Kengo Hayashi, Takashi Shimizu, Naohisa Sakamoto, J. Nonaka
{"title":"Parallel particle-based volume rendering using adaptive particle size adjustment technique","authors":"Kengo Hayashi, Takashi Shimizu, Naohisa Sakamoto, J. Nonaka","doi":"10.1145/3139295.3139311","DOIUrl":null,"url":null,"abstract":"Numerical simulation results generated from high performance computing (HPC) environments have become extremely concurrent with the recent advances in computer simulation technology, and there is an increase in the demand for extra-scale visualization techniques. In this paper, we propose a parallel particle-based volume rendering method based on adaptive particle size adjustment technique, which is suitable for handling large-scale and complex distributed volume datasets in the HPC environment. In the experiment, the proposed technique is applied to a large-scale unstructured thermal fluid simulation, and a performance model is constructed to confirm the effectiveness of the proposed technique.","PeriodicalId":92446,"journal":{"name":"SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand)","volume":"19 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2017-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGGRAPH Asia 2017 Symposium on Visualization. SIGGRAPH Asia Symposium on Visualization (2017 : Bangkok, Thailand)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3139295.3139311","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Numerical simulation results generated from high performance computing (HPC) environments have become extremely concurrent with the recent advances in computer simulation technology, and there is an increase in the demand for extra-scale visualization techniques. In this paper, we propose a parallel particle-based volume rendering method based on adaptive particle size adjustment technique, which is suitable for handling large-scale and complex distributed volume datasets in the HPC environment. In the experiment, the proposed technique is applied to a large-scale unstructured thermal fluid simulation, and a performance model is constructed to confirm the effectiveness of the proposed technique.