learning and automatically identifying strategies to minimize power consumptions while maintaining the required quality of service requirements for a wide range of workloads and applications; and (c) dynamically reconfigure the computing, storage and network resources according to the selected optimization strategies. The proposed methodology exploits the emerging hardware and software standards to improve power efficiency of processors and devices such as such as Intel's quickstart and SpeedStep processors, disk spindown, power aware page allocation and RDRAM that offer a wider range of low-power states and reducing the cost of transitions. The impact of this project is in the significant reduction of power consumptions of Internet services and Web servers that account for 8% of the US electricity consumption. In addition, the project results have a profound impact on the environment because by reducing the demand for energy, the amount of CO2 produced each year by electricity generators is reduced significantly.

该项目的目的是通过（a）在线建模，监视和分析功耗和性能的分析中，开发一个理论框架和一种用于分布式计算中心的自主力和性能管理的分层方法； （b）自适应学习并自动识别策略，以最大程度地减少功耗，同时维持各种工作量和应用程序所需的服务质量要求； （c）根据选定的优化策略动态重新配置计算，存储和网络资源。 提出的方法利用了新兴的硬件和软件标准，以提高处理器和设备的功率效率，例如Intel的QuickStart和SpeedStep处理器，磁盘旋转，Power Awarding Page Page分配和RDRAM，这些分配和RDRAM提供了更广泛的低功耗状态并降低过渡成本。该项目的影响在于占美国电力消耗的8％的互联网服务和网络服务器的电力消耗量大大减少。 此外，项目结果对环境产生了深远的影响，因为通过减少能源需求，发电机每年生产的二氧化碳量大大减少。