摘要
BP神经网络算法在大规模数据训练过程中需要处理大量的计算,导致整体训练速度下降,时效性较差,针对以上问题,本文提出BP神经网络并行化策略,并利用MPI并行编程库结合C语言在Linux集群上验证了该算法的有效性,提高了BP神经网络的整体训练速度。
Back Propagation neural network algorithm requires huge amounts of computation for training.The problem leads to decrease of the speed training,and timeliness is very bad.In order to slove the computing problem,this paper raises a BP neural network parallel algorithm.MPI parallel programming library and C language in Linux on cluster are used to validated the effectiveness of the algorithm,and improved the whole training speed of the BP neural network.
出处
《内蒙古农业大学学报（自然科学版）》
CAS
北大核心
2011年第4期286-289,共4页
Journal of Inner Mongolia Agricultural University(Natural Science Edition)
基金
内蒙古自治区自然科学基金(200408020110)
关键词
BP神经网络
并行
集群
MPI
C语言
BP neutral network algorithm
parallel
cluster
C Language
