{"title":"Parallel data processing in a distributed object-oriented model","authors":"John R. Monde, Maria Seale","doi":"10.1109/DOA.1999.794059","DOIUrl":null,"url":null,"abstract":"The limitations of serial processors for managing large computationally intensive dataset problems in fields such as visualization and geographical information systems (GIS) are well known. Parallel processing techniques, where one or many computational tasks are distributed across a number of processing elements, have been proposed as a solution to the problem. The paper presents a distributed object oriented visualization model being developed by the University of Southern Mississippi to demonstrate interactive visualization of oceanographic data. This model allows data location independence as well as data structure independence. The test case for which we present experimental results involves visualization of oceanographic data (salinity, sound speed profile, currents, temperature, and depth) with Windows NT Pentium class computers serving as both server and client workstations.","PeriodicalId":360176,"journal":{"name":"Proceedings of the International Symposium on Distributed Objects and Applications","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Symposium on Distributed Objects and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DOA.1999.794059","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The limitations of serial processors for managing large computationally intensive dataset problems in fields such as visualization and geographical information systems (GIS) are well known. Parallel processing techniques, where one or many computational tasks are distributed across a number of processing elements, have been proposed as a solution to the problem. The paper presents a distributed object oriented visualization model being developed by the University of Southern Mississippi to demonstrate interactive visualization of oceanographic data. This model allows data location independence as well as data structure independence. The test case for which we present experimental results involves visualization of oceanographic data (salinity, sound speed profile, currents, temperature, and depth) with Windows NT Pentium class computers serving as both server and client workstations.