《计算机应用研究》|Application Research of Computers

基于GPU异构平台的实时CT图像重建系统的研究

Research on real-time computed tomographic reconstruction system based on GPU heterogeneous platform

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作者 夏松竹,杨静,方宝辉,徐金秀
机构 1.哈尔滨工程大学 计算机科学与技术学院,哈尔滨 150000;2.江南计算技术研究所,江苏 无锡 214083
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文章编号 1001-3695(2019)06-058-1879-04
DOI 10.19734/j.issn.1001-3695.2017.12.0859
摘要 针对采用单CPU CT图像重建时间长,采用CPU集群重建成本及能耗高的问题,提出了CPU多线程+GPU的异构重建模型。采用CPU多线程流水线模式,将整个任务分解为若干个处理阶段,相邻的两个阶段之间以循环缓存连接,上一阶段完成一次计算任务后将数据放到循环缓存里,然后继续下一次的计算任务,下一阶段探测到循环缓存里有数据后从缓存里取出数据开始计算。各个任务是并行处理任务的,针对某一耗时瓶颈模块再采用GPU并行加速,充分发挥CPU和GPU的计算资源。CPU多线程+GPU模型相对于CPU多线程模型加速了16.45倍,相对于串行CT图像重建加速了20.5倍以上。将CPU多线程+GPU模型重建的图像与CPU串行程序重建的CT图像相比较,数据结果在误差范围内,满足实验设计要求。提出的图像重建模型采用成本较低的GPU显卡就实现了性能大幅提升,大大降低了CT图像重建系统的成本及功耗,而成本及功耗的降低会引起CT医疗诊断费用的降低,最终惠及广大病患。
关键词 GPU; CT图像重建; 流水线; 反投影
基金项目 国家重点研发计划资助项目(2017YFB0202702)
国家“973”计划资助项目(2014CB744100)
国家“863”计划资助项目(2012AA01A306)
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英文标题 Research on real-time computed tomographic reconstruction system based on GPU heterogeneous platform
作者英文名 Xia Songzhu, Yang Jing, Fang Baohui, Xu Jinxiu
机构英文名 1.College of Computer Science & Technology,Harbin Engineering University,Harbin 150000,China;2.Jiangnan Institute of Computing Technology,Wuxi Jiangsu 214083,China
英文摘要 In order to solve long time consuming problems of single CPU computed tomographic(CT) reconstruction and the problems of high cost and high energy consumption in the reconstruction using CPU cluster, this paper proposed a heterogeneous reconstruction model of CPU multithreads +GPU. This model used the CPU multithread pipelining pattern, it divided the whole task into several stages, and connected each two adjacent phases by a loop buffer. Once the calculation of the current task stage completed, the data would be put into the loop buffer, and then the next computing task would continue to execute. When the data in the loop buffers was detected by the latter stage, the data would be removed from the loop buffers and calculated. In this way, each thread processed tasks in a parallel way. For a time consuming bottleneck module, it adopted the parallel acceleration of GPU to give full play to the computing resources of CPU and GPU. The CPU multithreads +GPU model is 16.45 times faster than the CPU multithreaded model, and accelerates more than 20.5 times faster than serial CT image reconstruction. By comparing with experimental results of CPU serial program, the result of the CPU multithreads +GPU model can meet the experimental design requirement in the range of error tolerance. The image reconstruction model proposed by using low cost GPU has greatly enhanced performance, greatly reduces the cost and power consumption of the CT system. The reduction in cost and power consumption will lead to a reduction in the cost of CT medical diagnosis, which will eventually benefit patients.
英文关键词 GPU; CT image reconstruction; pipeline; back-projection
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收稿日期 2017/12/12
修回日期 2018/2/28
页码 1879-1882
中图分类号 TP391.41
文献标志码 A