Y. Dewaraja, Michael Ljungberg, Amitava Majumdar, Abhijit Bose, K. Koral
{"title":"A parallel Monte Carlo code for planar and SPECT imaging: implementation, verification and applications in /sup 131/I SPECT","authors":"Y. Dewaraja, Michael Ljungberg, Amitava Majumdar, Abhijit Bose, K. Koral","doi":"10.1109/NSSMIC.2000.949310","DOIUrl":null,"url":null,"abstract":"This paper reports the implementation of the SIMIND Monte Carlo code on a IBM SP2 distributed memory parallel computer. Basic aspects of running Monte Carlo particle transport calculations on parallel architectures are described. The authors' parallelization is based on equally partitioning photons among the processors and uses the Message Passing Interface (MPI) library for interprocessor communication and the Scalable Parallel Random Number Generator (SPRNG) to generate uncorrelated random number streams. These parallelization techniques are also applicable to other distributed memory architectures. A linear increase in computing speed with the number of processors is demonstrated for up to 32 processors. This speed-up is especially significant in Single Photon Emission Computed Tomography (SPECT) simulations involving higher energy photon emitters, where explicit modeling of the phantom and collimator is required. For /sup 131/I, the accuracy of the parallel code is demonstrated by comparing simulated and experimental SPECT images from a heart/thorax phantom. Clinically realistic SPECT simulations using the voxel-man phantom are carried out to assess scatter and attenuation correction.","PeriodicalId":445100,"journal":{"name":"2000 IEEE Nuclear Science Symposium. Conference Record (Cat. No.00CH37149)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2000 IEEE Nuclear Science Symposium. Conference Record (Cat. No.00CH37149)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NSSMIC.2000.949310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper reports the implementation of the SIMIND Monte Carlo code on a IBM SP2 distributed memory parallel computer. Basic aspects of running Monte Carlo particle transport calculations on parallel architectures are described. The authors' parallelization is based on equally partitioning photons among the processors and uses the Message Passing Interface (MPI) library for interprocessor communication and the Scalable Parallel Random Number Generator (SPRNG) to generate uncorrelated random number streams. These parallelization techniques are also applicable to other distributed memory architectures. A linear increase in computing speed with the number of processors is demonstrated for up to 32 processors. This speed-up is especially significant in Single Photon Emission Computed Tomography (SPECT) simulations involving higher energy photon emitters, where explicit modeling of the phantom and collimator is required. For /sup 131/I, the accuracy of the parallel code is demonstrated by comparing simulated and experimental SPECT images from a heart/thorax phantom. Clinically realistic SPECT simulations using the voxel-man phantom are carried out to assess scatter and attenuation correction.