{"title":"Mapping of finite-element grids onto parallel computers using neural networks","authors":"R. Tan, V. Lakshmi Narasimhan","doi":"10.1109/ICAPP.1997.651533","DOIUrl":null,"url":null,"abstract":"In this paper, LSOM (Load-balancing Self-Organizing Map), a neural network based on Kohonen's self-organizing map is proposed for the problem of mapping finite-element method (FEM) grids to distributed-memory parallel computers with mesh interconnection networks. The rough global ordering produced by LSOM is then combined with the local refinement Kernighan-Lin algorithm (called LSOM-KL) to obtain the solution. LSOM-KL obtained a load imbalance of less than 0.1% and a low number of hops, comparable to results obtained with commonly used recursive bisection methods.","PeriodicalId":325978,"journal":{"name":"Proceedings of 3rd International Conference on Algorithms and Architectures for Parallel Processing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd International Conference on Algorithms and Architectures for Parallel Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAPP.1997.651533","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, LSOM (Load-balancing Self-Organizing Map), a neural network based on Kohonen's self-organizing map is proposed for the problem of mapping finite-element method (FEM) grids to distributed-memory parallel computers with mesh interconnection networks. The rough global ordering produced by LSOM is then combined with the local refinement Kernighan-Lin algorithm (called LSOM-KL) to obtain the solution. LSOM-KL obtained a load imbalance of less than 0.1% and a low number of hops, comparable to results obtained with commonly used recursive bisection methods.