A graph based framework for the definition of tools dealing with sparse and irregular distributed data structures

Proceedings Third International Workshop on High-Level Parallel Programming Models and Supportive Environments Pub Date : 1998-03-30 DOI:10.1109/HIPS.1998.665144

J. Lépine, S. Chaumette, F. Rubi

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引用次数: 5

Abstract

Industrial applications use specific problem oriented implementations of large sparse and irregular data structures. Hence there is a need for tools that make it possible for developers to visualize their applications in terms of these data, their structure, and the operations that are applied to them, whatever their effective implementation and their distribution are. We present both a framework which we have setup to support the development of such tools, and prototypes which we have developed. The resulting environment is composed of two layers: the first layer is a model that we have defined and implemented as high level libraries that make it possible to efficiently abstract from the implementation; the second layer offers prototype tools built on top of these libraries. These tools are integrated within a graphical environment called Visit (T. Brandes et al., 1996) which is part of the HPFIT research effort (T. Brandes et al., 1996). HPFIT is a joint project involving three research laboratories: LIP in Lyon, France, LaBRI in Bordeaux, France, and GMD/SCAI in Bonn, Germany. Its aim is to provide an integrated HPF development environment that supports sparse and irregular data structures.

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一个基于图的框架，用于定义处理稀疏和不规则分布数据结构的工具

工业应用程序使用大型稀疏和不规则数据结构的特定面向问题的实现。因此，需要一些工具，使开发人员能够根据这些数据、它们的结构和应用于它们的操作来可视化他们的应用程序，无论它们的有效实现和分布是什么。我们提供了一个框架，我们已经建立了支持这些工具的开发，和原型，我们已经开发。最终的环境由两层组成:第一层是一个模型，我们已经将其定义和实现为高级库，可以有效地从实现中抽象出来;第二层提供了构建在这些库之上的原型工具。这些工具集成在一个名为Visit的图形环境中(T. Brandes et al.， 1996)，这是HPFIT研究工作的一部分(T. Brandes et al.， 1996)。HPFIT是一个联合项目，涉及三个研究实验室:法国里昂的LIP，法国波尔多的LaBRI和德国波恩的GMD/SCAI。它的目标是提供一个支持稀疏和不规则数据结构的集成HPF开发环境。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings Third International Workshop on High-Level Parallel Programming Models and Supportive Environments

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