With the increase of the search for computational models where the expression of parallelism occurs naturally, some paradigms arise as options for the current generation of computers. In this context, dynamic dataflow and Gamma—General Abstract Model for Multiset mAnipulation—emerge as interesting computational model choices. In dynamic dataflow model, operations are performed as soon as their associated operands are available, without rely on a Program Counter to dictate the execution order of instructions. The Gamma paradigm is based on a parallel multiset rewriting scheme. It provides a nondeterministic execution model inspired by an abstract chemical machinemetaphor, where operations are formulated as reactions that occur freely among matching elements belonging to the multiset. In this work, equivalence relations between the dynamic dataflow and Gamma paradigms are exposed and explored, while methods to convert from dataflow to Gamma paradigm and vice versa are provided. It is shown that vertices and edges of a dynamic dataflow graph can correspond, respectively, to reactions and multiset elements in the Gamma paradigm. This work provides the scientific community with the possibility of taking profit of both parallel programming models, contributing with a versatility component to researchers and developers.

中文翻译：

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Gamma —多集免疫分析和动态数据流模型的通用抽象模型：等效性研究

随着对自然表达并行性的计算模型的搜索的增加，一些范式作为现代计算机的选择出现了。在这种情况下，动态数据流和γ- ģ ENERAL甲bstract中号Odel等对于中号ultiset米甲nipulation浮现有趣计算模型的选择。在动态数据流模型中，只要关联的操作数可用，就立即执行操作，而无需依靠程序计数器来指定指令的执行顺序。Gamma范例基于并行多集重写方案。它提供了受抽象化学机器启发的不确定性执行模型隐喻，其中操作被表述为在属于多集的匹配元素之间自由发生的反应。在这项工作中，动态数据流和Gamma范式之间的等价关系被揭示和探索，同时提供了从数据流转换为Gamma范式（反之亦然）的方法。结果表明，动态数据流图的顶点和边缘可以分别对应于Gamma范式中的反应和多集元素。这项工作为科学界提供了利用两个并行编程模型获利的可能性，并为研究人员和开发人员提供了多功能组件。