GPU-based Monte Carlo simulation for light propagation in complex heterogeneous tissues
GPU-based Monte Carlo simulation for light propagation in complex heterogeneous tissues
复制标题
基于 GPU 的蒙特卡罗模拟复杂异质组织中的光传播
DOI：
10.1364/oe.18.006811
复制
发表时间：
2010-03-29
期刊：
影响因子：
3.8
通讯作者：
Tian, Jie
中科院分区：
文献类型：
--
作者：
Ren, Nunu;Liang, Jimin;Tian, Jie
蒙特卡罗（MC）方法作为模拟光在异质组织中传播的最精确模型，在光学分子成像领域得到了广泛的应用。然而，MC方法是耗时的，由于大量的光子在组织中的传播的计算。异质组织的结构复杂性进一步增加了计算时间。本文提出了一种光在异质组织中传播的MC模拟的并行实现方法，其表面由不同数量的三角形网格构成。在图形处理单元（GPU）的基础上，利用统一计算设备架构（CUDA）平台实现代码，并充分利用GPU上的常量内存和纹理内存，对代码进行优化，尽可能降低访问延迟。我们测试的实现在同构和异构鼠标模型与NVIDIA GTX 260卡和2.40 GHz的英特尔至强CPU。实验结果证明了在GPU上并行MC模拟的可行性和有效性。(C)2010年美国光学学会
As the most accurate model for simulating light propagation in heterogeneous tissues, Monte Carlo (MC) method has been widely used in the field of optical molecular imaging. However, MC method is time-consuming due to the calculations of a large number of photons propagation in tissues. The structural complexity of the heterogeneous tissues further increases the computational time. In this paper we present a parallel implementation for MC simulation of light propagation in heterogeneous tissues whose surfaces are constructed by different number of triangle meshes. On the basis of graphics processing units (GPU), the code is implemented with compute unified device architecture (CUDA) platform and optimized to reduce the access latency as much as possible by making full use of the constant memory and texture memory on GPU. We test the implementation in the homogeneous and heterogeneous mouse models with a NVIDIA GTX 260 card and a 2.40GHz Intel Xeon CPU. The experimental results demonstrate the feasibility and efficiency of the parallel MC simulation on GPU. (C) 2010 Optical Society of America