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使用大规模并行图形处理单元加速体素化几何中的光子输运的蒙特卡罗模拟。

Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit.

机构信息

Division of Imaging and Applied Mathematics, OSEL, CDRH, U.S. Food and Drug Administration, Silver Spring, Maryland 20993-0002, USA.

出版信息

Med Phys. 2009 Nov;36(11):4878-80. doi: 10.1118/1.3231824.

Abstract

PURPOSE

It is a known fact that Monte Carlo simulations of radiation transport are computationally intensive and may require long computing times. The authors introduce a new paradigm for the acceleration of Monte Carlo simulations: The use of a graphics processing unit (GPU) as the main computing device instead of a central processing unit (CPU).

METHODS

A GPU-based Monte Carlo code that simulates photon transport in a voxelized geometry with the accurate physics models from PENELOPE has been developed using the CUDATM programming model (NVIDIA Corporation, Santa Clara, CA).

RESULTS

An outline of the new code and a sample x-ray imaging simulation with an anthropomorphic phantom are presented. A remarkable 27-fold speed up factor was obtained using a GPU compared to a single core CPU.

CONCLUSIONS

The reported results show that GPUs are currently a good alternative to CPUs for the simulation of radiation transport. Since the performance of GPUs is currently increasing at a faster pace than that of CPUs, the advantages of GPU-based software are likely to be more pronounced in the future.

摘要

目的

众所周知,辐射传输的蒙特卡罗模拟计算密集,可能需要很长的计算时间。作者引入了一种新的蒙特卡罗模拟加速范例:使用图形处理单元 (GPU) 作为主要计算设备,而不是中央处理单元 (CPU)。

方法

使用 CUDATM 编程模型 (NVIDIA Corporation,Santa Clara,CA),开发了一个基于 GPU 的蒙特卡罗代码,该代码使用准确的 PENELOPE 物理模型模拟体素化几何中的光子传输。

结果

本文介绍了新代码的大纲和一个带有人体模型的 X 射线成像模拟示例。与单个 CPU 核心相比,使用 GPU 可获得高达 27 倍的加速因子。

结论

报告的结果表明,GPU 目前是辐射传输模拟中 CPU 的一种很好的替代方案。由于 GPU 的性能目前比 CPU 增长得更快,因此基于 GPU 的软件的优势在未来可能更加明显。

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