ITR: Data-Driven Autonomic Performance Modulation for Servers

ITR：数据驱动的服务器自主性能调制

• 批准号: 0325056
• 负责人: Anand Sivasubramaniam
• 金额: $ 55.06万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2006-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0325056&HistoricalAwards=false
• 关键词: ITR; Data; Driven; Autonomic; Performance

The commoditization of high performance computer systems has resulted in their widespread deployment as servers in numerous environments. We find clusters and/or Symmetric Multiprocessors (SMPs) being extensively used for commercial services such as e-commerce and transaction processing, everyday file/web service needs, and for long running scientific applications in academic/research settings. While hardware and software procurement costs for their deployment have dropped significantly, the total cost of ownership is in fact growing because of the costs of involving a human in managing and tuning these systems. It is a non-trivial task today to tune a system and service for each environment/configuration. This proposal intends to develop a data-driven feedback framework - called Cruise Control - to aid in the design and deployment of such autonomic servers. There are several research questions to be investigated in the development of this framework: What system and workload events (data) should we monitor in the server that have a consequence on its performance? How do we represent and store this data in a meaningful manner (and compress them in the process) since it may be collected over several days and at very fine resolution? Based on this historical data and currently evolving conditions, how do we design a controller that can modulate the server execution to avoid performance bottlenecks in a cost-effective manner? What system mechanisms are needed within the underlying operating system and middleware layer to provide the data collection and server modulation functionalities? How do we structure and develop this complete infrastructure on commodity systems without degrading the performance of the server?The Cruise Control framework will provide system mechanisms for collecting the data and will attempt to characterize them to compress their representation. and will develop within the operating system mechanisms for effecting such performance modulation will also be developed within the operating system. This general framework will be implemented and validated experimentally for two different server environments - a commercial database server and a high performance computing server for scientific applications - on a cluster and a SMP hardware platform.

高性能计算机系统的商品化导致其在众多环境中作为服务器广泛部署。我们发现集群和/或对称多处理器 (SMP) 广泛用于商业服务，例如电子商务和事务处理、日常文件/Web 服务需求以及学术/研究环境中长期运行的科学应用。虽然其部署的硬件和软件采购成本已大幅下降，但由于人工管理和调整这些系统的成本，总拥有成本实际上正在增加。如今，针对每个环境/配置调整系统和服务是一项艰巨的任务。该提案旨在开发一个数据驱动的反馈框架（称为巡航控制），以帮助设计和部署此类自主服务器。在该框架的开发过程中需要研究几个研究问题：我们应该在服务器中监视哪些会影响其性能的系统和工作负载事件（数据）？由于这些数据可能需要几天的时间并以非常精细的分辨率收集，我们如何以有意义的方式表示和存储这些数据（并在此过程中压缩它们）？根据这些历史数据和当前不断变化的条件，我们如何设计一个可以调节服务器执行的控制器，以经济高效的方式避免性能瓶颈？底层操作系统和中间件层需要哪些系统机制来提供数据收集和服务器调制功能？我们如何在商品系统上构建和开发这个完整的基础设施，而不降低服务器的性能？ Cruise Control 框架将提供用于收集数据的系统机制，并尝试表征它们以压缩其表示。并且将在操作系统内开发用于实现这种性能调制的机制也将在操作系统内开发。该通用框架将在集群和 SMP 硬件平台上针对两种不同的服务器环境（商业数据库服务器和用于科学应用的高性能计算服务器）进行实施和实验验证。