Data Intensive GRID Benchmarks

通过定义一套基准来衡量网格体系结构的预期服务质量和网格应用程序的预期解决时间，网格的高效开发和部署将得到推进。特别是，需要关注备选中间件实现对应用程序性能的影响的基准测试。该项目的结果将是：(1)一组用于测量网格基础设施性能和网格中间件开销的低级基准探测。(2)综合应用基准套件，体现了几种新兴数据密集型网格应用的预期网格使用场景。(3)应用程序分析工具，可以总结网格应用程序的资源使用模式，从而告知随着生产应用程序的成熟而不断发展的综合基准的细化。(4)维护性能数据网站，Grid用户可以在网站上获取基准，查看本小组和其他人报告的结果，并提交自己的新结果。(5)对影响网格性能的因素进行研究（有些是本提案的一部分，但也由更广泛的社区进行）。随着网格的出现，与网格一起部署测量方法非常重要，这样应用程序和体系结构才能在科学原则的指导下发展。所有的科学都需要统一的度量标准——一种交流结果的共同语言。一个系统，要设计得好，就必须进行测量，以便可以定量地比较不同的实现。此外，系统用户需要描述系统功能的性能目标，以便他们能够开发和调整应用程序以实现知情目标。系统架构师需要用户如何使用系统的例子来指导设计过程。因此，基准测试是网格中间件的重要组成部分，它使人们能够就技术进步和设计折衷进行交流。拟议的工作将开发一套数据密集型网格基准，在构建网格的人和计划使用网格的人之间来回传递信息。数据密集型应用程序形成的一类问题需要访问远离其计算资源的多个数据存档。它们属于网格，因为它们已经是分布式的（与传统的高性能计算应用程序相反，传统的高性能计算应用程序可能会或可能不会很好地扩展到网格）。我们需要一个包含这些新兴应用程序资源需求的基准套件，以帮助网格架构师理解应用程序将如何对基础设施和中间件造成压力，并让用户提前了解他们所期望的应用程序的服务质量。

Efficient development and deployment of Grids will be advanced by defining a suite of benchmark to measure expected quality-of-service for Grid architectures and anticipated time-to-solution of Grid applications. In particular, the benchmarks to focus on the impact of alternative middleware implementations on application performance are needed. The outcomes of the project will be:(1) A set of low-level benchmark probes for measuring the performance of Grid infrastructure and the overheads of Grid middleware.(2) A synthetic applications benchmark suite embodying anticipated Grid usage scenarios of several emerging data intensive Grid applications.(3) Applications profiling tools that can summarize the resource usage patterns of Grid applications, and thus inform the refinement of an evolving synthetic benchmark as production applications mature.(4) A maintained website of performance data where Grid users can obtain benchmarks, view results reported by this group and others, and submit their own new results.(5) Enabled research (some as part of this proposal, but also by the wider community) into factor affecting Grid performance.As Grids emerge, it is important to deploy measurement methods along with them so that applications and architectures can evolve guided by scientific principles. All sciences need agreed upon metrics-a common language for communicating results. And a system, to be well engineered, must be measured so that alternative implementations can be compared quantitatively. Also, users of systems need performance objectives that describe system capabilities so that they can develop and tune their applications towards informed objectives. And system architects need examples of how the users will exercise the system to inform the design process. Benchmarks are thus an important part of the middleware for Grids, enabling communication about technological advances and design tradeoffs. The proposed work will develop a suite of data intensive Grid benchmarks to convey information back and forth between people building Grids and people planning to use them. The data-intensive applications form a class of problems requires access to multiple data archives remote from their computational resources. They belong on the Grid because they are already distributed (as opposed to traditional HPC applications that may or may not scale well to Grids). A benchmark suite to embody the resource requirements of these emerging applications is needed to help Grid architects understand how applications will stress infrastructure and middleware, and give users an early look at the quality-of-service they can expect for their applications.