{"title":"Cone beam tomography using MPI on heterogeneous workstation clusters","authors":"D. Reimann, V. Chaudhary, M. Flynn, I.K. Sethi","doi":"10.1109/MPIDC.1996.534106","DOIUrl":null,"url":null,"abstract":"With cone beam CT long computation and a large amount of memory is required. The majority of the computation is in the backprojection step. We have investigated the use of parallel methods on workstation clusters using MPI to overcome both the long processing time and lessen memory requirements on individual workstations. We used the asynchronous MPI implementation to reconstruct a 256/sup 3/ volume from 256/sup 2/ projection views with 6 workstations. Our previous efforts in load balancing resulted in processor utilization of 81.8%. Use of asynchronous communication in the cone beam CT problem has improved processor utilization to 91.9%.","PeriodicalId":432081,"journal":{"name":"Proceedings. Second MPI Developer's Conference","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. Second MPI Developer's Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MPIDC.1996.534106","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
With cone beam CT long computation and a large amount of memory is required. The majority of the computation is in the backprojection step. We have investigated the use of parallel methods on workstation clusters using MPI to overcome both the long processing time and lessen memory requirements on individual workstations. We used the asynchronous MPI implementation to reconstruct a 256/sup 3/ volume from 256/sup 2/ projection views with 6 workstations. Our previous efforts in load balancing resulted in processor utilization of 81.8%. Use of asynchronous communication in the cone beam CT problem has improved processor utilization to 91.9%.
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