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。网格被有效地用于在足够大的规模上支持分布式应用程序的运行，以向其开发人员提供新的学科结果。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，网格是一种执行给定计算的许多参数化实例的科学模拟。开发可访问的、高效的、容错的网格版本的仿真软件将使学科科学家能够调查广泛的场景，并以比目前可能的数量级更快的速度获得新的结果。许多科学家希望将大规模仿真视为支持某种程度的用户交互的软件工具。只有在模拟可以轻松部署和动态控制的情况下，即如果计算可以控制时，这才是有效的。传统的场景是用户根据在执行过程中不断演变的部分结果来引导模拟。部分结果为模拟的最终结果提供了一个日益精细的指标，并可用于在执行过程中确定哪些参数集是最有希望的。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，以及科学家指导此类计算的需求，开发针对网格的性能高效和可指导的软件工具变得越来越重要。该项目将解决在大规模网格环境中支持可引导的科学模拟的需要而产生的重要的计算机科学问题。该项目将设计、开发和原型一个虚拟软件仪器，作为设计和原型可扩展的、可引导的网格科学模拟的工具。它将使用蒙特卡罗模拟程序Mcell作为开发和测试虚拟仪器的原型应用程序。虚拟仪器本身将由一套软件模块、库、接口和转向敏感的调度算法组成。该项目将对计算机科学界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在神经科学方面获得新的结果。

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.