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

我们提出的试点项目将探讨开发一个更有效的编程模型，这种分布式和数据密集型环境的可能性，使用一个抽象的机制，从GridRPC社区数据处理的数据管理。与GridRPC范例的核心功能句柄类似，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。程序员可以将数据句柄当作变量来使用，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，如果我们可以提供TGS的数据处理机制，在正确的抽象层次，一个集成不同的现有网格数据管理方法，同时暴露适量的结构，以科学的最终用户，那么我们可以使基于SCE的TeraGrid应用程序，涉及工作流模式与广泛的复杂性。

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.