A performance evaluation on monte carlo simulation for radiation dosimetry using cell processor
A performance evaluation on monte carlo simulation for radiation dosimetry using cell processor
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DOI：
10.3233/jcm-2011-0358
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发表时间：
2011-01-01
影响因子：
0.5
通讯作者：
Chow, James C. L.
中科院分区：
文献类型：
--
作者：
Chow, James C. L.
本研究使用EGSnrc程式探讨细胞处理器在蒙地卡罗模拟中的效能。基于非正式的20-80规则的EGSnrc代码中的两个处理器密集型函数，即HOWNEAR和RANMAR GET的执行速度进行了测量，使用分析器gprof，它指定了函数的执行次数和总时间。这些功能在为Cell处理器设计的测试架构中使用Playstation 3（PS3）系统重新实现。这个特定的框架旨在将程序功能划分为两个隔离的分支代码，以便在系统中的powerPC处理元素（PPE）和协同处理元素（SPE）上执行。使用CPU和Cell处理器计算的光子和电子束在异质体模中的深度剂量分布进行了比较，结果无差异。结果发现，我们研究的算法可以在Cell处理器上并行化，只要EGSnrc的架构发生变化，使代码在PPE上初始化，并在PPE和SPE之间分割程序内的模拟循环的执行。由于发现EGSnrc性能目前受到使用Cell处理器的PPE的限制，因此PC的计算平台与图形处理单元或GPGPU上的通用编程耦合可以提供更可行的加速途径。
This study investigated the performance of Cell processor in Monte Carlo simulation using the EGSnrc code. The execution speeds of two processor-intensive functions namely, HOWNEAR and RANMAR GET in the EGSnrc code based on the informal 20-80 rule were measured, using the profiler gprof, which specified the number of executions and total time spent in the function. The functions were re-implemented in a testing architecture designed for Cell processor using a Playstation3 (PS3) system. This specific framework was designed to divide the program functionality in two-isolating branching code for execution on the powerPC processing element (PPE) and synergistic processing elements (SPEs) in the system. Depth dose profiles in heterogeneous phantoms using photon and electron beams calculated by a CPU and Cell processor were compared and there was no difference in the results. It was found that our examined algorithms could be parallelizable on the Cell processor, provided that an architectural change of the EGSnrc was made so that the code was initialized on the PPE, and execution of the simulation loop within the program be split between the PPE and SPE. Since it was found that the EGSnrc performance was currently limited by the PPE using the Cell processor, a computing platform of PC coupled with a general purpose programming on graphics processing units or GPGPU may provide a more viable avenue for acceleration.