{"title":"Parallel data acquisition for visualization of very large sparse matrices","authors":"D. Langr, I. Šimeček, P. Tvrdík, T. Dytrych","doi":"10.1109/SYNASC.2013.51","DOIUrl":null,"url":null,"abstract":"The problem of visualization of very large sparse matrices emerging on massively parallel computer systems is identified and a new method along with an accompanying algorithm for parallel acquisition of visualization data for such matrices are presented. The proposed method is based on downsampling a matrix into blocks for which the desired visualization data are saved into a file. This file is then supposed to be downloaded and processed into a final image on a personal computer. Experimental results for the evaluation of the performance and scalability of the proposed algorithm are further provided and discussed.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2013.51","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
The problem of visualization of very large sparse matrices emerging on massively parallel computer systems is identified and a new method along with an accompanying algorithm for parallel acquisition of visualization data for such matrices are presented. The proposed method is based on downsampling a matrix into blocks for which the desired visualization data are saved into a file. This file is then supposed to be downloaded and processed into a final image on a personal computer. Experimental results for the evaluation of the performance and scalability of the proposed algorithm are further provided and discussed.
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