Liu T, Ding A, Xu X
Rensselaer Polytechnic Inst., Troy, NY.
Med Phys. 2012 Jun;39(6Part17):3818. doi: 10.1118/1.4735582.
To develop a Graphics Processing Unit (GPU) based Monte Carlo (MC) code that accelerates dose calculations on a dual-GPU system.
We simulated a clinical case of prostate cancer treatment. A voxelized abdomen phantom derived from 120 CT slices was used containing 218×126×60 voxels, and a GE LightSpeed 16-MDCT scanner was modeled. A CPU version of the MC code was first developed in C++ and tested on Intel Xeon X5660 2.8GHz CPU, then it was translated into GPU version using CUDA C 4.1 and run on a dual Tesla m 090 GPU system. The code was featured with automatic assignment of simulation task to multiple GPUs, as well as accurate calculation of energy- and material- dependent cross-sections.
Double-precision floating point format was used for accuracy. Doses to the rectum, prostate, bladder and femoral heads were calculated. When running on a single GPU, the MC GPU code was found to be ×19 times faster than the CPU code and ×42 times faster than MCNPX. These speedup factors were doubled on the dual-GPU system. The dose Result was benchmarked against MCNPX and a maximum difference of 1% was observed when the relative error is kept below 0.1%.
A GPU-based MC code was developed for dose calculations using detailed patient and CT scanner models. Efficiency and accuracy were both guaranteed in this code. Scalability of the code was confirmed on the dual-GPU system.
开发一种基于图形处理单元（GPU）的蒙特卡罗（MC）代码，以加速在双GPU系统上的剂量计算。
我们模拟了一例前列腺癌治疗的临床病例。使用从120层CT切片导出的体素化腹部体模，其包含218×126×60个体素，并对GE LightSpeed 16层MDCT扫描仪进行了建模。首先用C++开发了MC代码的CPU版本，并在英特尔至强X5660 2.8GHz CPU上进行了测试，然后使用CUDA C 4.1将其转换为GPU版本，并在双Tesla m 090 GPU系统上运行。该代码的特点是能自动将模拟任务分配到多个GPU上，以及能精确计算与能量和材料相关的截面。
为保证精度采用了双精度浮点格式。计算了直肠、前列腺、膀胱和股骨头的剂量。在单GPU上运行时，发现MC GPU代码比CPU代码快19倍，比MCNPX快42倍。在双GPU系统上，这些加速因子翻倍。将剂量结果与MCNPX进行了基准对比，当相对误差保持在0.1%以下时，观察到最大差异为1%。
开发了一种基于GPU的MC代码，用于使用详细的患者和CT扫描仪模型进行剂量计算。该代码保证了效率和准确性。在双GPU系统上证实了该代码的可扩展性。
