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High-level abstractions for message-passing parallel programming

机译:消息传递并行编程的高级抽象

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摘要

Large-scale scientific and engineering computation problems are usually complex and consequently the development of parallel programs for solving these problems is a difficult task. In this paper, we describe the graph-oriented programming (GOP) model and environment for building and evaluating parallel applications. The GOP model provides higher level abstractions for message-passing parallel programming and the software environment offers tools which can ease programmers for parallelizing, writing, and deploying scientific and engineering computing applications. We discuss the motivations and various issues in developing the model and the software environment, present the design of the system architecture and the components, and describe the evaluation of the environment implemented on top of MPI with a sample parallel scientific application program. With the support of the high-level abstractions provided by the proposed GOP environment, programming of parallel applications on various parallel architectures can be greatly simplified.
机译:大型科学和工程计算问题通常很复杂,因此开发用于解决这些问题的并行程序是一项艰巨的任务。在本文中,我们描述了用于构建和评估并行应用程序的面向图的编程(GOP)模型和环境。 GOP模型为消息传递并行编程提供了更高层次的抽象,而软件环境则提供了可以简化程序员用于并行化,编写和部署科学和工程计算应用程序的工具。我们讨论了开发模型和软件环境的动机和各种问题,介绍了系统体系结构和组件的设计,并通过示例并行科学应用程序描述了在MPI之上实施的环境评估。在所建议的GOP环境提供的高级抽象的支持下,可以大大简化在各种并行体系结构上的并行应用程序的编程。

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