{"title":"Multiple Network Embedding into Hybercubes","authors":"Ajay K. Gupta, Susanne E. Hambrusch","doi":"10.1109/DMCC.1990.556400","DOIUrl":null,"url":null,"abstract":"Abstract In this paper we consider the problem of embedding r guest networks G0, ..., Gr−1, into a k-dimensional hypercube H so that every processor of H is assigned at most r guest processors and dilation and congestion are minimized. Network G, can be a complete binary tree, a leap tree, a linear array, or a mesh. We show that r such guest networks can simultaneously be embedded into H without a significant increase in dilation and congestion compared to the embedding of a single network when r ≤ k. For r > k, the increase in the cost measures is proportional to r/k. We consider two models which differ in the requirements imposed on the r guest processors assigned to a processor of H.","PeriodicalId":204431,"journal":{"name":"Proceedings of the Fifth Distributed Memory Computing Conference, 1990.","volume":"108 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fifth Distributed Memory Computing Conference, 1990.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DMCC.1990.556400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Abstract In this paper we consider the problem of embedding r guest networks G0, ..., Gr−1, into a k-dimensional hypercube H so that every processor of H is assigned at most r guest processors and dilation and congestion are minimized. Network G, can be a complete binary tree, a leap tree, a linear array, or a mesh. We show that r such guest networks can simultaneously be embedded into H without a significant increase in dilation and congestion compared to the embedding of a single network when r ≤ k. For r > k, the increase in the cost measures is proportional to r/k. We consider two models which differ in the requirements imposed on the r guest processors assigned to a processor of H.