PowerList和ParList理论中的有界并行性

Virginia Niculescu, A. Guran
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引用次数: 1

摘要

基于PowerList、PowerArray和ParList理论的递归、数据并行程序是一个非常有效的模型。它保证了这类程序的简单和正确的设计,允许工作在一个高层次的抽象。通过在这些理论中引入数据分布,这种高层次的抽象可以与性能相协调。正式引入分布的一个重要优点是,它允许我们评估成本,这取决于可用处理器的数量,这被视为一个参数。在本文中,我们通过引入使用ParList结构定义的并行程序的数据分布来推广在PowerLists上定义的数据分布。使用这些分布,我们还定义了将ParList并行程序转换为PowerList并行程序的可能性,这更有效。这是一个重要的优势,因为PowerList程序可以有效地映射到实际架构(例如超立方体)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bounded Parallelism in PowerList and ParList Theories
A very efficient model for recursive, data-parallel programs can be one based on PowerList, PowerArray, and ParList theories. It assures simple and correct design of this kind of programs, allowing work at a high level of abstraction. This high level of abstraction could be reconciled with performance by introducing data-distributions into these theories.%An important advantage of formally introducing distributions is that this allows us to evaluate costs, depending on the number of available processors, which is considered as a parameter. In this paper, we generalize the data distributions defined on PowerLists by introducing data distributions for parallel programs defined using ParList structures. Using these distributions we also define a possibility to transform ParList parallel programs into PowerList parallel programs, which are more efficient. This is an important advantage since PowerList programs could be efficiently mapped on real architecture (e.g. hypercubes).
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