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Parallel training for neural networks using PVM with shared memory

被引：0
|
作者：
Araújo, MAA [1 ]
Teixeira, EP [1 ]
Camargo, FR [1 ]
Almeida, JPV [1 ]
机构：
[1] Catholic Univ GO, BR-74030110 Goiania, Go, Brazil
来源：
CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS | 2003年
关键词：
Artificial Neural Networks; backpropagation; parallel computing; PVM framework and Shared Memory;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
This paper presents a peculiar parallel implementation of Artificial Neural Networks using the backpropagation training algorithm. The message pass interface PVM is used in the Linux operating system environment, implemented in a cluster of IBM-PC machines. An optimized object-oriented framework to train Neural Networks, developed in C++, is part of the system presented in this paper. A shared memory framework was implemented to improve the training phase. One of the advantages of the system is the low cost, considering that its performance can be compared to similar powerful parallel machines.
引用
收藏
页码：1315 / 1322
页数：8
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