{"title":"使用四叉树存储格式的稀疏矩阵计算","authors":"I. Šimeček","doi":"10.1109/SYNASC.2009.55","DOIUrl":null,"url":null,"abstract":"Computations with sparse matrices are widespread in scientific projects. Used data format affects strongly the performance. Efficient formats for storing sparse matrices are still under development, since the computation using widely-used formats (like XY or CSR) is slow and specialized formats (like SPARSITY or CARB) have a large transformation overhead.In this paper, we represent some improvements to the quadtree storage format. We also compare the performance during the execution of some basic routines from the linear algebra using widely-used formats and the quadtree storage format.","PeriodicalId":286180,"journal":{"name":"2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"520 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Sparse Matrix Computations Using the Quadtree Storage Format\",\"authors\":\"I. Šimeček\",\"doi\":\"10.1109/SYNASC.2009.55\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Computations with sparse matrices are widespread in scientific projects. Used data format affects strongly the performance. Efficient formats for storing sparse matrices are still under development, since the computation using widely-used formats (like XY or CSR) is slow and specialized formats (like SPARSITY or CARB) have a large transformation overhead.In this paper, we represent some improvements to the quadtree storage format. We also compare the performance during the execution of some basic routines from the linear algebra using widely-used formats and the quadtree storage format.\",\"PeriodicalId\":286180,\"journal\":{\"name\":\"2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing\",\"volume\":\"520 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SYNASC.2009.55\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2009.55","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sparse Matrix Computations Using the Quadtree Storage Format
Computations with sparse matrices are widespread in scientific projects. Used data format affects strongly the performance. Efficient formats for storing sparse matrices are still under development, since the computation using widely-used formats (like XY or CSR) is slow and specialized formats (like SPARSITY or CARB) have a large transformation overhead.In this paper, we represent some improvements to the quadtree storage format. We also compare the performance during the execution of some basic routines from the linear algebra using widely-used formats and the quadtree storage format.