GPU-based parallel computing for fast image reconstruction in micro CT

SHEN Fei1; 2 CHEN Rongchang1; 2 XIAO Tiqiao1 1

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GPU-based parallel computing for fast image reconstruction in micro CT

更新时间：2021-03-05

- GPU-based parallel computing for fast image reconstruction in micro CT
- NUCLEAR TECHNIQUES Vol. 34, Issue 6, (2011)
- 作者机构：
  
  1. 中国科学院上海应用物理研究所
  2. 中国科学院研究生院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.41
- Published：01 June 2011
- 稿件说明：
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[1]沈飞,陈荣昌,肖体乔.基于GPU并行计算实现快速显微CT重构[J].核技术,2011,34(06):401-405.

SHEN Fei1, 2 CHEN Rongchang1, 2 XIAO Tiqiao1 1. GPU-based parallel computing for fast image reconstruction in micro CT[J]. Nuclear techniques, 2011, 34(6): 401-405.
[1]沈飞,陈荣昌,肖体乔.基于GPU并行计算实现快速显微CT重构[J].核技术,2011,34(06):401-405. DOI：

SHEN Fei1, 2 CHEN Rongchang1, 2 XIAO Tiqiao1 1. GPU-based parallel computing for fast image reconstruction in micro CT[J]. Nuclear techniques, 2011, 34(6): 401-405. DOI：

摘要

图像处理器（GPU

graphics processing unit）是一种高度并行化的流式处理器

将其引入显微CT重构可大幅加快重构速度。将CT重建程序并行化设计

使用CUDA编程标准成功实现程序编写

在单块NVDIA GTX295的GPU上运行CT重建程序。结果表明

与CPU串行方法相比

使用GPU并行计算最高可得150倍左右的加速比

将重构时间缩短至15 min左右。因此可认为

GPU并行处理可显著提高显微CT重构速度

采用优化设计的GPU服务器还可进一步提高重构速度。

Abstract

The micro-CT of the X-ray imaging beamline at Shanghai Synchrotron Radiation Facility can achieve sub-micron resolution

while the data size for a single set of CT projection is often dozens of giga bytes.With the serials methods

several hours of CPU time are usually needed for processing a single set of data

while the beamline operates 24 hours a day and seven days a week

with dozens of CT data sets being collected by users every day.Conventional methods based on CPU are no longer applicable for processing such massive data sets.GPU is a highly parallel stream processor

which is capable of accelerating the CT reconstruction significantly.In this paper

CUDA programming standard is used to program the paralleled CT reconstruction.The test results show that the program running in a NVDIA GTX295 GPU can accelerate the CT reconstruction by a factor of 150.The reconstructing time could be shortened to 15 minutes or around.The reconstruction speed shall be further improved by a GPU server with more pieces of GPU chips.

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Related Institution

School of Nuclear Science and Engineering, East China University of Technology

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