多核和多核处理器上质子束治疗图像重建的混合MPI+OpenMP并行化

James Della-Giustina, C. Barajas, M. Gobbert, D. Mackin, J. Polf
{"title":"多核和多核处理器上质子束治疗图像重建的混合MPI+OpenMP并行化","authors":"James Della-Giustina, C. Barajas, M. Gobbert, D. Mackin, J. Polf","doi":"10.22360/springsim.2018.hpc.014","DOIUrl":null,"url":null,"abstract":"The advantage of proton beam therapy is that the lethal dose of radiation is delivered by a sharp increase toward the end of the beam range, known as the Bragg peak (BP), with no dose delivered beyond. By using these characteristics of the BP, radiation dose to the tumor can be maximized, with greatly reduced radiation dose to the surrounding healthy tissue. If the secondary gamma rays that are emitted through interaction of the protons in the beam with atoms in the patient tissue could be imaged in (near) real-time during beam delivery, it could provide a means of visualizing the delivery of dose for verification of proper treatment delivery. However, such imaging requires very fast image reconstruction to be feasible. This project focuses on measuring the performance of a new parallel version of the CCI (Compton camera imaging) image reconstruction algorithm. We show two conclusions: (i) The new hybrid MPI+OpenMP parallelization of the code on the many-core Intel Xeon Phi KNL processor with 68 computational cores makes fast reconstruction times possible and thus enables the use of CCI in real time during treatment. (ii) A compute node with two of the latest multi-core Intel Skylake CPUs with 24 cores performs even better in a first comparison of both types of processors available on Stampede2 at the Texas Advanced Computing Center (TACC).","PeriodicalId":413389,"journal":{"name":"Spring Simulation Multiconference","volume":"134 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Hybrid MPI+OpenMP parallelization of image reconstruction in proton beam therapy on multi-core and many-core processors\",\"authors\":\"James Della-Giustina, C. Barajas, M. Gobbert, D. Mackin, J. Polf\",\"doi\":\"10.22360/springsim.2018.hpc.014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The advantage of proton beam therapy is that the lethal dose of radiation is delivered by a sharp increase toward the end of the beam range, known as the Bragg peak (BP), with no dose delivered beyond. By using these characteristics of the BP, radiation dose to the tumor can be maximized, with greatly reduced radiation dose to the surrounding healthy tissue. If the secondary gamma rays that are emitted through interaction of the protons in the beam with atoms in the patient tissue could be imaged in (near) real-time during beam delivery, it could provide a means of visualizing the delivery of dose for verification of proper treatment delivery. However, such imaging requires very fast image reconstruction to be feasible. This project focuses on measuring the performance of a new parallel version of the CCI (Compton camera imaging) image reconstruction algorithm. We show two conclusions: (i) The new hybrid MPI+OpenMP parallelization of the code on the many-core Intel Xeon Phi KNL processor with 68 computational cores makes fast reconstruction times possible and thus enables the use of CCI in real time during treatment. (ii) A compute node with two of the latest multi-core Intel Skylake CPUs with 24 cores performs even better in a first comparison of both types of processors available on Stampede2 at the Texas Advanced Computing Center (TACC).\",\"PeriodicalId\":413389,\"journal\":{\"name\":\"Spring Simulation Multiconference\",\"volume\":\"134 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Spring Simulation Multiconference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22360/springsim.2018.hpc.014\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spring Simulation Multiconference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22360/springsim.2018.hpc.014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

质子束治疗的优点是,致命剂量的辐射是通过向光束范围的末端(即布拉格峰(BP))急剧增加来传递的,而不会传递超过该范围的剂量。利用BP的这些特性,可以最大限度地提高对肿瘤的辐射剂量,同时大大降低对周围健康组织的辐射剂量。如果通过光束中的质子与患者组织中的原子相互作用发射的二次伽马射线可以在光束传递过程中(近)实时成像,它可以提供一种可视化剂量传递的方法,以验证适当的治疗传递。然而,这种成像需要非常快的图像重建才能实现。这个项目的重点是测量一个新的并行版本的CCI(康普顿相机成像)图像重建算法的性能。我们得出了两个结论:(i)在具有68个计算核的多核Intel Xeon Phi KNL处理器上,新的混合MPI+OpenMP并行化代码使快速重建时间成为可能,从而使CCI在治疗期间能够实时使用。(ii)在德克萨斯州高级计算中心(TACC)的Stampede2上对两种类型的处理器进行首次比较时,带有两个最新的24核英特尔Skylake cpu的计算节点表现更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid MPI+OpenMP parallelization of image reconstruction in proton beam therapy on multi-core and many-core processors
The advantage of proton beam therapy is that the lethal dose of radiation is delivered by a sharp increase toward the end of the beam range, known as the Bragg peak (BP), with no dose delivered beyond. By using these characteristics of the BP, radiation dose to the tumor can be maximized, with greatly reduced radiation dose to the surrounding healthy tissue. If the secondary gamma rays that are emitted through interaction of the protons in the beam with atoms in the patient tissue could be imaged in (near) real-time during beam delivery, it could provide a means of visualizing the delivery of dose for verification of proper treatment delivery. However, such imaging requires very fast image reconstruction to be feasible. This project focuses on measuring the performance of a new parallel version of the CCI (Compton camera imaging) image reconstruction algorithm. We show two conclusions: (i) The new hybrid MPI+OpenMP parallelization of the code on the many-core Intel Xeon Phi KNL processor with 68 computational cores makes fast reconstruction times possible and thus enables the use of CCI in real time during treatment. (ii) A compute node with two of the latest multi-core Intel Skylake CPUs with 24 cores performs even better in a first comparison of both types of processors available on Stampede2 at the Texas Advanced Computing Center (TACC).
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信