A Fast Implementation of IMRT Algorithm by the GPU

LI Xia ZHANG Shuzhi WU Zhangwen HOU Qing GOU Chengjun

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A Fast Implementation of IMRT Algorithm by the GPU

更新时间：2021-03-05

- A Fast Implementation of IMRT Algorithm by the GPU
- NUCLEAR TECHNIQUES Vol. 35, Issue 4, (2012)
- 作者机构：
  
  辐射物理及技术教育部重点实验室,四川大学原子核科学技术研究所
- 作者简介：
- 基金信息：
  
  国家科技支撑计划项目(2011BAI12B05)资助;四川大学辐射物理及技术教育部重点实验室开放课题的资助
- DOI：
  CLC： R730.5;TP391.41
- Published：01 April 2012
- 稿件说明：
移动端阅览
[1]李霞,张树芝,吴章文,侯氢,勾成俊.基于GPU的快速调强算法研究[J].核技术,2012,35(04):297-300.

LI Xia ZHANG Shuzhi WU Zhangwen HOU Qing GOU Chengjun. A Fast Implementation of IMRT Algorithm by the GPU[J]. Nuclear techniques, 2012, 35(4): 297-300.
[1]李霞,张树芝,吴章文,侯氢,勾成俊.基于GPU的快速调强算法研究[J].核技术,2012,35(04):297-300. DOI：

LI Xia ZHANG Shuzhi WU Zhangwen HOU Qing GOU Chengjun. A Fast Implementation of IMRT Algorithm by the GPU[J]. Nuclear techniques, 2012, 35(4): 297-300. DOI：

摘要

研究了使用图形处理器（GPU）对调强放射治疗计划系统（IMRT）中分子动力学优化方法的加速方法及效果。利用统一计算设备构架（CUDA）平台

分别对4个临床肿瘤调强病例的笔束剂量响应矩阵的乘积运算进行GPU并行优化加速。比较和分析GPU并行加速笔束剂量响应矩阵的乘积运算的结果。结果表明

GPU平台上的计算结果与CPU平台的计算结果存在一定的差异

其最大相对误差为5.822×10

-7

这一差异在临床上是可以接受的

GPU并行运算可以使计算速度提升9-12倍。

Abstract

In this paper

we study the speedup effect when graphics processing unit（GPU） is used in intensity modulated radiation therapy（IMRT）.The pencil-beam-dose-response matrix multiplication calculation in optimization process is implemented in compute unified device architecture（CUDA） running on the GPU

and C running on the CPU.The speedup factors are compared and analyzed.Test results show that the maximum relative error of 5.822×10

-7

can be found between the CPU results and GPU results

such discrepancy level is acceptable clinically

and the speedup factors reach 9-12 by using GPU.

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