基于GPU的蒙特卡洛放疗剂量并行计算

GPU-based Parallel Monte Carlo Simulation for Radiotherapy Dose Calculation

目的:蒙特卡洛模拟在放疗剂量计算领域被广泛视为最精确的计算方法,但对于日常的临床应用,其效率仍有较大提升需求和空间。方法:本文会呈现放疗剂量计算领域的最新成果--维持相同的粒子输运原理的同时,使用CUDA语言,利用显卡的GPU(Graphic Processing Unit)并行处理蒙特卡洛计算中的主要过程,计算光子剂量沉积。这样既可以保证不失去蒙卡模拟的精度,又可以极大地提高运算速度。结果:实践表明在使用NVIDIA GTX460 1G DDR5 plus INTEL i52300的硬件设备,在GPU上并行计算蒙特卡洛放疗剂量沉积时,计算100万个光子剂量沉积时加速因子达到116.6,处理1000万光子入射,加速因子可达127.5。结论:本文中利用显卡GPU运行CUDA语言对放疗剂量计算进行模拟,是一种可以大幅有效提高剂量计算效率方法。

Objective： Monte Carlo simulation is commonly considered to be the most accurate dose calculation method in radiotherapy. However, its efficiency still requires improvement for many routine clinical applications.Methods： This paper will present recent progresses in GPU-based Monte Carlo dose calculation. We utilizes the parallel computation ability of a GPU to achieve high efficiency, while maintaining the same particle transport physics as in the original Monte Carlo simulation code and therefore obtains the same level of simulation accuracy. Results： Our research results show that using an NVIDIA GTX460 GPU card against an INTEL i5 2300 in computing a one-million sample with all 336 processor cores working together, speed-up factors can be as high as 116.6,as for a ten-million situation,even obtain a result as high as 127.5. Conclusions：Using GPU and CUDA to process a Monte Carlo simulation can highly improve the efficiency of dose calculation.