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，可以提高网格的有效开发和部署。特别是，需要关注替代中间件实现对应用程序性能的影响的基准测试。该项目的成果将是：（1）一套低层次的基准探针测量网格基础设施的性能和网格中间件的开销。(2)一个综合的应用程序基准套件，体现了预期的网格使用场景的几个新兴的数据密集型网格应用程序。(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，从而通知生产应用程序成熟的不断发展的合成基准的细化。(4)一个维护的性能数据网站，网格用户可以在其中获得基准测试，查看该组和其他人报告的结果，并提交自己的新结果。(5)支持对影响网格性能的因素进行研究（有些是本提案的一部分，但也有更广泛的社区参与）。随着网格的出现，重要的是要将测量方法沿着部署，以便应用程序和体系结构能够在科学原则的指导下发展。所有的科学都需要商定的衡量标准--一种交流结果的共同语言。一个系统要设计得好，必须进行测量，以便可以定量地比较替代实现。此外，系统的用户需要描述系统能力的性能目标，以便他们可以开发和调整他们的应用程序，以实现明智的目标。系统架构师需要用户如何使用系统的例子来通知设计过程。因此，基准测试是网格中间件的一个重要组成部分，可以实现关于技术进步和设计权衡的交流。拟议的工作将开发一套数据密集型网格基准之间的人建设网格和计划使用它们的人来回传递信息。数据密集型应用程序形成了一类需要访问远离其计算资源的多个数据归档的问题。它们属于网格，因为它们已经是分布式的（与传统的HPC应用程序相反，传统的HPC应用程序可能会也可能不会很好地扩展到网格）。 需要一个基准测试套件来体现这些新兴应用程序的资源需求，以帮助网格架构师了解应用程序将如何强调基础设施和中间件，并让用户提前了解他们可以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.