Automatic Construction of Performance Skeletons for Grid Resource Selection

国家科学基金会分布式系统研究CISE/CNSABSTRACTPROPOSAL编号：0410797主要研究者：Subhlok，Jaspal。研究机构：休斯顿大学PROPOSAL标题：网格计算的自动性能框架应用程序的性能框架是一个短时间运行的程序，它在任何运行时场景中的执行时间反映了它所代表的应用程序的预期执行时间。这样一个骨架可以用来快速估计一个长时间运行的应用程序在一组给定的执行节点上的性能，即使节点和网络链路是共享的。该项目正在进行的研究，使自动构建的性能骨架的资源密集型应用程序。性能框架必须模拟应用程序的执行行为，如计算、内存和通信模式，以便对应用程序的性能进行建模。构建应用程序性能框架的方法包括以下步骤：（1）执行目标应用程序并记录执行跟踪，捕获详细的CPU、内存和网络活动。 (2)捕获应用程序执行跟踪中的重复模式，并将其总结为紧凑的执行信号。 (3)从执行签名捕获的汇总系统活动生成性能骨架可执行程序。性能建模是有效使用高性能计算资源的核心。性能骨架是一种快速、创新和准确的方法，可以用来评估在各种不可预测的网格环境中长时间运行的应用程序的性能。对于运行数小时的应用程序，使用此方法进行精确的性能评估通常只需要几秒钟的框架执行。这个项目也正在开发一个框架，在网格环境中的资源选择与性能骨架。

National Science FoundationDistributed Systems Research CISE/CNSABSTRACTPROPOSAL NUMBER: 0410797PRINCIPAL INVESTIGATOR: Subhlok, Jaspal.INSTITUTION: University of HoustonPROPOSAL TITLE: Automatic Performance Skeletons for Grid ComputingThe performance skeleton of an application is a short running program whose execution time in any run-time scenario reflects the expected execution time of the application it represents. Such a skeleton can be employed to quickly esti-mate the performance of a long running application on a given set of execution nodes even when the nodes and network links are shared. This project is per-forming research to enable automatic construction of performance skeletons of resource intensive applications. A performance skeleton must mimic application execution behavior, such as computation, memory, and communication pat-terns, in order to model the application's performance. The approach being taken to construct the performance skeleton of an application consists of the following steps:(1) Execute the target application and record the execution trace that captures detailed CPU, memory and network activity. (2) Capture repeated patterns in the application execution trace and summarize it as a compact execution signa-ture. (3) Generate the performance skeleton executable program from the summarized system activity captured by the execution signature.Performance modeling is central to effective use of high performance computa-tional resources. Performance skeletons represent a fast, innovative and accu-rate approach to estimating the performance of long running applications on diverse and unpredictable grid environments. Accurate performance estimation with this method typically takes only a few seconds of skeleton execution for applications that run for several hours. This project is also developing a frame-work for resource selection in grid environments with performance skeletons.