Collaborative Research: CSR--AES: TeraGridSolve: General Purpose Scientific Computing Environments for the TeraGrid

我们提出的试点项目将探索为这种分布式和数据密集型环境开发更有效的编程模型的可能性，使用来自GridRPC社区数据句柄的数据管理抽象机制。类似于作为GridRPC范例中心的函数句柄，数据句柄是一种抽象，可以在运行时动态绑定到数据和存储资源。程序员可以像使用变量一样使用数据句柄，在多个GridSolve调用之间传递它，同时，内部GridSolve运行时系统可以对它们执行各种操作（例如读，写）。我们相信，如果我们能够在适当的抽象层次上为TGS提供一种数据处理机制，这种机制可以集成不同的现有网格数据管理方法，同时向科学最终用户公开适当数量的结构，那么我们就可以启用基于sce的TeraGrid应用程序，这些应用程序涉及到复杂程度很高的工作流模式。

Our proposed pilot project will explore the possibility of developing a more effective programming model for such distributed and data intensive environments, using an abstract mechanism for data management from the GridRPC community data handles. Analogous to the function handles that are central to the GridRPC paradigm, a data handle is an abstraction that can be dynamically bound to data and storage resources at run-time. A programmer can use a data handle as if it were variable, passing it between multiple GridSolve calls, while at the same time, the internal GridSolve run-time system can perform various operations (e.g. read, write) on them. We believe that if we can provide TGS with a data handle mechanism at the right level of abstraction, one that integrates different existing grid data management approaches while exposing the appropriate amount of structure to the scientific end user, then we can enable SCE-based TeraGrid applications that involve workflow patterns with a wide range complexity.