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Implementing Parallel Genetic Algorithm Using Concurrent-functional Languages

机译:使用并发功能语言实现并行遗传算法

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The spread of multiprocessor and multi-core architectures have a pervasive effect on the way software is developed. In order to take full advantage of them, a parallel implementation of every single program would be needed, but also a radical reformulation of the algorithms that are more appropriate to that kind of implementation. In this work we design and implement an evolutionary computation model using programming languages with built-in concurrent concepts. This article shows the advantages of these paradigms in order to implement a parallel genetic algorithm (pGA) with an island pools based topology in the concurrent-functional oriented programming languages: Erlang, Scala, and Clojure. Some implementation decisions are analyzed and the results of the solution of a study case are shown.
机译:多处理器和多核架构的传播对开发的软件的普遍效应。 为了充分利用它们,需要每一个程序的并行实现,而是对更适合这种实施的算法的算法的激进重构。 在这项工作中,我们使用具有内置并发概念的编程语言来设计和实施进化计算模型。 本文展示了这些范例的优势,以便在并发功能导向的编程语言中实现并行遗传算法(PGA)与基于岛池的拓扑结构:Erlang,Scala和Clojure。 分析了一些实施决策,并显示了研究壳体解决方案的结果。

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