高性能影像处理平台构建及显微CT图像重建算法的并行实现  

A high performance image processing platform based on CPU-GPU heterogeneous cluster with parallel image reconstructions for micro-CT

作　　者：丁喻[1,2] 漆玉金[1] 张雪竹[1] 赵翠兰[1] 

机构地区：[1]中国科学院上海应用物理研究所,上海201800 [2]中国科学院研究生院,北京100049

出　　处：《核技术》2011年第8期626-631,共6页Nuclear Techniques

基　　金：国家自然科学基金项目(10875162)资助

摘　　要：介绍了一种高性能的影像处理平台,该平台基于CPU-GPU异构集群,初始系统是由一台Dell Precision T7500和一台HP XW8600工作站构建而成,系统采用消息传递接口(MPI)和CUDA(Compute Unified Device Architecture)为程序并行编程和运行环境。在此平台上成功实现了X射线显微CT成像图像重建算法(FDK)的并行加速计算与处理。结果表明,GPU单机比CPU单机的平均计算速度提高近194倍,CPU-GPU集群比单独CPU集群的计算速度提高46倍,计算效率显著提高,能满足快速三维图像重建及图像结果的实时显示要求。CPU-GPU异构集群是构建高性能影像处理平台的有效途径。In this paper,we report the development of a high-performance image processing platform,which is based on CPU-GPU heterogeneous cluster.Currently,it consists of a Dell Precision T7500 and HP XW8600 workstations with parallel programming and runtime environment,using the message-passing interface（MPI） and CUDA（Compute Unified Device Architecture）.We succeeded in developing parallel image processing techniques for 3D image reconstruction of X-ray micro-CT imaging.The results show that a GPU provides a computing efficiency of about 194 times faster than a single CPU,and the CPU-GPU clusters provides a computing efficiency of about 46 times faster than the CPU clusters.These meet the requirements of rapid 3D image reconstruction and real time image display.In conclusion,the use of CPU-GPU heterogeneous cluster is an effective way to build high-performance image processing platform.

关 键 词：CPU-GPU异构集群 并行计算 三维图像重建 

分 类 号：TP317.4[自动化与计算机技术—计算机软件与理论]