{"title":"Visualization of Large Graphs Using GPU Computing","authors":"T. Ježowicz, M. Kudelka, J. Platoš, V. Snás̃el","doi":"10.1109/INCoS.2013.126","DOIUrl":null,"url":null,"abstract":"Graphs may be used to visualize relationships between objects. Relations are represented by edges and objects are called nodes. When graph is drawn, one can easily see and understand the basic structure of data. Many different applications can be found in social network analysis, computer networks, scientific literature analysis, etc. However drawing large graphs (thousands or a millions of nodes), is still challenging problem. There exist many different algorithms for drawing graphs. Each algorithm has specific behavior and different applications and limits. Some algorithms are focused on quality while others are more suitable for large graphs. This paper aims to speed up the computation using GPU, so larger graphs can be visualized in acceptable time, or visualization can be done even in real-time.","PeriodicalId":353706,"journal":{"name":"2013 5th International Conference on Intelligent Networking and Collaborative Systems","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 5th International Conference on Intelligent Networking and Collaborative Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INCoS.2013.126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Graphs may be used to visualize relationships between objects. Relations are represented by edges and objects are called nodes. When graph is drawn, one can easily see and understand the basic structure of data. Many different applications can be found in social network analysis, computer networks, scientific literature analysis, etc. However drawing large graphs (thousands or a millions of nodes), is still challenging problem. There exist many different algorithms for drawing graphs. Each algorithm has specific behavior and different applications and limits. Some algorithms are focused on quality while others are more suitable for large graphs. This paper aims to speed up the computation using GPU, so larger graphs can be visualized in acceptable time, or visualization can be done even in real-time.