{"title":"The Parallelization of Three-Dimensional Electro-magnetic Particle Model Using Both MPI and OPENMP","authors":"Xiaoyang Yan, Weiweng Zhang, Huifang Deng, S. Bu","doi":"10.1109/ICCIS.2010.58","DOIUrl":null,"url":null,"abstract":"Three-Dimensional Electro-Magnetic Particle Model (3DEMPM), based on the equations of Maxwell and Newton-Lorentz, takes advantages of the Finite-Difference Time-Domain (FDTD) and Particle-In-Cell (PIC) to trace a large quantity of particles in order to gain insight into the physics of them. Although MPI alone can be used to parallelize with 1D decomposition along x-direction, the efficiency decreases with increase of CPUs because there are more communications involved. We combine MPI and OPENMP to reduce the communications in the PC cluster, one node of which shares memory with duel-core. The whole domain is decomposed into several sub-domains, the same number as the nodes. Between the nodes we use MPI to realize the communications, and inside each node the OPENMP is applied to do the parallel computing with no communication. In this way, the higher speed-up is achieved while the communication is reduced.","PeriodicalId":227848,"journal":{"name":"2010 International Conference on Computational and Information Sciences","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Computational and Information Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2010.58","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Three-Dimensional Electro-Magnetic Particle Model (3DEMPM), based on the equations of Maxwell and Newton-Lorentz, takes advantages of the Finite-Difference Time-Domain (FDTD) and Particle-In-Cell (PIC) to trace a large quantity of particles in order to gain insight into the physics of them. Although MPI alone can be used to parallelize with 1D decomposition along x-direction, the efficiency decreases with increase of CPUs because there are more communications involved. We combine MPI and OPENMP to reduce the communications in the PC cluster, one node of which shares memory with duel-core. The whole domain is decomposed into several sub-domains, the same number as the nodes. Between the nodes we use MPI to realize the communications, and inside each node the OPENMP is applied to do the parallel computing with no communication. In this way, the higher speed-up is achieved while the communication is reduced.