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Suitability of Using Self-Organizing Neural Networks in Configuring P-System Communications Architectures

机译:在配置P系统通信体系结构中使用自组织神经网络的适用性

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摘要

Nowadays, it is possible to find out different viable architectures that implements P Systems in a distributed cluster of processors. These proposed architectures have reached a certain compromise between the massively parallelism character of the system and the evolution step times. They are based in the distribution of several membranes in each processor, the use of proxies to control the communication between membranes and mainly, the suitable distribution of the architecture in a balanced tree of processors. For a given P-system and K processors, there exists a great volume of possible distributions of membranes over these. The main disadvantage related with these architectures is focused in the selection of the distribution of membranes that minimizes the external communications between them and maximizes the parallelism grade. In this paper, we suggest the use of Self-Organizing Neural Networks (SONN) with growing capability to help in this selection process for a given P-system.
机译:如今,可以找到在处理器的分布式集群中实现P Systems的不同可行体系结构。这些提议的体系结构已经在系统的大规模并行性与演进步骤之间达成了某种折衷。它们的基础是每个处理器中多个膜的分布,使用代理来控制膜之间的通信以及主要是在处理器的平衡树中适当地分配体系结构。对于给定的P系统和K处理器,在它们上面存在大量可能的膜分布。与这些架构有关的主要缺点集中在膜的分布选择上,这使得它们之间的外部通信最小化并且使平行度等级最大化。在本文中,我们建议使用功能不断增强的自组织神经网络(SONN)来帮助针对给定的P系统进行此选择过程。

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