Prediction Of Dynamic Load Balancing Based On BP Algorithm

The rapid development of network technology provides the proper conditions for the network parallel computing,and the typical representative is the Parallel computing based on LAN cluster and the grid computing based on the Internet.Parallel computing cluster for the excellent scalability and the high performance-price ratio has become a hot research topic in the High Performance Computing field at present.The task scheduling and dynamic load balancing are the key to network parallel computing.We can improve the efficiency of parallel program effectively if we can measure and predict node's load accurately in the parallel programming,and conducts the research to have the important theory and the application value.In this paper,the content of parallel computing technology and the MPI(Message Passing Interface) parallel programming are introduced firstly,and the load balancing problem of parallel programming is researched.Secondly,the load characteristics are analyzed,which are the basis of load prediction.Establishing a load balancing system based on BP algorithm combined with the MPI parallel programming standard on the Windows system,and putting forward the plan and framework.Building the load collection module take advantage of the self-adaptive and initiative strategy of load collection,which can collect the node load information accurately and promptly,and providing the sources of data for the load prediction.Predicting the node's load information changes using the BP neural network, and establishing the prediction model based on BP neural network.Finally,building a parallel computing platform based on MPI in LAN,and tesing the system model.Result shows that the load scheduling system based on the BP algorithm prediction improves performance certainly compared with the way of MPI direct allocation.