Division of Imaging and Applied Mathematics, OSEL, CDRH, U.S. Food and Drug Administration, Silver Spring, Maryland 20993-0002, USA.
Med Phys. 2009 Nov;36(11):4878-80. doi: 10.1118/1.3231824.
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).
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).
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.
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.
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)。
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。
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。
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。