Doerner Edgardo, Caprile Paola
Institute of Physics, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860, Santiago, 7820436, Chile.
Med Phys. 2018 Jun 5. doi: 10.1002/mp.13033.
The purpose of this study was to present a parallel solution for the EGSnrc Monte Carlo code system combining MPI and OpenMP programming models as an alternative to the provided implementation, based on the use of a batch-queueing system (BQS).
Relying on a previous implementation based on OpenMP by E. Doerner and P. Caprile [Med. Phys. 44, 6672 (2017)], this work incorporates MPI features to efficiently distribute the simulation on current high-performance computing (HPC) systems. These features are introduced through properly defined macros, which are enabled depending on the compilation flags given by the user. The presented solution was benchmarked using the DOSXYZnrc code for a 6 MV clinical photon beam impinging on an homogeneous water phantom.
The platform validation against the serial run results confirmed that the introduction of new features does not modify the final dose distribution. The performance tests indicated that the new implementation was able to handle efficiently the workload distribution among the computing units available. Using all the resources available, the hybrid simulation was 10% faster than the MPI only solution and 30% faster than the BQS implementation.
The hybrid method presented is a viable solution to parallelize MC simulations using the EGSnrc codes in distributed computing systems in an simple and efficient way, taking advantage of the available resources and giving the user the possibility of choosing between different parallelization schemes (only OpenMP/MPI or a combination of both).
本研究的目的是为EGSnrc蒙特卡罗代码系统提供一种并行解决方案，该方案结合MPI和OpenMP编程模型，作为基于批处理排队系统（BQS）的现有实现的替代方案。
基于E. Doerner和P. Caprile先前基于OpenMP的实现[《医学物理》44, 6672 (2017)]，本工作纳入MPI功能，以便在当前的高性能计算（HPC）系统上高效地分布模拟。这些功能通过适当定义的宏引入，这些宏根据用户给出的编译标志启用。使用DOSXYZnrc代码对6兆伏临床光子束撞击均匀水模体的情况对所提出的解决方案进行了基准测试。
与串行运行结果的平台验证证实，新功能的引入不会改变最终剂量分布。性能测试表明，新实现能够有效地处理可用计算单元之间的工作负载分布。使用所有可用资源时，混合模拟比仅使用MPI的解决方案快10%，比BQS实现快30%。
所提出的混合方法是一种可行的解决方案，可在分布式计算系统中以简单有效的方式使用EGSnrc代码并行化蒙特卡罗模拟，利用可用资源，并为用户提供在不同并行化方案（仅OpenMP/MPI或两者结合）之间进行选择的可能性。
