ITR: Virtual Instruments: Scalable Software Instruments for the Grid

分布式通信、计算和存储资源的集合，也称为“计算网格”，正在成为高性能计算的关键平台。网格被有效地用于支持足够大规模的分布式应用程序的运行，以向其开发人员提供新的学科成果。几乎每个科学和工程领域的研究人员都对一类特别适合网格的应用程序特别感兴趣，这些应用程序是执行给定计算的许多参数化实例的科学模拟。可访问的，高效的，容错的网格版本的仿真软件的开发将使学科科学家调查广泛的情况下，并获得新的结果数量级比目前可能的许多科学家希望看到大规模的模拟软件工具，支持一定程度的用户交互。只有当模拟可以很容易地部署和动态控制时，这才是有效的，也就是说，如果计算可以被操纵。传统的场景是用户根据在执行期间不断演变的部分结果来操纵模拟。的部分结果提供了一个越来越精细的指标的最终结果的模拟，并可以用来识别中期执行的参数集是最有前途的。考虑到广域联合网格环境为大规模模拟提供聚合计算能力、数据存储和传播设施的潜力，以及科学家引导此类计算的需求，开发针对网格的高性能和可操纵的软件工具变得越来越重要。这个项目将解决在大规模网格环境中支持可操纵的科学模拟的重要计算机科学问题，该项目将设计、开发和原型化一个虚拟软件工具，作为设计和原型化网格可伸缩、可操纵的科学模拟的工具。它将使用蒙特卡罗模拟程序MCell作为虚拟仪器开发和测试的原型应用程序。虚拟仪器本身将由一组软件模块、库、接口和转向敏感调度算法组成。该项目将对计算机科学和学科科学界产生影响。它将通过开发事件模型，性能模型，数据管理策略以及自适应调度和转向算法来促进计算机科学的新研究。它还将使领域科学家能够在神经科学领域获得新成果。

Ensembles of distributed communication, computation, and storage resources, also known as "Computational Grids", are emerging as a critical platform for high-performance computing. Grids are used effectively to support runs of distributed applications at a large enough scale to provide new disciplinary results to their developers. Researchers in almost every field of science and engineering are particularly interested in a class of applications particularly well suited to the Grid, scientific simulations where many parameterized instances of a give computation are performed. The development of accessible, efficient, fault-tolerant Grid-enabled versions of simulation software will enable disciplinary scientists to investigate wide-ranging scenarios and to obtain new results orders of magnitude faster than is currently possible.Many scientists would like to view large-scale simulations as software instruments that support some level of user interaction. This would be effective only if simulations can be deployed easily and controlled dynamically, i.e. if the computation can be steered. A traditional scenario is for the user to steer the simulation based on partial results that evolve continuously during execution. The partial results provide an increasingly refined indicator of the final results of the simulation and can be used to identify mid-execution which parameter sets are most promising. Given the potential of wide-area, federated Grid environments to deliver the aggregate computational power, data storage and dissemination facilities for large-scale simulations, and the need for scientists to steer such computations, it is increasingly important to develop performance-efficient and steerable software instruments that target the Grid. This project will address the significant computer science problems that arise from the need to support steerable scientific simulations in large-scale Grid environments.The project will design, develop, and prototype a virtual software instrument as a vehicle for designing and prototyping scalable, steerable scientific simulations for the Grid. It will use a Monte Carlo simulation program, MCell, as a prototype application for development and testing of the virtual instrument. The virtual instrument itself will consist of a set of software modules, libraries, interfaces, and steering-sensitive scheduling algorithms. The project will have impact on both the computer science and disciplinary science communities. It will foster new research in computer science through the development of event models, performance models, data management strategies, and adaptive scheduling and steering algorithms. It will also enable domain scientists to obtain new results in neuroscience.