Cameron Christensen, T. Fogal, Nathan Luehr, Cliff Woolley
{"title":"Topology-aware image compositing using NVLink","authors":"Cameron Christensen, T. Fogal, Nathan Luehr, Cliff Woolley","doi":"10.1109/LDAV.2016.7874334","DOIUrl":null,"url":null,"abstract":"Compositing is a significant factor in distributed visualization performance at scale on high-performance computing (HPC) systems. For applications such as Para VieworVisIt, the common approach is “sort-last” rendering. For this approach, data are split up to be rendered such that each MPI rank has one or more portions of the over-all domain. After rendering its individual piece(s), each rank has one or more partial images that must be composited with the others to form the final image. The common approach for this step is to use a tree-like communication pattern to reduce the rendered images down to a single image to be displayed to the user. A variety of algorithms have been explored to perform this step efficiently in order to achieve interactive rendering on massive systems [7, 3, 8, 4].","PeriodicalId":148570,"journal":{"name":"2016 IEEE 6th Symposium on Large Data Analysis and Visualization (LDAV)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 6th Symposium on Large Data Analysis and Visualization (LDAV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LDAV.2016.7874334","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
Compositing is a significant factor in distributed visualization performance at scale on high-performance computing (HPC) systems. For applications such as Para VieworVisIt, the common approach is “sort-last” rendering. For this approach, data are split up to be rendered such that each MPI rank has one or more portions of the over-all domain. After rendering its individual piece(s), each rank has one or more partial images that must be composited with the others to form the final image. The common approach for this step is to use a tree-like communication pattern to reduce the rendered images down to a single image to be displayed to the user. A variety of algorithms have been explored to perform this step efficiently in order to achieve interactive rendering on massive systems [7, 3, 8, 4].